Department of
Artificial Intelligence & Machine Learning

About the AIML department

The Department of AIML Engineering was established in the year 2023 with an intake of 60students for  Undergraduate program.

The department has well-equipped, Laboratories, qualified and experienced faculty members, and excellent infrastructure.

The Department has good academic curriculum. It is one of the most popular courses among engineering students.

Our AIML Department is at the forefront of technological innovation, dedicated to shaping future leaders in the field.

The syllabus is designed by Visvesvaraya Technological University includes the following areas of learning:

Core Areas of Learning:

 Mathematics–3 (Computer Science), random variables, probability distributions,
Statistical Inference 1, Statistical Inference 2, Design of Experiments & ANOVA
 Digital Design and Computer Organization, Introduction to Digital Design,
Combinational Logic, Basic Structure of Computers, Input/output Organization, Basic
Processing Unit.
 OPERATING SYSTEMS: Introduction to operating systems, System structures,
Process Management, Process Synchronization, Memory Management, File System,
Implementation of File System.
 Data Structures Applications Using ‘C’, Introduction To Data Structures, Stacks,
Queues, Linked Lists, Trees, Graphs. Hashing.
 Python Programming for Data Science , Introduction to python, Decision structure,
Lists,The NumPy Library, The pandas Library, The pandas : Reading and Writing
data.
 Data Analytics with Excel, To Apply analysis techniques to datasets in Excel , Learn
how to use Pivot Tables and Pivot Charts to streamline your workflow in Excel ,
Understand and Identify the principles of data analysis, Become adept at using Excel
functions and ,Techniques for analysis , Build presentation ready dashboards in Excel.

Other optional courses :
 Personality and Soft Skills Development
Methods of Teaching/Departmental Initiatives:
 Lecture Mode
 Power Point Presentations
 Assignments – Internal assessment Papers
 Seminars
 Organized Hackthon -EPICTHON
 Conducts value added course

VISION

To empower students to become AI and ML professionals, driving industry innovation and positively impacting society through cutting-edge technologies.

MISSION

• To develop state of the art academic and infrastructural facilities with modern equipment and E-learning resources to produce self-sustainable professional in the field of Artificial Intelligence and Machine Learning.
• To collaborate with Industry through projects-based learning, internships enabling the students to explore, apply various directions of learning.
• To impart premier quality, skill-based and value-based education to the students in the field of Artificial Intelligence and Machine Learning.
• To cultivate a research-oriented mindset in students, encouraging them to create applications that have practical value and make a positive impact on society.

Laboratory Details 

Annexure-II 1  

Mathematics for Computer Science Semester 3  Course Code BCS301 CIE Marks 50 Teaching Hours/Week (L: T:P: S) 3:2:0:0 SEE Marks 50 Total Hours of Pedagogy 40 hours Theory + 20 Hours Tutorial Total Marks 100 

Credits 04 Exam Hours 3  Examination type (SEE) Theory  

Course objectives: This course will enable the students to:  

1. To introduce the concept of random variables, probability distributions, specific discrete  and continuous distributions with practical application in Computer Science Engineering  and social life situations.  
2. To Provide the principles of statistical inferences and the basics of hypothesis testing with  emphasis on some commonly encountered hypotheses.  
3. To Determine whether an input has a statistically significant effect on the system’s  response through ANOVA testing.  

Teaching-Learning Process  

Pedagogy (General Instructions):  

Teachers can use the following strategies to accelerate the attainment of the various course  outcomes.  

1. In addition to the traditional lecture method, different types of innovative teaching methods  may be adopted so that the delivered lessons shall develop students’ theoretical and applied  Mathematical skills.  
2. State the need for Mathematics with Engineering Studies and Provide real-life examples.  3. Support and guide the students for self–study.  
3. You will assign homework, grading assignments and quizzes, and documenting students’  progress.  
4. Encourage the students to group learning to improve their creative and analytical skills.  6. Show short related video lectures in the following ways:  

• As an introduction to new topics (pre-lecture activity).  
• As a revision of topics (post-lecture activity).  
• As additional examples (post-lecture activity).  
• As an additional material of challenging topics (pre-and post-lecture activity).  • As a model solution of some exercises (post-lecture activity). 

Module-1: Probability Distributions 

Probability Distributions: Review of basic probability theory. Random variables (discrete  and continuous), probability mass and density functions. Mathematical expectation, mean and  variance. Binomial, Poisson and normal distributions- problems (derivations for mean and  standard deviation for Binomial and Poisson distributions only)-Illustrative examples.  Exponential distribution. (12  Hours) 

(RBT Levels: L1, L2 and L3) 

Pedagogy Chalk and Board, Problem-based learning  

Module-2: Joint probability distribution & Markov Chain 

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Annexure-II 2  

Joint probability distribution: Joint Probability distribution for two discrete random  variables, expectation, covariance and correlation.  

Markov Chain: Introduction to Stochastic Process, Probability Vectors, Stochastic matrices,  Regular stochastic matrices, Markov chains, Higher transition probabilities, Stationary  distribution of Regular Markov chains and absorbing states. (12  Hours) 

 (RBT Levels: L1, L2 and L3)  

Pedagogy Chalk and Board, Problem-based learning  

Module-3: Statistical Inference 1 

Introduction, sampling distribution, standard error, testing of hypothesis, levels of significance,  test of significances, confidence limits, simple sampling of attributes, test of significance for  large samples, comparison of large samples. (12  Hours) 

(RBT Levels: L1, L2 and L3)  

Pedagogy Chalk and Board, Problem-based learning  

Module-4: Statistical Inference 2 

Sampling variables, central limit theorem and confidences limit for unknown mean. Test of  Significance for means of two small samples, students ‘t’ distribution, Chi-square distribution  as a test of goodness of fit. F-Distribution. (12  Hours) 

 (RBT Levels: L1, L2 and L3) 

Pedagogy Chalk and Board, Problem-based learning  

Module-5: Design of Experiments & ANOVA 

Principles of experimentation in design, Analysis of completely randomized design,  randomized block design. The ANOVA Technique, Basic Principle of ANOVA, One-way  ANOVA, Two-way ANOVA, Latin-square Design, and Analysis of Co-Variance.  (12 Hours) 

(RBT Levels: L1, L2 and L3)  

Pedagogy Chalk and Board, Problem-based learning  

Course outcome (Course Skill Set)  

At the end of the course, the student will be able to:  

1. Explain the basic concepts of probability, random variables, probability distribution  2. Apply suitable probability distribution models for the given scenario.  
2. Apply the notion of a discrete-time Markov chain and n-step transition probabilities to  solve the given problem  
3. Use statistical methodology and tools in the engineering problem-solving process.  5. Compute the confidence intervals for the mean of the population.  
4. Apply the ANOVA test related to engineering problems.  

Assessment Details (both CIE and SEE)  

The weightage of Continuous Internal Evaluation (CIE) is 50% and for Semester End Exam (SEE)  is 50%. The minimum passing mark for the CIE is 40% of the maximum marks (20 marks out of  50) and for the SEE minimum passing mark is 35% of the maximum marks (18 out of 50 marks).  A student shall be deemed to have satisfied the academic requirements and earned the credits  allotted to each subject/ course if the student secures a minimum of 40% (40 marks out of 100) in  the sum total of the CIE (Continuous Internal Evaluation) and SEE (Semester End Examination)  taken together.  

Continuous Internal Evaluation:  

• For the Assignment component of the CIE, there are 25 marks and for the Internal Assessment  

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Test component, there are 25 marks.  

Annexure-II 3  

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• The first test will be administered after 40-50% of the syllabus has been covered, and the  second test will be administered after 85-90% of the syllabus has been covered  
• Any two assignment methods mentioned in the 22OB2.4, if an assignment is project-based  then only one assignment for the course shall be planned. The teacher should not conduct two  assignments at the end of the semester if two assignments are planned.  
• For the course, CIE marks will be based on a scaled-down sum of two tests and other methods  of assessment.  

Internal Assessment Test question paper is designed to attain the different levels of Bloom’s  taxonomy as per the outcome defined for the course.  

Semester-End Examination:  

Theory SEE will be conducted by the University as per the scheduled timetable, with common  question papers for the course (duration 03 hours).  

1. The question paper will have ten questions. Each question is set for 20 marks.  2. There will be 2 questions from each module. Each of the two questions under a module (with  a maximum of 3 sub-questions), should have a mix of topics under that module.  3. The students have to answer 5 full questions, selecting one full question from each module.  Marks scored shall be proportionally reduced to 50 marks. 

Suggested Learning Resources:  

Textbooks:  

1. Ronald E. Walpole, Raymond H Myers, Sharon L Myers & Keying Ye “Probability &  Statistics for Engineers & Scientists”, Pearson Education, 9th edition, 2017. 2. Peter Bruce, Andrew Bruce & Peter Gedeck “Practical Statistics for Data  Scientists” O’Reilly Media, Inc., 2nd edition 2020. 

Reference Books: (Name of the author/Title of the Book/ Name of the publisher/Edition and  Year) 

1. Erwin Kreyszig, “Advanced Engineering Mathematics”, John Wiley & Sons,  9th Edition, 2006.  
2. B. S. Grewal “Higher Engineering Mathematics”, Khanna publishers, 44th Ed., 2021.  3. G Haribaskaran “Probability, Queuing Theory & Reliability Engineering”, Laxmi  Publication, Latest Edition, 2006 
3. Irwin Miller & Marylees Miller, John E. Freund’s “Mathematical Statistics with  Applications” Pearson. Dorling Kindersley Pvt. Ltd. India, 8th edition, 2014.  5. S C Gupta and V K Kapoor, “Fundamentals of Mathematical Statistics”, S Chand and  Company, Latest edition.  
4. Robert V. Hogg, Joseph W. McKean & Allen T. Craig. “Introduction to  Mathematical Statistics”, Pearson Education 7th edition, 2013.  
5. Jim Pitman. Probability, Springer-Verlag, 1993.  
6. Sheldon M. Ross, “Introduction to Probability Models” 11th edition. Elsevier, 2014.  9. A. M. Yaglom and I. M. Yaglom, “Probability and Information”. D. Reidel Publishing  Company. Distributed by Hindustan Publishing Corporation (India) Delhi, 1983.  10. P. G. Hoel, S. C. Port and C. J. Stone, “Introduction to Probability Theory”, Universal  Book Stall, (Reprint), 2003.  
7. S. Ross, “A First Course in Probability”, Pearson Education India, 6th Ed., 2002.  12. W. Feller, “An Introduction to Probability Theory and its Applications”, Vol. 1, Wiley, 3rd  

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Ed., 1968.  

Annexure-II 4  

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13. N.P. Bali and Manish Goyal, A Textbook of Engineering Mathematics, Laxmi  Publications, Reprint, 2010.  
14. Veerarajan T, Engineering Mathematics (for semester III), Tata McGraw-Hill, New  Delhi, 2010  

Web links and Video Lectures (e-Resources):  

http://nptel.ac.in/courses.php?disciplineID=111  

http://www.class-central.com/subject/math(MOOCs)  

http://academicearth.org/  

http://www.bookstreet.in. 

VTU EDUSAT PROGRAMME – 20  

 VTU e-Shikshana Program  

Activity-Based Learning (Suggested Activities in Class)/Practical-Based Learning  

• Programming Assignment  
• Seminars 

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MKV-TEMPLATE for IPCC (26.04.2022) Annexure-III  

Digital Design and Computer Organization Semester 3  Course Code BCS302 CIE Marks 50 Teaching Hours/Week (L:T:P: S) 3:0:2:0 SEE Marks 50 Total Hours of Pedagogy 40 hours Theory + 20 Hours of Practicals Total Marks 100 

Credits 04 Exam Hours 3  Examination nature (SEE) Theory  

Course objectives:  

• To demonstrate the functionalities of binary logic system  
• To explain the working of combinational and sequential logic system  
• To realize the basic structure of computer system  
• To illustrate the working of I/O operations and processing unit  

Teaching-Learning Process (General Instructions)  

These are sample Strategies; that teachers can use to accelerate the attainment of the various course outcomes.  1. Chalk and Talk 

2. Live Demo with experiments 
3. Power point presentation 

 MODULE-1 8 Hr  Introduction to Digital Design: Binary Logic, Basic Theorems And Properties Of Boolean Algebra,  Boolean Functions, Digital Logic Gates, Introduction, The Map Method, Four-Variable Map, Don’t-Care  Conditions, NAND and NOR Implementation, Other Hardware Description Language – Verilog Model of a  simple circuit.  

Text book 1: 1.9, 2.4, 2.5, 2.8, 3.1, 3.2, 3.3, 3.5, 3.6, 3.9  

 MODULE-2 8 Hr  Combinational Logic: Introduction, Combinational Circuits, Design Procedure, Binary Adder- Subtractor,  Decoders, Encoders, Multiplexers. HDL Models of Combinational Circuits – Adder, Multiplexer, Encoder. Sequential Logic: Introduction, Sequential Circuits, Storage Elements: Latches, Flip-Flops.  

Text book 1: 4.1, 4.2, 4.4, 4.5, 4.9, 4.10, 4.11, 4.12, 5.1, 5.2, 5.3, 5.4.  

 MODULE-3 8 Hr  Basic Structure of Computers: Functional Units, Basic Operational Concepts, Bus structure, Performance – Processor Clock, Basic Performance Equation, Clock Rate, Performance Measurement.Machine  Instructions and Programs: Memory Location and Addresses, Memory Operations, Instruction and  Instruction sequencing, Addressing Modes.  

Text book 2: 1.2, 1.3, 1.4, 1.6, 2.2, 2.3, 2.4, 2.5  

 MODULE-4 8 Hr  

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Input/output Organization: Accessing I/O Devices, Interrupts – Interrupt Hardware, Enabling and Disabling  Interrupts, Handling Multiple Devices, Direct Memory Access: Bus Arbitration, Speed, size and Cost of  memory systems. Cache Memories – Mapping Functions.  

Text book 2: 4.1, 4.2.1, 4.2.2, 4.2.3, 4.4, 5.4, 5.5.1  

 MODULE-5 8 Hr 

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MKV-TEMPLATE for IPCC (26.04.2022) Annexure-III  

Basic Processing Unit: Some Fundamental Concepts: Register Transfers, Performing ALU operations,  fetching a word from Memory, Storing a word in memory. Execution of a Complete Instruction. Pipelining:  Basic concepts, Role of Cache memory, Pipeline Performance.  

Text book 2: 7.1, 7.2, 8.1 

PRACTICAL COMPONENT OF IPCC 

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Experiments  

Simulation packages preferred: Multisim, Modelsim, PSpice or any other relevant O  

1 Given a 4-variable logic expression, simplify it using appropriate technique and simulate the same  using basic gates. 

2 Design a 4 bit full adder and subtractor and simulate the same using basic gates. 3 Design Verilog HDL to implement simple circuits using structural, Data flow and Behavioural model.  

4 Design Verilog HDL to implement Binary Adder-Subtractor – Half and Full Adder, Half and Full  Subtractor.  

5 Design Verilog HDL to implement Decimal adder. 

6 Design Verilog program to implement Different types of multiplexer like 2:1, 4:1 and 8:1. 7 Design Verilog program to implement types of De-Multiplexer.  

8 Design Verilog program for implementing various types of Flip-Flops such as SR, JK and D. 

Course outcomes (Course Skill Set):  

At the end of the course, the student will be able to:  

CO1: Apply the K–Map techniques to simplify various Boolean expressions.  

CO2: Design different types of combinational and sequential circuits along with Verilog programs.  CO3: Describe the fundamentals of machine instructions, addressing modes and Processor performance.  CO4: Explain the approaches involved in achieving communication between processor and I/O devices.  CO5:Analyze internal Organization of Memory and Impact of cache/Pipelining on Processor Performance.  Assessment Details (both CIE and SEE)  

The weightage of Continuous Internal Evaluation (CIE) is 50% and for Semester End Exam (SEE) is 50%.  The minimum passing mark for the CIE is 40% of the maximum marks (20 marks out of 50) and for the  SEE minimum passing mark is 35% of the maximum marks (18 out of 50 marks). A student shall be  deemed to have satisfied the academic requirements and earned the credits allotted to each subject/  course if the student secures a minimum of 40% (40 marks out of 100) in the sum total of the CIE  (Continuous Internal Evaluation) and SEE (Semester End Examination) taken together.  

CIE for the theory component of the IPCC (maximum marks 50)  

• IPCC means practical portion integrated with the theory of the course.  
• CIE marks for the theory component are 25 marks and that for the practical component is 25  marks.  
• 25 marks for the theory component are split into 15 marks for two Internal Assessment Tests (Two  Tests, each of 15 Marks with 01-hour duration, are to be conducted) and 10 marks for other  

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MKV-TEMPLATE for IPCC (26.04.2022) Annexure-III  

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assessment methods mentioned in 22OB4.2. The first test at the end of 40-50% coverage of the  syllabus and the second test after covering 85-90% of the syllabus.  

• Scaled-down marks of the sum of two tests and other assessment methods will be CIE marks for the  theory component of IPCC (that is for 25 marks).  
• The student has to secure 40% of 25 marks to qualify in the CIE of the theory component of IPCC.  CIE for the practical component of the IPCC  
• 15 marks for the conduction of the experiment and preparation of laboratory record, and 10 marks for the test to be conducted after the completion of all the laboratory sessions.  
• On completion of every experiment/program in the laboratory, the students shall be evaluated  including viva-voce and marks shall be awarded on the same day.  
• The CIE marks awarded in the case of the Practical component shall be based on the continuous  evaluation of the laboratory report. Each experiment report can be evaluated for 10 marks. Marks of  all experiments’ write-ups are added and scaled down to 15 marks.  
• The laboratory test (duration 02/03 hours) after completion of all the experiments shall be  conducted for 50 marks and scaled down to 10 marks. 
• Scaled-down marks of write-up evaluations and tests added will be CIE marks for the laboratory  component of IPCC for 25 marks.  
• The student has to secure 40% of 25 marks to qualify in the CIE of the practical component of the  IPCC.  

SEE for IPCC  

Theory SEE will be conducted by University as per the scheduled timetable, with common question  papers for the course (duration 03 hours) 

1. The question paper will have ten questions. Each question is set for 20 marks.  2. There will be 2 questions from each module. Each of the two questions under a module (with a  maximum of 3 sub-questions), should have a mix of topics under that module.  3. The students have to answer 5 full questions, selecting one full question from each module.  4. Marks scored by the student shall be proportionally scaled down to 50 Marks  The theory portion of the IPCC shall be for both CIE and SEE, whereas the practical portion will  have a CIE component only. Questions mentioned in the SEE paper may include questions from  the practical component. 

Suggested Learning Resources: 

Books 

1. M. Morris Mano & Michael D. Ciletti, Digital Design With an Introduction to Verilog Design, 5e,  Pearson Education.  
2. Carl Hamacher, ZvonkoVranesic, SafwatZaky, Computer Organization, 5th Edition, Tata McGraw  Hill.  

Web links and Video Lectures (e-Resources):  

https://cse11-iiith.vlabs.ac.in/ 

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MKV-TEMPLATE for IPCC (26.04.2022) Annexure-III  

Activity Based Learning (Suggested Activities in Class)/ Practical Based learning  Assign the group task to Design the various types of counters and display the output accordingly  

Assessment Methods  

• Lab Assessment (25 Marks)  
• GATE Based Aptitude Test  

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MKV-TEMPLATE for IPCC (26.04.2022) Annexure-III  

OPERATING SYSTEMS Semester 3  

Course Code BCS303 CIE Marks 50  Teaching Hours/Week (L:T:P: S) 3:0:2:0 SEE Marks 50  Total Hours of Pedagogy 40 hours Theory + 20 hours practicals Total Marks 100  Credits 04 Exam Hours 3  Examination nature (SEE) Theory 

Course objectives:  

• To Demonstrate the need for OS and different types of OS  
• To discuss suitable techniques for management of different resources  
• To demonstrate different APIs/Commands related to processor,  

memory, storage and file system management.  

Teaching-Learning Process (General Instructions)  

Teachers can use the following strategies to accelerate the attainment of the various course outcomes.  1. Lecturer methods (L) need not to be only traditional lecture method, but alternative effective  teaching methods could be adopted to attain the outcomes.  

2. Use of Video/Animation to explain functioning of various concepts.  
3. Encourage collaborative (Group Learning) Learning in the class.  
4. Adopt Problem Based Learning (PBL), which fosters students’ Analytical skills, develop design  thinking skills such as the ability to design, evaluate, generalize, and analyze information rather  than simply recall it.  
5. Role play for process scheduling.  
6. Demonstrate the installation of any one Linux OS on VMware/Virtual Box  

 MODULE-1 8 Hours  Introduction to operating systems, System structures: What operating systems do; Computer System  organization; Computer System architecture; Operating System structure; Operating System operations;  Process management; Memory management; Storage management; Protection and Security; Distributed  system; Special-purpose systems; Computing environments.  

Operating System Services: User – Operating System interface; System calls; Types of system calls;  System programs; Operating system design and implementation; Operating System structure; Virtual  machines; Operating System debugging, Operating System generation; System boot.  

Textbook 1: Chapter – 1 (1.1-1.12), 2 (2.2-2.11)  

 MODULE-2 8 Hours  Process Management: Process concept; Process scheduling; Operations on processes; Inter process  communication 

 Multi-threaded Programming: Overview; Multithreading models; Thread Libraries; Threading issues.    

 Process Scheduling: Basic concepts; Scheduling Criteria; Scheduling Algorithms; Thread scheduling;  Multiple-processor scheduling,  

Textbook 1: Chapter – 3 (3.1-3.4), 4 (4.1-4.4), 5 (5.1 -5.5) 

 MODULE-3 8 Hours  

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MKV-TEMPLATE for IPCC (26.04.2022) Annexure-III  

Process Synchronization: Synchronization: The critical section problem; Peterson’s solution;  Synchronization hardware; Semaphores; Classical problems of synchronization; 

Deadlocks: System model; Deadlock characterization; Methods for handling deadlocks; Deadlock  prevention; Deadlock avoidance; Deadlock detection and recovery from deadlock.  

Textbook 1: Chapter – 6 (6.1-6.6), 7 (7.1 -7.7)  

 MODULE-4 8 Hours  

Memory Management: Memory management strategies: Background; Swapping; Contiguous memory  allocation; Paging; Structure of page table; Segmentation.  

Virtual Memory Management: Background; Demand paging; Copy-on-write; Page replacement;  Allocation of frames; Thrashing.  

Textbook 1: Chapter -8 (8.1-8.6), 9 (9.1-9.6)  

 MODULE-5 8 Hours File System, Implementation of File System: File system: File concept; Access methods; Directory and  Disk structure; File system mounting; File sharing; Implementing File system: File system structure; File  system implementation; Directory implementation; Allocation methods; Free space management. 

Secondary Storage Structure, Protection: Mass storage structures; Disk structure; Disk attachment; Disk  scheduling; Disk management; Protection: Goals of protection, Principles of protection, Domain of  protection, Access matrix. 

Textbook 1: Chapter – 10 (10.1-10.5) ,11 (11.1-11.5),12 (12.1-12.5), 14 (14.1-14.4)    

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MKV-TEMPLATE for IPCC (26.04.2022) Annexure-III  

PRACTICAL COMPONENT OF IPCC(May cover all / major modules)  

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Sl.N O 

Experiments 

1 Develop a c program to implement the Process system calls (fork (), exec(), wait(), create process,  terminate process) 

2 Simulate the following CPU scheduling algorithms to find turnaround time and waiting time a) FCFS  b) SJF c) Round Robin d) Priority. 

3 Develop a C program to simulate producer-consumer problem using semaphores. 

4 Develop a C program which demonstrates interprocess communication between a reader  process and a writer process. Use mkfifo, open, read, write and close APIs in your program.  5Develop a C program to simulate Bankers Algorithm for DeadLock Avoidance. 

6 Develop a C program to simulate the following contiguous memory allocation Techniques:  a) Worst fit b) Best fit c) First fit. 

7 Develop a C program to simulate page replacement algorithms:  

1. a) FIFO b) LRU 

8 Simulate following File Organization Techniques  

1. a) Single level directory b) Two level directory 

9 Develop a C program to simulate the Linked file allocation strategies. 

10 Develop a C program to simulate SCAN disk scheduling algorithm. 

Course outcomes (Course Skill Set):  

At the end of the course, the student will be able to: 

CO 1. Explain the structure and functionality of operating system  

CO 2. Apply appropriate CPU scheduling algorithms for the given problem.  

CO 3. Analyse the various techniques for process synchronization and deadlock handling.  CO 4. Apply the various techniques for memory management  

CO 5. Explain file and secondary storage management strategies.  

CO 6. Describe the need for information protection mechanisms  

Assessment Details (both CIE and SEE)  

The weightage of Continuous Internal Evaluation (CIE) is 50% and for Semester End Exam (SEE) is 50%. The  minimum passing mark for the CIE is 40% of the maximum marks (20 marks out of 50) and for the SEE  minimum passing mark is 35% of the maximum marks (18 out of 50 marks). A student shall be deemed to  have satisfied the academic requirements and earned the credits allotted to each subject/ course if the student  secures a minimum of 40% (40 marks out of 100) in the sum total of the CIE (Continuous Internal Evaluation)  and SEE (Semester End Examination) taken together.  

CIE for the theory component of the IPCC (maximum marks 50)  

• IPCC means practical portion integrated with the theory of the course.  
• CIE marks for the theory component are 25 marks and that for the practical component is 25 marks.  
• 25 marks for the theory component are split into 15 marks for two Internal Assessment Tests (Two Tests,  each of 15 Marks with 01-hour duration, are to be conducted) and 10 marks for other assessment methods  

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MKV-TEMPLATE for IPCC (26.04.2022) Annexure-III  

mentioned in 22OB4.2. The first test at the end of 40-50% coverage of the syllabus and the second test  after covering 85-90% of the syllabus.  

• Scaled-down marks of the sum of two tests and other assessment methods will be CIE marks for the theory component of IPCC (that is for 25 marks).  
• The student has to secure 40% of 25 marks to qualify in the CIE of the theory component of IPCC.  CIE for the practical component of the IPCC 
• 15 marks for the conduction of the experiment and preparation of laboratory record, and 10 marks for the  test to be conducted after the completion of all the laboratory sessions.  
• On completion of every experiment/program in the laboratory, the students shall be evaluated including  viva-voce and marks shall be awarded on the same day.  
• The CIE marks awarded in the case of the Practical component shall be based on the continuous evaluation  of the laboratory report. Each experiment report can be evaluated for 10 marks. Marks of all experiments’ write-ups are added and scaled down to 15 marks.  
• The laboratory test (duration 02/03 hours) after completion of all the experiments shall be conducted for  50 marks and scaled down to 10 marks. 
• Scaled-down marks of write-up evaluations and tests added will be CIE marks for the laboratory  component of IPCC for 25 marks. 
• The student has to secure 40% of 25 marks to qualify in the CIE of the practical component of the IPCC. SEE for IPCC  

Theory SEE will be conducted by University as per the scheduled timetable, with common question papers for  the course (duration 03 hours) 

1. The question paper will have ten questions. Each question is set for 20 marks.  
2. There will be 2 questions from each module. Each of the two questions under a module (with a maximum  of 3 sub-questions), should have a mix of topics under that module. 
3. The students have to answer 5 full questions, selecting one full question from each module. 4. Marks scoredby the student shall be proportionally scaled down to 50 Marks 

The theory portion of the IPCC shall be for both CIE and SEE, whereas the practical portion will have a  CIE component only. Questions mentioned in the SEE paper may include questions from the practical  component. 

Suggested Learning Resources: 

Textbooks  

1. Abraham Silberschatz, Peter Baer Galvin, Greg Gagne, Operating System Principles 8th edition,  Wiley-India, 2015  

Reference Books 

1. Ann McHoes Ida M Fylnn, Understanding Operating System, Cengage Learning, 6th Edition   2. D.M Dhamdhere, Operating Systems: A Concept Based Approach 3rd Ed, McGraw- Hill, 2013.  3. P.C.P. Bhatt, An Introduction to Operating Systems: Concepts and Practice 4th Edition, PHI(EEE),  2014.  
2. William Stallings Operating Systems: Internals and Design Principles, 6th Edition, Pearson.  Web links and Video Lectures (e-Resources):  
3. https://youtu.be/mXw9ruZaxzQ 

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MKV-TEMPLATE for IPCC (26.04.2022) Annexure-III  

2. https://youtu.be/vBURTt97EkA 
3. https://www.youtube.com/watch?v=783KAB 

tuE4&list=PLIemF3uozcAKTgsCIj82voMK3TMR0YE_f  

4. https://www.youtube.com/watch?v=3- 

ITLMMeeXY&list=PL3pGy4HtqwD0n7bQfHjPnsWzkeRn6mkO  

Activity Based Learning (Suggested Activities in Class)/ Practical Based learning 

• Assessment Methods  

o Case Study on Unix Based Systems (10 Marks)  

o Lab Assessment (25 Marks)  

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DATA STRUCTURES AND APPLICATIONS Semester 3  

Course Code BCS304 CIE Marks 50 Teaching Hours/Week (L: T:P: S) 3:0:0:0 SEE Marks 50 Total Hours of Pedagogy 40 Total Marks 100 Credits 03 Exam Hours 3  Examination type (SEE) Theory  

Course objectives:  

CLO 1. To explain fundamentals of data structures and their applications.  

CLO 2. To illustrate representation of Different data structures such as Stack, Queues, Linked  Lists, Trees and Graphs.  

CLO 3. To Design and Develop Solutions to problems using Linear Data Structures  CLO 4. To discuss applications of Nonlinear Data Structures in problem solving.  CLO 5. To introduce advanced Data structure concepts such as Hashing and Optimal Binary  Search Trees  

Teaching-Learning Process (General Instructions)  

Teachers can use following strategies to accelerate the attainment of the various course outcomes.  1. Chalk and Talk with Black Board 

2. ICT based Teaching 
3. Demonstration based Teaching 

 Module-1 8Hours  INTRODUCTION TO DATA STRUCTURES: Data Structures, Classifications (Primitive  & Non-Primitive), Data structure Operations 

Review of pointers and dynamic Memory Allocation,  

ARRAYS and STRUCTURES: Arrays, Dynamic Allocated Arrays, Structures and Unions,  Polynomials, Sparse Matrices, representation of Multidimensional Arrays, Strings  STACKS: Stacks, Stacks Using Dynamic Arrays, Evaluation and conversion of Expressions Text Book: Chapter-1:1.2 Chapter-2: 2.1 to 2.7 Chapter-3: 3.1,3.2,3.6  

Reference Book 1: 1.1 to 1.4  

 Module-2 8Hours  QUEUES: Queues, Circular Queues, Using Dynamic Arrays, Multiple Stacks and queues. LINKED LISTS : Singly Linked, Lists and Chains, Representing Chains in C, Linked  Stacks and Queues, Polynomials  

Text Book: Chapter-3: 3.3, 3.4, 3.7 Chapter-4: 4.1 to 4.4  

 Module-3 8Hours  LINKED LISTS : Additional List Operations, Sparse Matrices, Doubly Linked List. TREES: Introduction, Binary Trees, Binary Tree Traversals, Threaded Binary Trees. Text Book: Chapter-4: 4.5,4.7,4.8 Chapter-5: 5.1 to 5.3, 5.5 

 Module-4 8Hours  TREES(Cont..): Binary Search trees, Selection Trees, Forests, Representation of Disjoint  sets, Counting Binary Trees,  

GRAPHS: The Graph Abstract Data Types, Elementary Graph Operations  

Text Book: Chapter-5: 5.7 to 5.11 Chapter-6: 6.1, 6.2  

 Module-5 8Hours  

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HASHING: Introduction, Static Hashing, Dynamic Hashing  

PRIORITY QUEUES: Single and double ended Priority Queues, Leftist Trees  

INTRODUCTION TO EFFICIENT BINARY SEARCH TREES: Optimal Binary Search  Trees  

Text Book: Chapter 8: 8.1 to 8.3 Chapter 9: 9.1, 9.2 Chapter 10: 10.1 

Course outcome (Course Skill Set)  

At the end of the course the student will be able to:  

CO 1. Explain different data structures and their applications.  

CO 2. Apply Arrays, Stacks and Queue data structures to solve the given problems.  CO 3. Use the concept of linked list in problem solving.  

CO 4. Develop solutions using trees and graphs to model the real-world problem.  CO 5. Explain the advanced Data Structures concepts such as Hashing Techniques and Optimal  Binary Search Trees.  

Assessment Details (both CIE and SEE)  

The weightage of Continuous Internal Evaluation (CIE) is 50% and for Semester End Exam (SEE) is  50%. The minimum passing mark for the CIE is 40% of the maximum marks (20 marks out of 50)  and for the SEE minimum passing mark is 35% of the maximum marks (18 out of 50 marks). A  student shall be deemed to have satisfied the academic requirements and earned the credits  allotted to each subject/ course if the student secures a minimum of 40% (40 marks out of 100) in  the sum total of the CIE (Continuous Internal Evaluation) and SEE (Semester End Examination)  taken together.  

Continuous Internal Evaluation:  

• For the Assignment component of the CIE, there are 25 marks and for the Internal Assessment  Test component, there are 25 marks.  
• The first test will be administered after 40-50% of the syllabus has been covered, and the  second test will be administered after 85-90% of the syllabus has been covered  
• Any two assignment methods mentioned in the 22OB2.4, if an assignment is project-based then  only one assignment for the course shall be planned. The teacher should not conduct two  assignments at the end of the semester if two assignments are planned.  
• For the course, CIE marks will be based on a scaled-down sum of two tests and other methods  of assessment.  

Internal Assessment Test question paper is designed to attain the different levels of Bloom’s  taxonomy as per the outcome defined for the course.  

Semester-End Examination:  

Theory SEE will be conducted by University as per the scheduled timetable, with common question papers  for the course (duration 03 hours).  

1. The question paper will have ten questions. Each question is set for 20 marks.  
2. There will be 2 questions from each module. Each of the two questions under a module (with a  maximum of 3 sub-questions), should have a mix of topics under that module.  
3. The students have to answer 5 full questions, selecting one full question from each module.  4. Marks scored shall be proportionally reduced to 50 marks. 

Suggested Learning Resources:  

Textbook: 

1. Ellis Horowitz, Sartaj Sahni and Susan Anderson-Freed, Fundamentals of Data Structures  in C, 2nd Ed, Universities Press, 2014 

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Reference Books: 

1. Seymour Lipschutz, Data Structures Schaum’s Outlines, Revised 1st Ed, McGraw Hill,  2014.  
2. Gilberg & Forouzan, Data Structures: A Pseudo-code approach with C, 2nd Ed, Cengage  Learning,2014.  
3. Reema Thareja, Data Structures using C, 3rd Ed, Oxford press, 2012.  
4. Jean-Paul Tremblay & Paul G. Sorenson, An Introduction to Data Structures with  Applications, 2nd Ed, McGraw Hill, 2013  
5. A M Tenenbaum, Data Structures using C, PHI, 1989  
6. Robert Kruse, Data Structures and Program Design in C, 2nd Ed, PHI, 1996.  

Web links and Video Lectures (e-Resources):  

• http://elearning.vtu.ac.in/econtent/courses/video/CSE/06CS35.html  
• https://nptel.ac.in/courses/106/105/106105171/  
• http://www.nptelvideos.in/2012/11/data-structures-and-algorithms.html  
• https://www.youtube.com/watch?v=3Xo6P_V-qns&t=201s  
• https://ds2-iiith.vlabs.ac.in/exp/selection-sort/index.html  
• https://nptel.ac.in/courses/106/102/106102064/  
• https://ds1-iiith.vlabs.ac.in/exp/stacks-queues/index.html  
• https://ds1-iiith.vlabs.ac.in/exp/linked-list/basics/overview.html  
• https://ds1-iiith.vlabs.ac.in/List%20of%20experiments.html  
• https://ds1-iiith.vlabs.ac.in/exp/tree-traversal/index.html  
• https://ds1-iiith.vlabs.ac.in/exp/tree-traversal/depth-first-traversal/dft-practice.html  
• https://infyspringboard.onwingspan.com/web/en/app/toc/lex_auth_013501595428077568125 59/overview 

Activity Based Learning (Suggested Activities in Class)/ Practical Based learning  

• Role Play  
• Flipped classroom  
• Assessment Methods for 25 Marks (opt two Learning Activities)  

o Case Study  

o Programming Assignment  

o Gate Based Aptitude Test  

o MOOC Assignment for selected Module  

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DATA STRUCTURES LABORATORY  

SEMESTER – III 

Course Code BCSL305 CIE Marks 50  Number of Contact Hours/Week 0:0:2 SEE Marks 50  Total Number of Lab Contact Hours 28 Exam Hours 03  Credits – 1  

Course Learning Objectives:  

This laboratory course enables students to get practical experience in design, develop, implement, analyze  and evaluation/testing of  

• Dynamic memory management 
• Linear data structures and their applications such as stacks, queues and lists 
• Non-Linear data structures and their applications such as trees and graphs 

Descriptions (if any):  

• Implement all the programs in “C ” Programming Language and Linux OS. 

Programs List:  

1. Develop a Program in C for the following:  
2. a) Declare a calendar as an array of 7 elements (A dynamically Created array) to represent  7 days of a week. Each Element of the array is a structure having three fields. The first  

field is the name of the Day (A dynamically allocated String), The second field is the  

date of the Day (A integer), the third field is the description of the activity for a  

particular day (A dynamically allocated String).  

1. b) Write functions create(), read() and display(); to create the calendar, to read the data  from the keyboard and to print weeks activity details report on screen.  

2. Develop a Program in C for the following operations on Strings.  
3. Read a main String (STR), a Pattern String (PAT) and a Replace String (REP) 
4. Perform Pattern Matching Operation: Find and Replace all occurrences of PAT in  STR with REP if PAT exists in STR. Report suitable messages in case PAT does not  

exist in STR 

Support the program with functions for each of the above operations. Don’t use Built-in  functions.  

3. Develop a menu driven Program in C for the following operations on STACK of Integers  (Array Implementation of Stack with maximum size MAX)  
4. Push an Element on to Stack 
5. Pop an Element from Stack 
6. Demonstrate how Stack can be used to check Palindrome 
7. Demonstrate Overflow and Underflow situations on Stack 
8. Display the status of Stack 
9. Exit 

Support the program with appropriate functions for each of the above operations  

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4. Develop a Program in C for converting an Infix Expression to Postfix Expression. Program  should support for both parenthesized and free parenthesized  

expressions with the operators: +, -, *, /, % (Remainder), ^ (Power) and alphanumeric  operands.  

5. Develop a Program in C for the following Stack Applications  
6. Evaluation of Suffix expression with single digit operands and operators: +, -, *, /, %, ^  
7. Solving Tower of Hanoi problem with n disks 
8. Develop a menu driven Program in C for the following operations on Circular QUEUE of  Characters (Array Implementation of Queue with maximum size MAX)  
9. Insert an Element on to Circular QUEUE 
10. Delete an Element from Circular QUEUE 
11. Demonstrate Overflow and Underflow situations on Circular QUEUE 
12. Display the status of Circular QUEUE 
13. Exit 

Support the program with appropriate functions for each of the above operations  

7. Develop a menu driven Program in C for the following operations on Singly Linked List  (SLL) of Student Data with the fields: USN, Name, Programme, Sem,  

PhNo  

1. Create a SLL of N Students Data by using front insertion. 
2. Display the status of SLL and count the number of nodes in it 
3. Perform Insertion / Deletion at End of SLL 
4. Perform Insertion / Deletion at Front of SLL(Demonstration of stack) 
5. Exit 
6. Develop a menu driven Program in C for the following operations on Doubly Linked List  (DLL) of Employee Data with the fields: SSN, Name, Dept, Designation,  

Sal, PhNo  

1. Create a DLL of N Employees Data by using end insertion. 
2. Display the status of DLL and count the number of nodes in it 
3. Perform Insertion and Deletion at End of DLL 
4. Perform Insertion and Deletion at Front of DLL 
5. Demonstrate how this DLL can be used as Double Ended Queue. 
6. Exit 
7. Develop a Program in C for the following operationson Singly Circular Linked List (SCLL)  with header nodes  
8. Represent and Evaluate a Polynomial P(x,y,z) = 6x2y2z-4yz5+3x3yz+2xy5z-2xyz3
9. Find the sum of two polynomials POLY1(x,y,z) and POLY2(x,y,z) and store the  

result in POLYSUM(x,y,z) 

Support the program with appropriate functions for each of the above operations  

10. Develop a menu driven Program in C for the following operations on Binary Search Tree  (BST) of Integers .  
11. Create a BST of N Integers: 6, 9, 5, 2, 8, 15, 24, 14, 7, 8, 5, 2 
12. Traverse the BST in Inorder, Preorder and Post Order 
13. Search the BST for a given element (KEY) and report the appropriate message 
14. Exit 
15. Develop a Program in C for the following operations on Graph(G) of Cities  
16. Create a Graph of N cities using Adjacency Matrix. 
17. Print all the nodes reachable from a given starting node in a digraph using DFS/BFS  method 

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12. Given a File of N employee records with a set K of Keys (4-digit) which uniquely determine  the records in file F. Assume that file F is maintained in memory by a Hash Table (HT) of m  memory locations with L as the set of memory addresses (2-digit) of locations in HT. Let the  keys in K and addresses in L are Integers. Develop a Program in C that uses Hash function H:  

K →L as H(K)=K mod m (remainder method), and implement hashing  

technique to map a given key K to the address space L. Resolve the collision (if any) using  linear probing.  

Laboratory Outcomes: The student should be able to:  

• Analyze various linear and non-linear data structures 
• Demonstrate the working nature of different types of data structures and their applications ● Use appropriate searching and sorting algorithms for the give scenario. 
• Apply the appropriate data structure for solving real world problems 

Conduct of Practical Examination:  

• Experiment distribution 

o For laboratories having only one part: Students are allowed to pick one experiment from  the lot with equal opportunity. 

o For laboratories having PART A and PART B: Students are allowed to pick one  

experiment from PART A and one experiment from PART B, with equal opportunity. 

• Change of experiment is allowed only once and marks allotted for procedure to be made zero of  the changed part only. 
• Marks Distribution (Need to change in accordance with university regulations)  

1. c) For laboratories having only one part – Procedure + Execution + Viva-Voce: 15+70+15 =  100 Marks 
2. d) For laboratories having PART A and PART B 
3. Part A – Procedure + Execution + Viva = 6 + 28 + 6 = 40 Marks 
4. Part B – Procedure + Execution + Viva = 9 + 42 + 9 = 60 Marks 
   

Annexure-II 1  

Object Oriented Programming with JAVA Semester 3 Course Code BCS306A CIE Marks 50 Teaching Hours/Week (L: T:P: S) 2:0:2 SEE Marks 50 Total Hours of Pedagogy 28 Hours of Theory + 20 Hours of Practical Total Marks 100  Credits 03 Exam Hours 03 Examination type (SEE) Theory 

Note – Students who have undergone “ Basics of Java Programming BPLCK105C/205C” in first year are not eligible to opt this course 

Course objectives:  

• To learn primitive constructs JAVA programming language.  
• To understand Object Oriented Programming Features of JAVA.  
• To gain knowledge on: packages, multithreaded programing and exceptions. 

Teaching-Learning Process (General Instructions)  

These are sample Strategies, which teachers can use to accelerate the attainment of the various course  outcomes and make Teaching –Learning more effective  

1. Use Online Java Compiler IDE: https://www.jdoodle.com/online-java-compiler/ or any other.  2. Demonstration of programing examples.  
2. Chalk and board, power point presentations  
3. Online material (Tutorials) and video lectures. 

Module-1  

An Overview of Java: Object-Oriented Programming (Two Paradigms, Abstraction, The Three OOP  Principles), Using Blocks of Code, Lexical Issues (Whitespace, Identifiers, Literals, Comments,  Separators, The Java Keywords).  

Data Types, Variables, and Arrays: The Primitive Types (Integers, Floating-Point Types, Characters,  Booleans), Variables, Type Conversion and Casting, Automatic Type Promotion in Expressions, Arrays,  Introducing Type Inference with Local Variables.  

Operators: Arithmetic Operators, Relational Operators, Boolean Logical Operators, The Assignment  Operator, The ? Operator, Operator Precedence, Using Parentheses.  

Control Statements: Java’s Selection Statements (if, The Traditional switch), Iteration Statements  (while, do-while, for, The For-Each Version of the for Loop, Local Variable Type Inference in a for Loop,  Nested Loops), Jump Statements (Using break, Using continue, return).  

Chapter 2, 3, 4, 5 

Module-2  

Introducing Classes: Class Fundamentals, Declaring Objects, Assigning Object Reference Variables,  Introducing Methods, Constructors, The this Keyword, Garbage Collection. 

Methods and Classes: Overloading Methods, Objects as Parameters, Argument Passing, Returning  Objects, Recursion, Access Control, Understanding static, Introducing final, Introducing Nested and  Inner Classes.  

Chapter 6, 7  

Module-3  

Inheritance: Inheritance Basics, Using super, Creating a Multilevel Hierarchy, When Constructors Are  Executed, Method Overriding, Dynamic Method Dispatch, Using Abstract Classes, Using final with  Inheritance, Local Variable Type Inference and Inheritance, The Object Class. 

Interfaces: Interfaces, Default Interface Methods, Use static Methods in an Interface, Private Interface  Methods.  

Chapter 8, 9 

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Module-4  

Packages: Packages, Packages and Member Access, Importing Packages. 

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Exceptions: Exception-Handling Fundamentals, Exception Types, Uncaught Exceptions, Using try and  catch, Multiple catch Clauses, Nested try Statements, throw, throws, finally, Java’s Built-in Exceptions,  Creating Your Own Exception Subclasses, Chained Exceptions. 

Chapter 9, 10  

Module-5  

Multithreaded Programming: The Java Thread Model, The Main Thread, Creating a Thread, Creating  Multiple Threads, Using isAlive() and join(), Thread Priorities, Synchronization, Interthread  Communication, Suspending, Resuming, and Stopping Threads, Obtaining a Thread’s State. Enumerations, Type Wrappers and Autoboxing: Enumerations (Enumeration Fundamentals, The  values() and valueOf() Methods), Type Wrappers (Character, Boolean, The Numeric Type Wrappers),  Autoboxing (Autoboxing and Methods, Autoboxing/Unboxing Occurs in Expressions,  Autoboxing/Unboxing Boolean and Character Values).  

Chapter 11, 12  

Course outcome (Course Skill Set)  

At the end of the course, the student will be able to:  

1. Demonstrate proficiency in writing simple programs involving branching and looping structures.  2. Design a class involving data members and methods for the given scenario.  
2. Apply the concepts of inheritance and interfaces in solving real world problems.  4. Use the concept of packages and exception handling in solving complex problem  5. Apply concepts of multithreading, autoboxing and enumerations in program development  

Programming Experiments (Suggested and are not limited to)  

1. Develop a JAVA program to add TWO matrices of suitable order N (The value of N should be read from  command line arguments).  
2. Develop a stack class to hold a maximum of 10 integers with suitable methods. Develop a JAVA main  method to illustrate Stack operations.  
3. A class called Employee, which models an employee with an ID, name and salary, is designed as shown in  the following class diagram. The method raiseSalary (percent) increases the salary by the given  percentage. Develop the Employee class and suitable main method for demonstration.  4. A class called MyPoint, which models a 2D point with x and y coordinates, is designed as follows:  

• Two instance variables x (int) and y (int).  
• A default (or “no-arg”) constructor that construct a point at the default location of (0, 0).  ● A overloaded constructor that constructs a point with the given x and y coordinates.  ● A method setXY() to set both x and y.  
• A method getXY() which returns the x and y in a 2-element int array. 
• A toString() method that returns a string description of the instance in the format “(x, y)”.  
• A method called distance(int x, int y) that returns the distance from this point to another point at the  given (x, y) coordinates  
• An overloaded distance(MyPoint another) that returns the distance from this point to the given  MyPoint instance (called another)  
• Another overloaded distance() method that returns the distance from this point to the origin (0,0)  Develop the code for the class MyPoint. Also develop a JAVA program (called TestMyPoint) to test all the  methods defined in the class.  

5. Develop a JAVA program to create a class named shape. Create three sub classes namely: circle, triangle  and square, each class has two member functions named draw () and erase (). Demonstrate  

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Annexure-II 3  

polymorphism concepts by developing suitable methods, defining member data and main program.  6. Develop a JAVA program to create an abstract class Shape with abstract methods calculateArea() and  calculatePerimeter(). Create subclasses Circle and Triangle that extend the Shape class and implement  the respective methods to calculate the area and perimeter of each shape. 

7. Develop a JAVA program to create an interface Resizable with methods resizeWidth(int width) and  resizeHeight(int height) that allow an object to be resized. Create a class Rectangle that implements the  Resizable interface and implements the resize methods  
8. Develop a JAVA program to create an outer class with a function display. Create another class inside the  outer class named inner with a function called display and call the two functions in the main class.  9. Develop a JAVA program to raise a custom exception (user defined exception) for DivisionByZero using  try, catch, throw and finally.  
9. Develop a JAVA program to create a package named mypack and import & implement it in a suitable  class.  
10. Write a program to illustrate creation of threads using runnable class. (start method start each of the  newly created thread. Inside the run method there is sleep() for suspend the thread for 500  milliseconds).  
11. Develop a program to create a class MyThread in this class a constructor, call the base class constructor,  using super and start the thread. The run method of the class starts after this. It can be observed that  both main thread and created child thread are executed concurrently.  

Deve 

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Assessment Details (both CIE and SEE)  

Annexure-II 4  

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The weightage of Continuous Internal Evaluation (CIE) is 50% and for Semester End Exam (SEE) is 50%. The  minimum passing mark for the CIE is 40% of the maximum marks (20 marks out of 50) and for the SEE  minimum passing mark is 35% of the maximum marks (18 out of 50 marks). A student shall be deemed to  have satisfied the academic requirements and earned the credits allotted to each subject/ course if the  student secures a minimum of 40% (40 marks out of 100) in the sum total of the CIE (Continuous Internal  Evaluation) and SEE (Semester End Examination) taken together.  

CIE for the theory component of the IPCC (maximum marks 50)  

• IPCC means practical portion integrated with the theory of the course.  
• CIE marks for the theory component are 25 marks and that for the practical component is 25 marks.  
• 25 marks for the theory component are split into 15 marks for two Internal Assessment Tests (Two  Tests, each of 15 Marks with 01-hour duration, are to be conducted) and 10 marks for other assessment  methods mentioned in 22OB4.2. The first test at the end of 40-50% coverage of the syllabus and the  second test after covering 85-90% of the syllabus.  
• Scaled-down marks of the sum of two tests and other assessment methods will be CIE marks for the  theory component of IPCC (that is for 25 marks).  
• The student has to secure 40% of 25 marks to qualify in the CIE of the theory component of IPCC.  CIE for the practical component of the IPCC  
• 15 marks for the conduction of the experiment and preparation of laboratory record, and 10 marks for  the test to be conducted after the completion of all the laboratory sessions.  
• On completion of every experiment/program in the laboratory, the students shall be evaluated including  viva-voce and marks shall be awarded on the same day.  
• The CIE marks awarded in the case of the Practical component shall be based on the continuous  evaluation of the laboratory report. Each experiment report can be evaluated for 10 marks. Marks of all  experiments’ write-ups are added and scaled down to 15 marks.  
• The laboratory test (duration 02/03 hours) after completion of all the experiments shall be conducted  for 50 marks and scaled down to 10 marks. 
• Scaled-down marks of write-up evaluations and tests added will be CIE marks for the laboratory  component of IPCC for 25 marks.  
• The student has to secure 40% of 25 marks to qualify in the CIE of the practical component of the IPCC.  SEE for IPCC  

Theory SEE will be conducted by University as per the scheduled timetable, with common question papers  for the course (duration 03 hours) 

1. The question paper will have ten questions. Each question is set for 20 marks.  2. There will be 2 questions from each module. Each of the two questions under a module (with a  maximum of 3 sub-questions), should have a mix of topics under that module.  
2. The students have to answer 5 full questions, selecting one full question from each module.  4. Marks scored by the student shall be proportionally scaled down to 50 Marks  

The theory portion of the IPCC shall be for both CIE and SEE, whereas the practical portion will have a  CIE component only. Questions mentioned in the SEE paper may include questions from the practical  component. 

Suggested Learning Resources:  

Textbook 

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Annexure-II 5  

1. Java: The Complete Reference, Twelfth Edition, by Herbert Schildt, November 2021, McGraw-Hill, ISBN:  9781260463422 

Reference Books  

1. Programming with Java, 6th Edition, by E Balagurusamy, Mar-2019, McGraw Hill Education, ISBN: 9789353162337. 
2. Thinking in Java, Fourth Edition, by Bruce Eckel, Prentice Hall, 2006  (https://sd.blackball.lv/library/thinking_in_java_4th_edition.pdf)  

Web links and Video Lectures (e-Resources):  

• Java Tutorial: https://www.geeksforgeeks.org/java/  
• Introduction To Programming In Java (by Evan Jones, Adam Marcus and Eugene Wu):  https://ocw.mit.edu/courses/6-092-introduction-to-programming-in-java-january-iap-2010/ 
• Java Tutorial: https://www.w3schools.com/java/  
• Java Tutorial: https://www.javatpoint.com/java-tutorial  

Activity Based Learning (Suggested Activities)/ Practical Based learning  

1. Installation of Java (Refer: https://www.java.com/en/download/help/index_installing.html)  2. Demonstration of online IDEs like geeksforgeeks, jdoodle or any other Tools  
2. Demonstration of class diagrams for the class abstraction, type visibility, composition and  inheritance  

Assessment Method  

• Programming Assignment / Course Project  

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Annexure-II 1  

Python Programming for Data Science Semester 3  

Course Code BDS306B CIE Marks 50 Teaching Hours/Week (L: T:P: S) 2:0:2:0 SEE Marks 50 Total Hours of Pedagogy 28 Hours Theory + 20 Hours Practical Total Marks 100 Credits 03 Exam Hours 03 Examination type (SEE) Theory 

Note – Students who have undergone “ Introduction to Python Programming BPLCK105B/205B” in first year are not eligible to opt this course  

Course Learning objectives:  

CLO 1:To understand Python constructs and use them to build the programs.  CLO 2: To analyse different conditional statements and their applications in programs.  CLO 3: To learn and use basic data structures in python language.  

CLO 4: To learn and demonstrate array manipulations by reading data from files  CLO 5: To understand and use different data in a data analytics context.  

Teaching-Learning Process (General Instructions)  

These are sample Strategies, which teachers can use to accelerate the attainment of the various course  outcomes.  

1. Chalk and board, power point presentations  
2. Online material (Tutorials) and video lectures. 
3. Demonstration of programing examples.  

 Module-1 6 hr  Introduction to python: Elements of python language, python block structure, variables and  assignment statement, data types in python, operations, simple input/output print statements,  formatting print statement. 

Text Book 1: Chapter 3 ( 3.2, 3.3, 3.4, 3.6, 3.7, 3.9 and 3.10) 

 Module-2 5 hr  Decision structure: forming conditions, if statement, the if-else and nested if-else, looping  statements: introduction to looping, python built in functions for looping, loop statements,  jump statement.  

Text Book 1: Chapter 4 (4.2 to 4.6) , Chapter 5 (5.1 to 5.4) 

 Module-3 5 hr  Lists: lists, operation on list, Tuples: introduction, creating,indexing and slicing, operations  on tuples. sets: creating, operation in sets, introduction dictionaries, creating, operations,  nested dictionary, looping over dictionary.  

Text Book 1: Chapter 7 ( 7.2 to 7.3) , Chapter 8 (8.1 to 8.4) and Chapter 9( 9.1 to 9.3, 9.7  to 9.12) 

 Module-4 6 hr The NumPy Library: Ndarray: the heart of the library, Basic operations, indexing, slicing  and iterating, conditions and boolean arrays, array manipulation, general concepts, reading  and writing array data on files. The pandas Library: an introduction to Data structure,  other functionalities on indexes, operations between data structures, function application and  mapping. 

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Text Book 2: Chapter 3 and Chapter 4. 

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Module-5 6 hr  The pandas : Reading and Writing data: i/o API tools, CSV and textual files, Reading data in  CSV or text files, reading and writing HTML files, reading data from XML files, Microsoft excel  files, JSON data, Pickle python object serialization. Pandas in Depth : data manipulation:  data preparation, concatenating data transformation discretization binning, permutation,  string manipulation, data aggregation group iteration. 

Text Book 2: Chapter 5 and Chapter 6  

Course outcome (Course Skill Set)  

At the end of the course, the student will be able to :  

CO1: Describe the constructs of python programming  

CO2: Use looping and conditional constructs to build programs.  

CO3: Apply the concept of data structure to solve the real world problem.  

CO4: Use the NumPy constructs for matrix manipulations  

CO5: Apply the Panda constructs for data analytics.  

Assessment Details (both CIE and SEE)  

The weightage of Continuous Internal Evaluation (CIE) is 50% and for Semester End Exam (SEE) is  50%. The minimum passing mark for the CIE is 40% of the maximum marks (20 marks out of 50)  and for the SEE minimum passing mark is 35% of the maximum marks (18 out of 50 marks). A  student shall be deemed to have satisfied the academic requirements and earned the credits  allotted to each subject/ course if the student secures a minimum of 40% (40 marks out of 100) in  the sum total of the CIE (Continuous Internal Evaluation) and SEE (Semester End Examination)  taken together.  

Continuous Internal Evaluation:  

• For the Assignment component of the CIE, there are 25 marks and for the Internal Assessment  Test component, there are 25 marks.  
• The first test will be administered after 40-50% of the syllabus has been covered, and the  second test will be administered after 85-90% of the syllabus has been covered  
• Any two assignment methods mentioned in the 22OB2.4, if an assignment is project-based then  only one assignment for the course shall be planned. The teacher should not conduct two  assignments at the end of the semester if two assignments are planned.  
• For the course, CIE marks will be based on a scaled-down sum of two tests and other methods of  assessment.  

Internal Assessment Test question paper is designed to attain the different levels of Bloom’s  taxonomy as per the outcome defined for the course.  

Semester-End Examination:  

Theory SEE will be conducted by University as per the scheduled timetable, with common question papers for  the course (duration 03 hours).  

1. The question paper will have ten questions. Each question is set for 20 marks.  
2. There will be 2 questions from each module. Each of the two questions under a module (with a  maximum of 3 sub-questions), should have a mix of topics under that module.  
3. The students have to answer 5 full questions, selecting one full question from each module.  4. Marks scored shall be proportionally reduced to 50 marks. 

2 

Suggested Learning Resources:  Text Books: 

Annexure-II 3  

15.09.2023 14.09.2023

1. S. Sridhar, J. Indumathi, V.M. Hariharan “Python Programming” Pearson publishers, 1st  edition 2023. 
2. Fabio Nelli, “Python Data Analytics”, Apress, Publishing, 1st Edition, 2015. Reference Book:  
3. Paul Deitel and Harvey deitel,”Intro to Python for Computer Science and Data  science”, 1st edition Pearson Publisher 2020.  

Web links and Video Lectures (e-Resources):  

• Nptel: Introduction to Python for Data  

Sciencehttps://www.youtube.com/watch?v=tA42nHmmEKw&list=PLh2mXjKcTPSACrQxPM2_1Ojus 5HX88ht7  

Activity Based Learning (Suggested Activities in Class)/ Practical Based learning  

• Assessment Methods  

o Programming Assignment (10 Marks)  

Practical Component  

Sl.NO Experiments 

1 Develop a python program to read n digit integer number, and separate the integer  number and display each digit. [Hint: input:5678 output: 5 6 7 8, use: floor and  mod operators)  

2 Develop a python program to accept 4 numbers and display them in sorted order using a  minimum number of if else statements.  

3 Develop python scripts to Calculate the mean, median, mode, variance and standard  deviation of n integer numbers.  

4 Develop a program for checking if a given n digit number is palindrome or not.  [hint: input 1221 output: palindrome, use //and % operator with loop statement]  5 Develop a python script to display a multiplication table for given integer n.  

6 Develop a python script to rotate right about a given position in that list and display them.  [hint: input [1,4,5,-10] position: 2, output: [-10,5,4,1]]  

7 DevelopWrite a python script to interchange the digits of a given integer number.  [hint: input: 23456, interchange: 3 and 5 output: 25436]  

3 

Annexure-II 4  

8 Develop a python program to capitalize a given list of strings.  

[hint: [hello, good, how, simple] output: [Hello, Good, How, Simple]  

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9 Using a dictionary, Develop a python program to determine and print the number of duplicate words  in a sentence.  

10 Develop python program to read Numpy array and print row (sum,mean std) and column  (sum,mean,std)  

11 Develop a python program to read and print in the console CSV file.  

12 Develop a python program to read a HTML file with basic tags, and construct a dictionary and  display the same in the console.  

Assessment Details (both CIE and SEE)  

The weightage of Continuous Internal Evaluation (CIE) is 50% and for Semester End Exam (SEE) is 50%.  The minimum passing mark for the CIE is 40% of the maximum marks (20 marks out of 50) and for the  SEE minimum passing mark is 35% of the maximum marks (18 out of 50 marks). A student shall be  deemed to have satisfied the academic requirements and earned the credits allotted to each subject/  course if the student secures a minimum of 40% (40 marks out of 100) in the sum total of the CIE  (Continuous Internal Evaluation) and SEE (Semester End Examination) taken together.  

CIE for the theory component of the IPCC (maximum marks 50)  

• IPCC means practical portion integrated with the theory of the course.  
• CIE marks for the theory component are 25 marks and that for the practical component is 25 marks.  
• 25 marks for the theory component are split into 15 marks for two Internal Assessment Tests (Two  Tests, each of 15 Marks with 01-hour duration, are to be conducted) and 10 marks for other  assessment methods mentioned in 22OB4.2. The first test at the end of 40-50% coverage of the  syllabus and the second test after covering 85-90% of the syllabus.  
• Scaled-down marks of the sum of two tests and other assessment methods will be CIE marks for the  theory component of IPCC (that is for 25 marks).  
• The student has to secure 40% of 25 marks to qualify in the CIE of the theory component of IPCC.  CIE for the practical component of the IPCC 
• 15 marks for the conduction of the experiment and preparation of laboratory record, and 10 marks for the test to be conducted after the completion of all the laboratory sessions. 
• On completion of every experiment/program in the laboratory, the students shall be evaluated  including viva-voce and marks shall be awarded on the same day.  
• The CIE marks awarded in the case of the Practical component shall be based on the continuous  evaluation of the laboratory report. Each experiment report can be evaluated for 10 marks. Marks of  all experiments’ write-ups are added and scaled down to 15 marks.  
• The laboratory test (duration 02/03 hours) after completion of all the experiments shall be  conducted for 50 marks and scaled down to 10 marks. 
• Scaled-down marks of write-up evaluations and tests added will be CIE marks for the laboratory  component of IPCC for 25 marks. 
• The student has to secure 40% of 25 marks to qualify in the CIE of the practical component of the IPCC. SEE for IPCC 

Theory SEE will be conducted by University as per the scheduled timetable, with common question papers  for the course (duration 03 hours) 

4 

Annexure-II 5  

1. The question paper will have ten questions. Each question is set for 20 marks.  

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2. There will be 2 questions from each module. Each of the two questions under a module (with a  maximum of 3 sub-questions), should have a mix of topics under that module.  
3. The students have to answer 5 full questions, selecting one full question from each module.  4. Marks scored by the student shall be proportionally scaled down to 50 Marks  The theory portion of the IPCC shall be for both CIE and SEE, whereas the practical portion will have  a CIE component only. Questions mentioned in the SEE paper may include questions from the  practical component. 

5 

Annexure-II 1  

Data Analytics with R Semester 3  

Course Code BDS306C CIE Marks 50 Teaching Hours/Week (L: T:P: S) 2;0;2;0 SEE Marks 50 Total Hours of Pedagogy 28 Hours Theory + 20 Hours Practical Total Marks 100 Credits 03 Exam Hours 03 Examination type (SEE) Theory 

Course Learning objectives:  

CLO 1: To Gain the knowledge of R Programming Concepts  

CLO 2: To Explain the concepts of Data Visualization  

CLO 3: To Explain the concept of Statistics in R.  

CLO 4: To Work with R charts and Graphs  

Teaching-Learning Process (General Instructions)  

1. Chalk and board, power point presentations  
2. Online material (Tutorials) and video lectures. 
3. Demonstration of programing examples.  

 Module-1 5 hours  Basics of R  

Introducing R, Initiating R, Packages in R, Environments and Functions, Flow Controls, Loops,  Basic Data Types in R, Vectors  

Chapter 1: 1.1 to 1.7 Chapter 2: 2.1,2.2 

 Module-2 5 hours  Basics of R Continued  

Matrices and Arrays, Lists, Data Frames, Factors, Strings, Dates and Times  Chapter 2: 2.3,2.4,2.5,2.6,2.7.2.8.1,2.8.2  

 Module-3 6 Hours  Data Preparation  

Datasets, Importing and Exporting files, Accessing Databases, Data Cleaning and  Transformation  

Chapter 3: 3.1,3.2,3.3,3.4  

 Module-4 6 Hours  Graphics using R  

Exploratory Data Analysis, Main Graphical Packages, Pie Charts, Scatter Plots, Line Plots,  Histograms, Box Plots, Bar Plots, Other Graphical packages  

Chapter 4: 4.1 to 4.9  

 Module-5 6 Hours  Statistical Analysis using R  

Basic Statistical Measures, Normal distribution, Binomial distribution, Correlation Analysis,  Regression Analysis-Linear Regression Analysis of Variance  

Chapter 5: 5.1, 5.3, 5.4, 5.5, 5.6.1, 5.7  

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1 

Course outcome (Course Skill Set)  

At the end of the course, the student will be able to :  

CO1: Describe the structures of R Programming.  

CO2: Illustrate the basics of Data Preparation with real world examples.  CO3: Apply the Graphical Packages of R for visualization.  CO4: Apply various Statistical Analysis methods for data analytics.  

Assessment Details (both CIE and SEE)  

Annexure-II 2  

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The weightage of Continuous Internal Evaluation (CIE) is 50% and for Semester End Exam (SEE) is  50%. The minimum passing mark for the CIE is 40% of the maximum marks (20 marks out of 50) and  for the SEE minimum passing mark is 35% of the maximum marks (18 out of 50 marks). A student shall be deemed to have satisfied the academic requirements and earned the credits allotted to each  subject/ course if the student secures a minimum of 40% (40 marks out of 100) in the sum total of the  CIE (Continuous Internal Evaluation) and SEE (Semester End Examination) taken together.  

Continuous Internal Evaluation:  

• For the Assignment component of the CIE, there are 25 marks and for the Internal Assessment  Test component, there are 25 marks.  
• The first test will be administered after 40-50% of the syllabus has been covered, and the second  test will be administered after 85-90% of the syllabus has been covered  
• Any two assignment methods mentioned in the 22OB2.4, if an assignment is project-based then  only one assignment for the course shall be planned. The teacher should not conduct two  assignments at the end of the semester if two assignments are planned.  
• For the course, CIE marks will be based on a scaled-down sum of two tests and other methods of  assessment.  

Internal Assessment Test question paper is designed to attain the different levels of Bloom’s taxonomy  as per the outcome defined for the course.  

Semester-End Examination:  

Theory SEE will be conducted by University as per the scheduled timetable, with common question papers for  the course (duration 03 hours).  

1. The question paper will have ten questions. Each question is set for 20 marks.  
2. There will be 2 questions from each module. Each of the two questions under a module (with a maximum  of 3 sub-questions), should have a mix of topics under that module.  
3. The students have to answer 5 full questions, selecting one full question from each module.  4. Marks scored shall be proportionally reduced to 50 marks. 

Suggested Learning Resources:  

Text Books: 

R Programming: An Approach to Data Analytics, G. Sudhamathy and C. Jothi Venkateswaran, MJP Publishers,  2019 

Reference Books:  

1..An Introduction to R, Notes on R: A Programming Environment for Data Analysis and  Graphics. W. N. Venables, D.M. Smith and the R Development Core Team. Version  3.0.1 (2013-05-16)  

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Annexure-II 3  

2. Cotton, R. (2013). Learning R: A Step by Step Function Guide to Data Analysis. 1st ed. O’Reilly Media Inc 

Web links and Video Lectures (e-Resources):  

1. URL: https://cran.r-project.org/doc/manuals/r-release/R-intro.pdf 
2. http://www.tutorialspoint.com/r/r_tutorial.pdf 
3. https://users.phhp.ufl.edu/rlp176/Courses/PHC6089/R_notes/intro.html 
4. https://cran.r-project.org/web/packages/explore/vignettes/explore_mtcars.html  5. https://www.w3schools.com/r/r_stat_data_set.asp  
5. https://rpubs.com/BillB/217355  

Activity Based Learning (Suggested Activities in Class)/ Practical Based learning  ● Programming Assignment (10 Marks)  

Practical Component  

Sl.NO Experiments 

1 Demonstrate the steps for installation of R and R Studio. Perform the following:  

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1. a) Assign different type of values to variables and display the type of variable. Assign different types  such as Double, Integer, Logical, Complex and Character and understand the difference between  each data type.  
2. b) Demonstrate Arithmetic and Logical Operations with simple examples.  
3. c) Demonstrate generation of sequences and creation of vectors.  
4. d) Demonstrate Creation of Matrices  
5. e) Demonstrate the Creation of Matrices from Vectors using Binding Function.  
6. f) Demonstrate element extraction from vectors, matrices and arrays 

2 Assess the Financial Statement of an Organization being supplied with 2 vectors of data: Monthly Revenue  and Monthly Expenses for the Financial Year. You can create your own sample data vector for this  experiment) Calculate the following financial metrics:  

1. Profit for each month.  
2. Profit after tax for each month (Tax Rate is 30%).  
3. Profit margin for each month equals to profit after tax divided by revenue.  
4. Good Months – where the profit after tax was greater than the mean for the year. e. Bad Months – where the profit after tax was less than the mean for the year.  
5. The best month – where the profit after tax was max for the year.  
6. The worst month – where the profit after tax was min for the year.  

Note:  

1. All Results need to be presented as vectors  
2. Results for Dollar values need to be calculated with $0.01 precision, but need to be presented in  Units of $1000 (i.e 1k) with no decimal points  
3. Results for the profit margin ratio need to be presented in units of % with no decimal point.  d. It is okay for tax to be negative for any given month (deferred tax asset) 
4. Generate CSV file for the data. 

3 Develop a program to create two 3 X 3 matrices A and B and perform the following operations a) Transpose  of the matrix b) addition c) subtraction d) multiplication  

4 Develop a program to find the factorial of given number using recursive function calls. 

3 

Annexure-II 4  

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5 Develop an R Program using functions to find all the prime numbers up to a specified number by the  method of Sieve of Eratosthenes. 

6 The built-in data set mammals contain data on body weight versus brain weight. Develop R  commands to:  

1. a) Find the Pearson and Spearman correlation coefficients. Are they similar?  
2. b) Plot the data using the plot command.  
3. c) Plot the logarithm (log) of each variable and see if that makes a difference. 

7 Develop R program to create a Data Frame with following details and do the following operations.  itemCode itemCategory itemPrice  

1001 Electronics 700 

1002 Desktop Supplies 300 

1003 Office Supplies 350 

1004 USB 400 

1005 CD Drive 800 

350. a) Subset the Data frame and display the details of only those items whose price is greater than or equal to  350. 
351. b) Subset the Data frame and display only the items where the category is either “Office Supplies” or  “Desktop Supplies” 
352. c) Create another Data Frame called “item-details” with three different fields itemCode, ItemQtyonHand  and ItemReorderLvl and merge the two frames  

8 Let us use the built-in dataset air quality which has Daily air quality measurements in New York, May to  September 1973. Develop R program to generate histogram by using appropriate arguments for the  following statements.  

1. a) Assigning names, using the air quality data set.  
2. b) Change colors of the Histogram  
3. c) Remove Axis and Add labels to Histogram  
4. d) Change Axis limits of a Histogram  
5. e) Add Density curve to the histogram 

9 Design a data frame in R for storing about 20 employee details. Create a CSV file named “input.csv” that  defines all the required information about the employee such as id, name, salary, start_date, dept. Import  into R and do the following analysis.  

1. a) Find the total number rows & columns  
2. b) Find the maximum salary  
3. c) Retrieve the details of the employee with maximum salary  
4. d) Retrieve all the employees working in the IT Department.  
5. e) Retrieve the employees in the IT Department whose salary is greater than 20000 and write these  details into another file “output.csv” 

10 Using the built in dataset mtcars which is a popular dataset consisting of the design and fuel consumption  patterns of 32 different automobiles. The data was extracted from the 1974 Motor Trend US magazine, and  comprises fuel consumption and 10 aspects of automobile design and performance for 32 automobiles  (1973-74 models). Format A data frame with 32 observations on 11 variables : [1] mpg Miles/(US) gallon,  [2] cyl Number of cylinders [3] disp Displacement (cu.in.), [4] hp Gross horsepower [5] drat Rear axle  ratio,[6] wt Weight (lb/1000) [7] qsec 1/4 mile time, [8] vs V/S, [9] am Transmission (0 = automatic, 1 =  manual), [10] gear Number of forward gears, [11] carb Number of carburetors  

Develop R program, to solve the following:  

1. a) What is the total number of observations and variables in the dataset?  
2. b) Find the car with the largest hp and the least hp using suitable functions 
3. c) Plot histogram / density for each variable and determine whether continuous variables are  normally distributed or not. If not, what is their skewness?  
4. d) What is the average difference of gross horse power(hp) between automobiles with 3 and 4  number of cylinders(cyl)? Also determine the difference in their standard deviations.  
5. e) Which pair of variables has the highest Pearson correlation?  

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Annexure-II 5  

11 Demonstrate the progression of salary with years of experience using a suitable data set (You can create  your own dataset). Plot the graph visualizing the best fit line on the plot of the given data points. Plot a  curve of Actual Values vs. Predicted values to show their correlation and performance of the model.  Interpret the meaning of the slope and y-intercept of the line with respect to the given data. Implement  using lm function. Save the graphs and coefficients in files. Attach the predicted values of salaries as a new  column to the original data set and save the data as a new CSV file. 

Assessment Details (both CIE and SEE)  

The weightage of Continuous Internal Evaluation (CIE) is 50% and for Semester End Exam (SEE) is 50%.  The minimum passing mark for the CIE is 40% of the maximum marks (20 marks out of 50) and for the  SEE minimum passing mark is 35% of the maximum marks (18 out of 50 marks). A student shall be  deemed to have satisfied the academic requirements and earned the credits allotted to each subject/  course if the student secures a minimum of 40% (40 marks out of 100) in the sum total of the CIE  (Continuous Internal Evaluation) and SEE (Semester End Examination) taken together.  

CIE for the theory component of the IPCC (maximum marks 50)  

• IPCC means practical portion integrated with the theory of the course.  
• CIE marks for the theory component are 25 marks and that for the practical component is 25 marks.  
• 25 marks for the theory component are split into 15 marks for two Internal Assessment Tests (Two  Tests, each of 15 Marks with 01-hour duration, are to be conducted) and 10 marks for other  assessment methods mentioned in 22OB4.2. The first test at the end of 40-50% coverage of the  syllabus and the second test after covering 85-90% of the syllabus.  
• Scaled-down marks of the sum of two tests and other assessment methods will be CIE marks for the  theory component of IPCC (that is for 25 marks).  
• The student has to secure 40% of 25 marks to qualify in the CIE of the theory component of IPCC.  CIE for the practical component of the IPCC 
• 15 marks for the conduction of the experiment and preparation of laboratory record, and 10 marks for the test to be conducted after the completion of all the laboratory sessions.  
• On completion of every experiment/program in the laboratory, the students shall be evaluated  including viva-voce and marks shall be awarded on the same day.  
• The CIE marks awarded in the case of the Practical component shall be based on the continuous  evaluation of the laboratory report. Each experiment report can be evaluated for 10 marks. Marks of  all experiments’ write-ups are added and scaled down to 15 marks.  
• The laboratory test (duration 02/03 hours) after completion of all the experiments shall be  conducted for 50 marks and scaled down to 10 marks. 
• Scaled-down marks of write-up evaluations and tests added will be CIE marks for the laboratory  component of IPCC for 25 marks. 
• The student has to secure 40% of 25 marks to qualify in the CIE of the practical component of the IPCC. SEE for IPCC 

Theory SEE will be conducted by University as per the scheduled timetable, with common question papers  for the course (duration 03 hours) 

1. The question paper will have ten questions. Each question is set for 20 marks.  
2. There will be 2 questions from each module. Each of the two questions under a module (with a  maximum of 3 sub-questions), should have a mix of topics under that module.  
3. The students have to answer 5 full questions, selecting one full question from each module.  4. Marks scored by the student shall be proportionally scaled down to 50 Marks  

The theory portion of the IPCC shall be for both CIE and SEE, whereas the practical portion will have  a CIE component only. Questions mentioned in the SEE paper may include questions from the  practical component. 

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5 

BSCK307 – Social Connect & Responsibility 2022 Scheme & syllabus 3rdsem 

BSCK307 – Social Connect & Responsibility  2022 Scheme & syllabus for 3rd sem 

15.09.2023

Semester 3rd 

Course Code BSCK307 CIE Marks 100  Teaching Hours/Week (L:T:P: S) 0:0:3:1 SEE Marks ——  Total Hours of Pedagogy 40 hour Practical Session +15 hour Planning Total Marks 100 (No SEE – Only CIE) For CIE Assessment – Activities Report Evaluation by College NSS  

Examination nature  

Officer / HOD / Sports Dept / Any Dept.  

Credits 01 – Credit  

Course objectives: The course will enable the students to:  

1. Provide a formal platform for students to communicate and connect to the surrounding.  
2. create a responsible connection with the society.  
3. Understand the community in general in which they work.  
4. Identify the needs and problems of the community and involve them in problem –solving.  5. Develop among themselves a sense of social & civic responsibility & utilize their knowledge   in finding practical solutions to individual and community problems.  
5. Develop competence required for group-living and sharing of responsibilities & gain skills   in mobilizing community participation to acquire leadership qualities and democratic attitudes.  

General Instructions – Pedagogy :  

These are sample Strategies, which teachers can use to accelerate the attainment of the various course outcomes.  1. In addition to the traditional lecture method, different types of innovative teaching methods may be adopted so  that the activities will develop students’ theoretical and applied social and cultural skills. 

2. State the need for activities and its present relevance in the society and Provide real-life examples.  3. Support and guide the students for self-planned activities.  
3. You will also be responsible for assigning homework, grading assignments and quizzes, and documenting  students’ progress in real activities in the field.  
4. Encourage the students for group work to improve their creative and analytical skills.  

Contents :  

The course is mainly activity-based that will offer a set of activities for the student that enables them to connect with fellow  human beings, nature, society, and the world at large.  

The course will engage students for interactive sessions, open mic, reading group, storytelling sessions, and semester-long  activities conducted by faculty mentors.  

In the following a set of activities planned for the course have been listed: 

Social Connect & Responsibility – Contents 

Part I:  

Plantation and adoption of a tree:  

Plantation of a tree that will be adopted for four years by a group of BE / B.Tech students. (ONE STUDENT ONE TREE)  They will also make an excerpt either as a documentary or a photo blog describing the plant’s origin, its usage in daily life,  its appearance in folklore and literature – – Objectives, Visit, case study, report, outcomes.  

Part II :  

Heritage walk and crafts corner:  

Heritage tour, knowing the history and culture of the city, connecting to people around through their history, knowing the  city and its craftsman, photo blog and documentary on evolution and practice of various craft forms – – Objectives,Visit,  case study, report, outcomes.  

Part III :  

Organic farming and waste management:  

Usefulness of organic farming, wet waste management in neighboring villages, and implementation in the campus – 

1 

BSCK307 – Social Connect & Responsibility 2022 Scheme & syllabus 3rdsem 

Objectives,Visit, case study, report, outcomes.  

Part IV:  

Water conservation:  

Knowing the present practices in the surrounding villages and implementation in the campus, documentary or photoblog  presenting the current practices – Objectives, Visit, case study, report, outcomes.  

Part V :  

Food walk:  

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City’s culinary practices, food lore, and indigenous materials of the region used in cooking – Objectives, Visit, case study,  report, outcomes. 

Course outcomes (Course Skill Set):  

At the end of the course, the student will be able to:  

 CO1: Communicate and connect to the surrounding.  

 CO2: Create a responsible connection with the society.  

 CO3: Involve in the community in general in which they work.  

 CO4: Notice the needs and problems of the community and involve them in problem –solving.   CO5: Develop among themselves a sense of social & civic responsibility & utilize their knowledge   in finding practical solutions to individual and community problems.  

CO6: Develop competence required for group-living and sharing of responsibilities & gain skills   in mobilizing community participation to acquire leadership qualities and democratic attitudes.  Activities:  

Jamming session, open mic, and poetry: Platform to connect to others. Share the stories with  others. Share the experience of Social Connect. Exhibit the talent like playing instruments,  singing, one-act play, art-painting, and fine art.  

PEDAGOGY:  

The pedagogy will include interactive lectures, inspiring guest talks, field visits, social  immersion, and a course project. Applying and synthesizing information from these sources to  define the social problem to address and take up the solution as the course project, with your  group. Social immersionwith NGOs/social sections will be a key part of the course. Will all lead  to the course project that will address the needs of the social sector?  

COURSE TOPICS:  

The course will introduce social context and various players in the social space, and present  approaches to discovering and understanding social needs. Social immersion and inspiring  conversional will culminate in developing an actual, idea for problem-based intervention, based  on an in-depth understanding of a key social problem.  

Duration :  

A total of 40 – 50 hrs engagement per semester is required for the 3rd semester of the B.E.  /B.Tech. program. The students will be divided into groups. Each group will be handled by  faculty mentor. Faculty mentor will design the activities (particularly Jamming sessions open  mic ,and poetry) Faculty mentors has to design the evaluation system as per VTU guidelines of  scheme & syllabus.  

Guideline for Assessment Process:  

Continuous Internal Evaluation (CIE):  

After completion of the course, the student shall prepare, with daily diary as reference, a  comprehensive report in consultation with the mentor/s to indicate what he has observed and  learned in the social connect period. The report should be signed by the mentor. The report shall  

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BSCK307 – Social Connect & Responsibility 2022 Scheme & syllabus 3rdsem 

be evaluated on the basis of the following criteria and/or other relevant criteria pertaining to the  activity completed. Marks allotted for the diary are out of 50. Planning and scheduling the social  connect Information/Data collected during the social connect Analysis of the information/data  and report writing Considering all above points allotting the marks as mentioned below  Excellent : 80 to 100  

Good : 60 to 79  

Satisfactory : 40 to 59  

Unsatisfactory and fail : <39  

Special Note :  

NO SEE – Semester End Exam – Completely Practical and activities based evaluation  Pedagogy – Guidelines :  

It may differ depending on local resources available for the study as well as environment and  climatic differences, location and time of execution. 

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Sl  No 

 Topic Group  size 

 Location Activity  execution 

Reporting Evaluation Of the Topic  

1. Plantation and  adoption of a  

tree:  

2. Heritage walk  and crafts  

corner:  

3. Organic farming  and waste  

management:  

4. Water  

conservation:  

& conservation  

techniques  

5. Food walk:  Practices in  

society  

May be  individual  or team  

May be  individual  or team  

May be  individual  or team  

May be  individual  or team 

May be  individual  or team  

Farmers land/ parks /  Villages / roadside/  community area /  College campus etc….. 

Temples / monumental  places / Villages/ City  Areas / Grama  

panchayat/ public  associations/Governme nt Schemes officers/  campus etc….. 

Farmers land / parks /  Villages visits  

/ roadside/ community  area / College campus  etc….. 

Villages/ City Areas /  Grama  

panchayat/ public  associations/Governme nt Schemes officers /  campus etc….. 

Villages/ City Areas /  Grama  

panchayat/ public  associations/Governme nt Schemes officers/  campus etc….. 

Site selection  

/proper  

consultation/Contin uous monitoring/  Information board  

Site selection  

/proper  

consultation/Contin uous monitoring/  Information board  

Group selection /  proper consultation  / Continuous  

monitoring /  

Information board  

site selection /  proper  

consultation/Contin uous monitoring/  Information board  

Group selection /  proper consultation  / Continuous  

monitoring /  

Information board  

Report should  

be submitted by  individual to the  concerned evaluation  authority  

Report should  

be submitted by  individual to the  concerned  

evaluation authority  

Report should  

be submitted by  individual to the  concerned  

evaluation authority  

Report should  

be submitted by  individual to the  concerned  

evaluation authority  

Report should  

be submitted by  individual to the  concerned  

evaluation authority  

Evaluation as  per the rubrics  Of scheme and  syllabus by  Faculty  

Evaluation as  per the rubrics  Of scheme and  syllabus by  Faculty  

Evaluation as  per the rubrics  Of scheme and  syllabus by  Faculty  

Evaluation as  per the rubrics  Of scheme and  syllabus by  Faculty  

Evaluation as  per the rubrics  Of scheme and  syllabus by  Faculty  

3 

BSCK307 – Social Connect & Responsibility 2022 Scheme & syllabus 3rdsem 

Plan of Action (Execution of Activities )  

Sl.NO Practice Session Description  

1 Lecture session in field to start activities  

2 Students Presentation on Ideas  

3 Commencement of activity and its progress  

4 Execution of Activity  

5 Execution of Activity  

6 Execution of Activity  

7 Execution of Activity  

8 Case study based Assessment, Individual performance  

9 Sector/ Team wise study and its consolidation  

10 Video based seminar for 10 minutes by each student At the end of semester with Report.  ∙ Each student should do activities according to the scheme and syllabus.  

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∙ At the end of semester student performance has to be evaluated by the faculty for the assigned  activity progress and its completion.  

∙ At last consolidated report of all activities from 1st to 5th, compiled report should be submitted as  per the instructions and scheme.  

———————————————————————————————————————  

Assessment Details for CIE (both CIE and SEE)  

Weightage CIE – 100% ∙ Implementation strategies of the project (  

Field Visit, Plan, Discussion 10 Marks Commencement of activities and its progress 20 Marks 

NSS work).  

∙ The last report should be signed by  

Case study based Assessment  Individual performance with report  

20 Marks 

NSS Officer, the HOD and principal.  ∙ At last report should be evaluated by the NSS  

Sector wise study & its consolidation 5*5 = 25 25 Marks 

officer of the institute.  

Video based seminar for 10 minutes by each  student At the end of semester with Report.  Activities 1 to 5, 5*5 = 25  

Total marks for the course in each  semester  

25 Marks  

100 Marks    

∙ Finally the consolidated marks sheet should  be sent to the university and also to be made  available at LIC visit.  

For each activity, 20 marks CIE will be evaluated for IA marks at the end of semester, Report and  assessment copy should be made available in the department. 

Students should present the progress of the activities as per the schedule in the prescribed practical session in the field.  There should be positive progress in the vertical order for the benefit of society in general through activities.  

4 

Template for Practical Course and if AEC is a practical Course Annexure-V  

Data Analytics with Excel Semester 3  

Course Code BCS358A CIE Marks 50 Teaching Hours/Week (L:T:P: S) 0:0:2:0 SEE Marks 50 Credits 01 Exam Hours 100 Examination type (SEE) Practical  

Course objectives:  

• To Apply analysis techniques to datasets in Excel  
• Learn how to use Pivot Tables and Pivot Charts to streamline your workflow in Excel  ● Understand and Identify the principles of data analysis  
• Become adept at using Excel functions and techniques for analysis  
• Build presentation ready dashboards in Excel  

Sl.NO Experiments  

1 Getting Started with Excel: Creation of spread sheets, Insertion of rows and columns, Drag  & Fill, use of Aggregate functions.  

2 Working with Data : Importing data, Data Entry & Manipulation, Sorting & Filtering. 3 Working with Data: Data Validation, Pivot Tables & Pivot Charts. 

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4 Data Analysis Process: Conditional Formatting, What-If Analysis, Data Tables, Charts &  Graphs. 

5 Cleaning Data with Text Functions: use of UPPER and LOWER, TRIM function, Concatenate.  

6 Cleaning Data Containing Date and Time Values: use of DATEVALUE function, DATEADD and  DATEDIF, TIMEVALUE functions. 

7 Conditional Formatting: formatting, parsing, and highlighting data in spreadsheets during  data analysis.  

8 Working with Multiple Sheets: work with multiple sheets within a workbook is crucial for  organizing and managing data, perform complex calculations and create comprehensive  reports.  

9 Create worksheet with following fields: Empno, Ename, Basic Pay(BP), Travelling  Allowance(TA), Dearness Allowance(DA), House Rent Allowance(HRA), Income Tax(IT),  Provident Fund(PF), Net Pay(NP). Use appropriate formulas to calculate the above scenario.  Analyse the data using appropriate chart and report the data. 

10 Create worksheet on Inventory Management: Sheet should contain Product code, Product  name, Product type, MRP, Cost after % of discount, Date of purchase. Use appropriate  formulas to calculate the above scenario. Analyse the data using appropriate chart and report  the data.  

Template for Practical Course and if AEC is a practical Course Annexure-V  

15.09.2023 14.09.2023

11 Create worksheet on Sales analysis of Merchandise Store: data consisting of Order ID,  Customer ID, Gender, age, date of order, month, online platform, Category of product, size,  quantity, amount, shipping city and other details. Use of formula to segregate different  categories and perform a comparative study using pivot tables and different sort of charts.  

12 Generation of report & presentation using Autofilter &macro. 

Course outcomes (Course Skill Set):  

At the end of the course the student will be able to:  

• Use advanced functions and productivity tools to assist in developing worksheets.  ● Manipulate data lists using Outline and PivotTables.  
• Use Consolidation to summarise and report results from multiple worksheets.  ● Apply Macros and Autofilter to solve the given real world scenario.  
  

Template for Practical Course and if AEC is a practical Course Annexure-V  Assessment Details (both CIE and SEE)  

15.09.2023 14.09.2023

The weightage of Continuous Internal Evaluation (CIE) is 50% and for Semester End Exam (SEE) is 50%.  The minimum passing mark for the CIE is 40% of the maximum marks (20 marks out of 50) and for the  SEE minimum passing mark is 35% of the maximum marks (18 out of 50 marks). A student shall be  deemed to have satisfied the academic requirements and earned the credits allotted to each subject/ course if the student secures a minimum of 40% (40 marks out of 100) in the sum total of the CIE  (Continuous Internal Evaluation) and SEE (Semester End Examination) taken together 

Continuous Internal Evaluation (CIE):  

CIE marks for the practical course are 50 Marks.  

The split-up of CIE marks for record/ journal and test are in the ratio 60:40.  

• Each experiment is to be evaluated for conduction with an observation sheet and record  write-up. Rubrics for the evaluation of the journal/write-up for hardware/software  experiments are designed by the faculty who is handling the laboratory session and are  made known to students at the beginning of the practical session.  
• Record should contain all the specified experiments in the syllabus and each experiment  write-up will be evaluated for 10 marks.  
• Total marks scored by the students are scaled down to 30 marks (60% of maximum  marks).  
• Weightage to be given for neatness and submission of record/write-up on time.  
• Department shall conduct a test of 100 marks after the completion of all the experiments  listed in the syllabus.  
• In a test, test write-up, conduction of experiment, acceptable result, and procedural  knowledge will carry a weightage of 60% and the rest 40% for viva-voce.  
• The suitable rubrics can be designed to evaluate each student’s performance and learning  ability.  
• The marks scored shall be scaled down to 20 marks (40% of the maximum marks).  The Sum of scaled-down marks scored in the report write-up/journal and marks of a test is the  total CIE marks scored by the student. 

Semester End Evaluation (SEE):  

• SEE marks for the practical course are 50 Marks.  
• SEE shall be conducted jointly by the two examiners of the same institute, examiners are  appointed by the Head of the Institute.  
• The examination schedule and names of examiners are informed to the university before  the conduction of the examination. These practical examinations are to be conducted  between the schedule mentioned in the academic calendar of the University.  
  

Template for Practical Course and if AEC is a practical Course Annexure-V  

• All laboratory experiments are to be included for practical examination.  
• (Rubrics) Breakup of marks and the instructions printed on the cover page of the answer  script to be strictly adhered to by the examiners. OR based on the course requirement  evaluation rubrics shall be decided jointly by examiners. 
• Students can pick one question (experiment) from the questions lot prepared by the  examiners jointly.  
• Evaluation of test write-up/ conduction procedure and result/viva will be conducted  jointly by examiners.  
• General rubrics suggested for SEE are mentioned here, writeup-20%, Conduction procedure  and result in -60%, Viva-voce 20% of maximum marks. SEE for practical shall be evaluated  for 100 marks and scored marks shall be scaled down to 50 marks (however, based on  course type, rubrics shall be decided by the examiners) 
• Change of experiment is allowed only once and 15% of Marks allotted to the procedure part  are to be made zero.  

The minimum duration of SEE is 02 hours  

Suggested Learning Resources:  

15.09.2023 14.09.2023

• Berk & Carey – Data Analysis with Microsoft® Excel: Updated for Offi ce 2007®, Third  Edition, © 2010 Brooks/Cole, Cengage Learning, ISBN-13: 978-0-495-39178-4 
• Wayne L. Winston – Microsoft Excel 2019: Data Analysis And Business Modeling, PHI,  ISBN: 9789389347180  
• Aryan Gupta – Data Analysis in Excel: The Best Guide.  (https://www.simplilearn.com/tutorials/excel-tutorial/data-analysis-excel)  
  

All AI & DS Programs 

Ethics and Public Policy for AI Semester  

Course Code BAI358B CIE Marks 50 Teaching Hours/Week (L:T:P: S) 1:0:0 SEE Marks 50 Total Hours of Pedagogy 14 Total Marks 100 Credits 03 Exam Hours 2  Examination type (SEE) Theory  

Course objectives:  

• To understand Ethical Framework for a Good AI Society, establishing Rules for trustworthy  AI 
• To Designing ethics for good society  
• To familiar with Tools, methods and practices for designing AI for social good ● To familiar with Innovation and future AI  
• To understand the Case Study: Ai in health care, knowing Regulation and Governance of AI  ethics 

Teaching-Learning Process (General Instructions)  

These are sample Strategies, which teachers can use to accelerate the attainment of the various course  outcomes.  

1. Chalk and Talk  
2. Real time Examples  
3. Natural Approaches  

Module-1  

An Ethical Framework for a Good AI Society: opportunities, Risks, principles and Recommendations.  Establishing the rules for building trustworthy AI  

Textbook1: Chapter 3, chapter 4  

Module-2  

Translating principles into practices of digital ethics: five risks of being Unethical  The Ethics of Algorithms: Key problems and Solution  

How to Design AI for Social Good: Seven Essential Factors  

Textbook1: Chapter 6, Chapter 8, Chapter 9 

Module-3  

How to design AI for social good: seven essential factors  

From What to How: An Initial Review of publicly available AI Ethics tools, Methods and Research to  Translate principles into Practices  

Textbook1: Chapter 9, Chapter 10 

Module-4  

Innovating with Confidence: Embedding AI Governance and fairness in financial Services Risk  management framework,  What the near future of AI could be. 

Textbook1: Chapter 20, chapter 22  

Module-5  

Human-AI Relationship, AI and Workforce, Autonomous Machines and Moral Decisions,  AI in HealthCare: balancing Progress and Ethics,  

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1 

All AI & DS Programs 

Regulation and Governance of AI Ethics  

Textbook2 : Chapter 5,Chapter 8, Chapter 9  

Course outcome (Course Skill Set)  

At the end of the course, the student will be able to :  

1. Describe Ethical Framework for a Good AI Society, establishing Rules for trustworthy AI  2. Explain ethics for good society  
2. Illustrate various Tools, methods and practices for designing AI for social good  4. Describe the Innovation and future AI  
3. Illustrate Regulation and Governance of AI ethics in Healthcare domain. 

Assessment Details (both CIE and SEE)  

The weightage of Continuous Internal Evaluation (CIE) is 50% and for Semester End Exam (SEE) is  50%. The minimum passing mark for the CIE is 40% of the maximum marks (20 marks out of 50)  and for the SEE minimum passing mark is 35% of the maximum marks (18 out of 50 marks). A  student shall be deemed to have satisfied the academic requirements and earned the credits  allotted to each subject/ course if the student secures a minimum of 40% (40 marks out of 100) in  the sum total of the CIE (Continuous Internal Evaluation) and SEE (Semester End Examination)  taken together.  

Continuous Internal Evaluation:  

• For the Assignment component of the CIE, there are 25 marks and for the Internal Assessment  Test component, there are 25 marks.  
• The first test will be administered after 40-50% of the syllabus has been covered, and the  second test will be administered after 85-90% of the syllabus has been covered  
• Any two assignment methods mentioned in the 22OB2.4, if an assignment is project-based  then only one assignment for the course shall be planned. The teacher should not conduct two  assignments at the end of the semester if two assignments are planned.  
• For the course, CIE marks will be based on a scaled-down sum of two tests and other methods  of assessment. 

Internal Assessment Test question paper is designed to attain the different levels of Bloom’s  taxonomy as per the outcome defined for the course.  

Semester-End Examination:  

Theory SEE will be conducted by University as per the scheduled timetable, with common question papers  for the course (duration 03 hours).  

1. The question paper will have ten questions. Each question is set for 20 marks.  2. There will be 2 questions from each module. Each of the two questions under a module (with a  maximum of 3 sub-questions), should have a mix of topics under that module.  
2. The students have to answer 5 full questions, selecting one full question from each module.  4. Marks scored shall be proportionally reduced to 50 marks. 

Suggested Learning Resources:  

Books 

1. “Ethics, governance and Policies in Artificial Intelligence“, Author-Editor : Luciano Floridi, Springer, 1st Edition 2021, vol 144, Oxford Internet Institute, University of ixford, UK, ISSN 0921-8599, e-ISSN 2542- 8349 Philosophical Studies series, ISBN 978-3-030-81906-4 e-ISBN 978-3-030-81907-1,  ://doi.orghttps/10.1007/978-3-030-81907-1, 2021.  
2. “Ethics and AI: Navigating the Moral Landscape of Digital Age”, Author: Aaron Aboagye,  

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2 

Template for Practical Course and if AEC is a practical Course Annexure-V  

 Project Management with Git Semester 3  Course Code BCS358C CIE Marks 50 Teaching Hours/Week (L:T:P: S) 0: 0 : 2: 0 SEE Marks 50 Credits 01 Exam Marks 100 

Examination type (SEE) Practical  

Course objectives:  

• .To familiar with basic command of Git  
• To create and manage branches  
• To understand how to collaborate and work with Remote Repositories 
• To familiar with virion controlling commands  

Sl.NO Experiments  

1 Setting Up and Basic Commands  

Initialize a new Git repository in a directory. Create a new file and add it to the staging area  and commit the changes with an appropriate commit message.  

2 Creating and Managing Branches  

15.09.2023 14.09.2023

Create a new branch named “feature-branch.” Switch to the “master” branch. Merge the  “feature-branch” into “master.” 

3 Creating and Managing Branches  

Write the commands to stash your changes, switch branches, and then apply the stashed  changes. 

4 Collaboration and Remote Repositories  

Clone a remote Git repository to your local machine. 

5 Collaboration and Remote Repositories  

Fetch the latest changes from a remote repository and rebase your local branch onto the  updated remote branch. 

6 Collaboration and Remote Repositories  

Write the command to merge “feature-branch” into “master” while providing a custom  commit message for the merge. 

7 Git Tags and Releases  

Write the command to create a lightweight Git tag named “v1.0” for a commit in your local  repository.  

8 Advanced Git Operations  

Template for Practical Course and if AEC is a practical Course Annexure-V  

15.09.2023 14.09.2023

Write the command to cherry-pick a range of commits from “source-branch” to the current  branch. 

9 Analysing and Changing Git History  

Given a commit ID, how would you use Git to view the details of that specific commit,  including the author, date, and commit message? 

10 Analysing and Changing Git History  

Write the command to list all commits made by the author “JohnDoe” between “2023-01-01”  and “2023-12-31.”  

11 Analysing and Changing Git History  

Write the command to display the last five commits in the repository’s history.  

12 Analysing and Changing Git History  

Write the command to undo the changes introduced by the commit with the ID “abc123”.  Course outcomes (Course Skill Set):  

At the end of the course the student will be able to:  

• Use the basics commands related to git repository  
• Create and manage the branches  
• Apply commands related to Collaboration and Remote Repositories  
• Use the commands related to Git Tags, Releases and advanced git operations  
• Analyse and change the git history  
  

Template for Practical Course and if AEC is a practical Course Annexure-V  Assessment Details (both CIE and SEE)  

15.09.2023 14.09.2023

The weightage of Continuous Internal Evaluation (CIE) is 50% and for Semester End Exam (SEE) is 50%.  The minimum passing mark for the CIE is 40% of the maximum marks (20 marks out of 50) and for the  SEE minimum passing mark is 35% of the maximum marks (18 out of 50 marks). A student shall be  deemed to have satisfied the academic requirements and earned the credits allotted to each subject/ course if the student secures a minimum of 40% (40 marks out of 100) in the sum total of the CIE  (Continuous Internal Evaluation) and SEE (Semester End Examination) taken together 

Continuous Internal Evaluation (CIE):  

CIE marks for the practical course are 50 Marks.  

The split-up of CIE marks for record/ journal and test are in the ratio 60:40.  

• Each experiment is to be evaluated for conduction with an observation sheet and record  write-up. Rubrics for the evaluation of the journal/write-up for hardware/software  experiments are designed by the faculty who is handling the laboratory session and are  made known to students at the beginning of the practical session.  
• Record should contain all the specified experiments in the syllabus and each experiment  write-up will be evaluated for 10 marks.  
• Total marks scored by the students are scaled down to 30 marks (60% of maximum  marks).  
• Weightage to be given for neatness and submission of record/write-up on time.  
• Department shall conduct a test of 100 marks after the completion of all the experiments  listed in the syllabus.  
• In a test, test write-up, conduction of experiment, acceptable result, and procedural  knowledge will carry a weightage of 60% and the rest 40% for viva-voce.  
• The suitable rubrics can be designed to evaluate each student’s performance and learning  ability.  
• The marks scored shall be scaled down to 20 marks (40% of the maximum marks).  The Sum of scaled-down marks scored in the report write-up/journal and marks of a test is the  total CIE marks scored by the student. 

Semester End Evaluation (SEE):  

• SEE marks for the practical course are 50 Marks.  
• SEE shall be conducted jointly by the two examiners of the same institute, examiners are  appointed by the Head of the Institute.  
• The examination schedule and names of examiners are informed to the university before  the conduction of the examination. These practical examinations are to be conducted  between the schedule mentioned in the academic calendar of the University.  
  

Template for Practical Course and if AEC is a practical Course Annexure-V  

• All laboratory experiments are to be included for practical examination.  
• (Rubrics) Breakup of marks and the instructions printed on the cover page of the answer  script to be strictly adhered to by the examiners. OR based on the course requirement  evaluation rubrics shall be decided jointly by examiners. 
• Students can pick one question (experiment) from the questions lot prepared by the  examiners jointly.  
• Evaluation of test write-up/ conduction procedure and result/viva will be conducted  jointly by examiners.  
• General rubrics suggested for SEE are mentioned here, writeup-20%, Conduction procedure  and result in -60%, Viva-voce 20% of maximum marks. SEE for practical shall be evaluated  for 100 marks and scored marks shall be scaled down to 50 marks (however, based on  course type, rubrics shall be decided by the examiners) 
• Change of experiment is allowed only once and 15% of Marks allotted to the procedure part  are to be made zero.  

The minimum duration of SEE is 02 hours  

Suggested Learning Resources:  

15.09.2023 14.09.2023

• Version Control with Git, 3rd Edition, by Prem Kumar Ponuthorai, Jon Loeliger Released October 2022,  Publisher(s): O’Reilly Media, Inc.  
• Pro Git book, written by Scott Chacon and Ben Straub and published by Apress, https://git scm.com/book/en/v2 
• https://infyspringboard.onwingspan.com/web/en/app/toc/lex_auth_0130944433473699842782_shared /overview 
• https://infyspringboard.onwingspan.com/web/en/app/toc/lex_auth_01330134712177459211926_share d/overview  
  

Template for Practical Course and if AEC is a practical Course Annexure-V  

PHP Programming Semester 3  

Course Code BAI358D CIE Marks 50 Teaching Hours/Week (L:T:P: S) 0:0:2:0 SEE Marks 50 Credits 01 Exam Hours 02 Examination type (SEE) Practical  

Course objectives:  

• To introduce the PHP syntax, elements, and control structures  
• To make use of PHP Functions and File handling  
• To illustrate the concept of PHP arrays and OOPs  

Sl.NO Experiments  

AIM: Introduction to HTML/PHP environment, PHP Data Types, Variables, Literals, and operators  

1 a. Develop a PHP program to calculate areas of Triangle and Rectangle.  

1. Develop a PHP program to calculate Compound Interest.  

2 Demonstrating the various forms to concatenate multiple strings  

Develop program(s) to demonstrate concatenation of strings:  

(i) Strings represented with literals (single quote or double quote)  

(ii) Strings as variables  

(iii) Multiple strings represented with literals (single quote or double quote) and variables  (iv) Strings and string variables containing single quotes as part string contents  

(v) Strings containing HTML segments having elements with attributes  

3 a. Develop a PHP Program(s) to check given number is:  

(i) Odd or even  

(ii) Divisible by a given number (N)  

(iii) Square of a another number  

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1. Develop a PHP Program to compute the roots of a quadratic equation by accepting the coefficients.  Print the appropriate messages.  

4 a. Develop a PHP program to find the square root of a number by using the newton’s algorithm. b. Develop a PHP program to generate Floyd’s triangle. 

5 a. Develop a PHP application that reads a list of numbers and calculates mean and standard deviation.  b. Develop a PHP application that reads scores between 0 and 100 (possibly including both 0 and 100)  and creates a histogram array whose elements contain the number of scores between 0 and 9, 10 and  19, etc. The last “box” in the histogram should include scores between 90 and 100. Use a function to  generate the histogram.  

6 a. Develop PHP program to demonstrate the date() with different parameter options.  b. Develop a PHP program to generate the Fibonacci series using a recursive function. 7 Develop a PHP program to accept the file and perform the following  

(i) Print the first N lines of a file  

(ii) Update/Add the content of a file  

8 Develop a PHP program to read the content of the file and print the frequency of occurrence of the word  accepted by the user in the file  

9 Develop a PHP program to filter the elements of an array with key names.  

Sample Input Data:  

1st array: (‘c1’ => ‘Red’, ‘c2’ => ‘Green’, ‘c3’ => ‘White’, c4 => ‘Black’) 

2nd array: (‘c2’, ‘c4’)  

Template for Practical Course and if AEC is a practical Course Annexure-V  

Output:  

Array  

(  

[c1] => Red  

[c3] => White  

)  

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10 Develop a PHP program that illustrates the concept of classes and objects by reading and printing  employee data, including Emp_Name, Emp_ID, Emp_Dept, Emp_Salary, and Emp_DOJ.  

11 a. Develop a PHP program to count the occurrences of Aadhaar numbers present in a text.  b. Develop a PHP program to find the occurrences of a given pattern and replace them with a text.  12 Develop a PHP program to read the contents of a HTML form and display the contents on a browser. 

NOTE: Necessary HTML elements (and CSS) can be used for designing the experiments.  

Course outcomes (Course Skill Set):  

At the end of the course, the student will be able to:  

• Apply basic concepts of PHP to develop web program  
• Develop programs in PHP involving control structures  
• Develop programs to handle structured data (object) and data items (array)  
• Develop programs to access and manipulate contents of files  
• Use super-global arrays and regular expressions to solve real world problems.  
  

Template for Practical Course and if AEC is a practical Course Annexure-V  Assessment Details (both CIE and SEE)  

15.09.2023 14.09.2023

The weightage of Continuous Internal Evaluation (CIE) is 50% and for Semester End Exam (SEE) is 50%.  The minimum passing mark for the CIE is 40% of the maximum marks (20 marks out of 50) and for the  SEE minimum passing mark is 35% of the maximum marks (18 out of 50 marks). A student shall be  deemed to have satisfied the academic requirements and earned the credits allotted to each subject/ course if the student secures a minimum of 40% (40 marks out of 100) in the sum total of the CIE  (Continuous Internal Evaluation) and SEE (Semester End Examination) taken together  

Continuous Internal Evaluation (CIE):  

CIE marks for the practical course are 50 Marks.  

The split-up of CIE marks for record/ journal and test are in the ratio 60:40.  

• Each experiment is to be evaluated for conduction with an observation sheet and record write-up.  Rubrics for the evaluation of the journal/write-up for hardware/software experiments are  designed by the faculty who is handling the laboratory session and are made known to students at  the beginning of the practical session.  
• Record should contain all the specified experiments in the syllabus and each experiment write-up  will be evaluated for 10 marks.  
• Total marks scored by the students are scaled down to 30 marks (60% of maximum marks).  ● Weightage to be given for neatness and submission of record/write-up on time.  
• Department shall conduct a test of 100 marks after the completion of all the experiments listed in  the syllabus.  
• In a test, test write-up, conduction of experiment, acceptable result, and procedural knowledge will  carry a weightage of 60% and the rest 40% for viva-voce.  
• The suitable rubrics can be designed to evaluate each student’s performance and learning ability.  
• The marks scored shall be scaled down to 20 marks (40% of the maximum marks).  The Sum of scaled-down marks scored in the report write-up/journal and marks of a test is the total CIE  marks scored by the student.  

Semester End Evaluation (SEE):  

• SEE marks for the practical course are 50 Marks.  
• SEE shall be conducted jointly by the two examiners of the same institute, examiners are  appointed by the Head of the Institute.  
• The examination schedule and names of examiners are informed to the university before the  conduction of the examination. These practical examinations are to be conducted between the  schedule mentioned in the academic calendar of the University.  
• All laboratory experiments are to be included for practical examination.  
• (Rubrics) Breakup of marks and the instructions printed on the cover page of the answer script  to be strictly adhered to by the examiners. OR based on the course requirement evaluation  rubrics shall be decided jointly by examiners. 
  

Template for Practical Course and if AEC is a practical Course Annexure-V  

• Students can pick one question (experiment) from the questions lot prepared by the examiners  jointly.  
• Evaluation of test write-up/ conduction procedure and result/viva will be conducted jointly by  examiners.  
• General rubrics suggested for SEE are mentioned here, writeup-20%, Conduction procedure and  result in -60%, Viva-voce 20% of maximum marks. SEE for practical shall be evaluated for 100 marks  and scored marks shall be scaled down to 50 marks (however, based on course type, rubrics shall be  decided by the examiners) 
• Change of experiment is allowed only once and 15% of Marks allotted to the procedure part are to be  made zero.  

The minimum duration of SEE is 02 hours  

Suggested Learning Resources:  

15.09.2023 14.09.2023

• BOOK: Programming in HTML and PHP (Coding for Scientists and Engineers, BY DEVID R BROOKS,  Springer International Publishing AG 2017  
• PHP TUTORIALS: [https://www.w3schools.com/php/}  
• PHP TUTORIALS: [ https://www.tutorialspoint.com/php/index.htm]  
• HTML TUTORIALS: [https://www.w3schools.com/html/]