The curriculum for B.Tech. Artificial Intelligence and Data Science (AD) consists of induction
programme, core courses, practical courses, programme elective courses, non-credit pass or fail courses, mini project & main project, internships and various activities. The curriculum is designed for 167 credits and has 7 non-credit courses. 167 credits include activities (co-curricular/extracurricular) of 2 credits. The curriculum is framed to mould eminent professionals with creative minds and innovative ideas. All the core theory courses and elective courses shall have five modules and sixth module for some courses.
SEMESTERWISE CREDIT DISTRIBUTION
Course Code | Course Title | L-T-P | Hours | Credit |
---|---|---|---|---|
102908/CH900A | ENGINEERING CHEMISTRY | 4-0-2 | 6 | 5 |
102908/MA100B | Calculus And Linear Algebra | 4-1-0 | 5 | 4 |
102906/CO100E | Introduction To Electrical And Electronics Engineering | 4-0-0 | 4 | 4 |
102903/CO100F | Introduction To C Programming | 3-0-2 | 5 | 4 |
102908/EN900G | English For Engineers | 2-0-2 | 4 | Pass/Fail |
102909/CO100I | Induction Programme | 6-0-0 | 6 | Pass/Fail |
Course Code | Course Title | L-T-P | Hours | Credit |
---|---|---|---|---|
102906/PH900A | ENGINEERING PHYSICS A | 4-0-2 | 6 | 5 |
102903/MA200B | Complex Analysis And Transforms | 4-1-0 | 5 | 4 |
102903/CE200C | Engineering Mechanics | 3-0-0 | 3 | 3 |
102908/ME900D | Engineering Graphics | 3-0-2 | 5 | 4 |
102008/AD200F | Introduction To Python Programming | 4-0-3 | 7 | 5 |
102906/CO922S | Manufacturing Practices A | 0-0-4 | 4 | 2 |
Course Code | Course Title | L-T-P | Hours | Credit |
---|---|---|---|---|
102008/MA300A | Statistical Foundations For Data Science | 4-0-3 | 7 | 5 |
102903/CO300B | Data Structures | 3-1-0 | 4 | 4 |
102903/MA300C | Discrete Mathematics | 4-0-0 | 4 | 4 |
102008/AD300D | Computer Systems | 3-1-0 | 4 | 4 |
102903/CO900E / 102908/EN900E | Management For Software Engineers / Communication | 3-0-0 | 3 | 3 |
102909/ES900G / 102908/CO900G | Constitution Of India / Environmental Science And | 2-0-0 | 2 | Pass/Fail |
LAB | ||||
102903/CO322S | Data Structures Lab | 0-0-3 | 3 | 2 |
Course Code | Course Title | L-T-P | Hours | Credit |
---|---|---|---|---|
102008/AD400A | Object Oriented Techniques | 4-0-3 | 7 | 5 |
102903/CO400B | DataBase Management Systems | 3-1-0 | 4 | 4 |
102008/MA400C | Optimization Techniques And Numerical Analysis | 4-0-0 | 4 | 4 |
102008/MA400D | Inferential Statistics | 3-1-0 | 4 | 4 |
102908/EN900E / 102903/CO900E | Communication Skills For Professionals / Management For Software Engineers | 3-0-0 | 3 | 3 |
102908/CO900G / 102909/ES900G | Environmental Science And Sustainable Engineering / Constitution Of India | 3-0-0 | 3 | 3 |
LAB | ||||
102903/CO422S | DataBase Management Systems Lab | 0-0-3 | 3 | 2 |
Course Code | Course Title | L-T-P | Hours | Credit |
---|---|---|---|---|
102008/AD500A | Foundations Of Artificial Intelligence | 4-0-3 | 7 | 5 |
102008/AD500B | Fundamentals Of Operating System | 3-1-0 | 4 | 4 |
102008/AD500C | Data Warehousing And Data Mining | 3-1-0 | 4 | 4 |
Elective 1 |
Course Code | Course Title | L-T-P | Hours | Credit |
---|---|---|---|---|
102008/AD501D | Web Programming | 3-1-0 | 4 | 4 |
102008/MA502D | Topology | 3-1-0 | 4 | 4 |
102008/MA505D | Mathematical Economics | 3-1-0 | 4 | 4 |
102902/MA504D | Operations Research | 3-1-0 | 4 | 4 |
102902/MA503D | Applied Linear Algebra | 3-1-0 | 4 | 4 |
102008/AD502D | Foundations Of Secure Computing | 3-1-0 | 4 | 4 |
102008/MA501D | Advanced Statistical Methods | 3-1-0 | 4 | 4 |
102903/MA506D | Advanced Graph Theory | 3-1-0 | 4 | 4 |
102908/ES900E / 102908/EN900F | Industrial Economics/Professional &Business Ethics | 3-0-0 | 3 | 3 |
102908/ES900G / 102908/ME900G | UHV And Social Work With Community Service / Indu | 2-0-0 | 2 | Pass/Fail |
102908/CO900G / 102909/ES900G | Environmental Science And Sustainable Engineering / Constitution Of India | 2-0-0 | 2 | Pass/Fail |
102008/AD522S | Data Mining Lab | 0-0-3 | 3 | 2 |
Course Code | Course Title | L-T-P | Hours | Credit |
---|---|---|---|---|
102008/AD600A | Speech And Language Processing | 4-0-3 | 7 | 5 |
102903/CO600B | Algorithm Analysis And Design | 3-1-0 | 4 | 4 |
102008/AD600C | Machine Learning | 3-0-0 | 3 | 3 |
Elective 2 |
Course Code | Course Title | L-T-P | Hours | Credit |
---|---|---|---|---|
102XXX/XX6XXD | Elective2 | 3-0-0 | 3 | 3 |
102903/CO602D | High Performance And Quantum Computing | 3-0-0 | 3 | 3 |
102008/MA602D | Mathematical Morphology | 3-0-0 | 3 | 3 |
102008/MA603D | Linear Algebra For Data Science | 3-0-0 | 3 | 3 |
102008/MA604D | Topological Data Analysis | 3-0-0 | 3 | 3 |
102902/CO606D | Semantic Web | 3-0-0 | 3 | 3 |
102902/CO607D | Introduction To IoT | 3-0-0 | 3 | 3 |
102008/MA601D | Numerical Methods In Data Science | 3-0-0 | 3 | 3 |
102008/AD601D | Fundamentals Of Autonomous System | 3-0-0 | 3 | 3 |
102902/CO608D | Information Retrieval | 3-0-0 | 3 | 3 |
102903/MA602D | Dynamic Programming And Queueing Theory | 3-0-0 | 3 | 3 |
102908/ES900E / 102908/EN900F | Industrial Economics / Professional And Business Ethics | 3-0-0 | 3 | 3 |
102908/ME900G / 102908/ES900G | Industrial Safety / UHV And Social Work With Community Service | 2-0-0 | 2 | Pass/Fail |
LAB | ||||
102008/AD622S | Machine Learning Lab | 0-0-3 | 3 | 2 |
102008/AD622T | Mini Project | 0-0-2 | 2 | 1 |
Course Code | Course Title | L-T-P | Hours | Credit |
---|---|---|---|---|
Elective 3 |
Course Code | Course Title | L-T-P | Hours | Credit |
---|---|---|---|---|
102008/MA701C | Number Theory And Abstract Algebra | 3-0-0 | 3 | 3 |
102008/MA705C | Stochastic Processes For Data Science | 3-0-0 | 3 | 3 |
102903/CO702C | Cloud Computing | 3-0-0 | 3 | 3 |
102903/CO704C | Image Processing | 3-0-0 | 3 | 3 |
102902/CO703C | Blockchain And Cyber Security | 3-0-0 | 3 | 3 |
102008/AD702C | Genetic Algorithm | 3-0-0 | 3 | 3 |
102008/MA702C | Combinatorics | 3-0-0 | 3 | 3 |
102008/MA703C | Fuzzy Logic And Set Theory | 3-0-0 | 3 | 3 |
102008/AD701C | Data Engineering | 3-0-0 | 3 | 3 |
LAB | ||||
102008/AD701S | Big Data Analytics Lab | 0-0-3 | 3 | 2 |
OPEN ELECTIVE | ||||
Basket 9 |
Course Code | Course Title | L-T-P | Hours | Credit |
---|---|---|---|---|
102908/MA702D | Statistical Methods For Engineering | 3-0-0 | 3 | 3 |
102008/AD700A | Big Data Analytics | 4-1-0 | 5 | 4 |
102008/AD700B | Fundamentals Of Deep Learning | 2-2-0 | 4 | 3 |
Elective 3 |
Course Code | Course Title | L-T-P | Hours | Credit |
---|---|---|---|---|
102008/MA704C | Quantum Topology And Quantum Computing | 3-0-0 | 3 | 3 |
102XXX/XX7XXC | Elective3 | 3-0-0 | 3 | 3 |
OPEN ELECTIVE | ||||
Course Code | Course Title | L-T-P | Hours | Credit |
---|---|---|---|---|
102XXX/XX7XXD | Open Elective | 3-0-0 | 3 | 3 |
Basket 1 |
Course Code | Course Title | L-T-P | Hours | Credit |
---|---|---|---|---|
102906/EC701D | Fundamentals Of IoT | 3-0-0 | 3 | 3 |
102906/EC702D | Fundamentals Of Digital Image Processing | 3-0-0 | 3 | 3 |
102906/EC703D | Embedded System | 3-0-0 | 3 | 3 |
Basket 10 |
Course Code | Course Title | L-T-P | Hours | Credit |
---|---|---|---|---|
102908/ES701D | Entrepreneurship And Economic Policies | 3-0-0 | 3 | 3 |
102908/PH701D | Solar Photovoltaics: Fundamentals To Device Modelling And Fabrication | 3-0-0 | 3 | 3 |
102908/PH702D | Graphene And Low Dimensional Materials | 3-0-0 | 3 | 3 |
102908/PH703D | Astronomy And Astrophysics: Exploring Celestial Dynamics | 3-0-0 | 3 | 3 |
102908/CH701D | Introduction To Functional Materials | 3-0-0 | 3 | 3 |
102908/CH702D | Introduction To Nanoscience | 3-0-0 | 3 | 3 |
102908/EN701D | Soft Skills & Interpersonal Communication | 3-0-0 | 3 | 3 |
Basket 2 |
Course Code | Course Title | L-T-P | Hours | Credit |
---|---|---|---|---|
102906/AE702D | Robotics And Industrial Automation | 3-0-0 | 3 | 3 |
102906/AE701D | Fundamentals Of Mechatronics | 3-0-0 | 3 | 3 |
Basket 4 |
Course Code | Course Title | L-T-P | Hours | Credit |
---|---|---|---|---|
102906/IT701D | Web Designing | 3-0-0 | 3 | 3 |
102906/IT702D | Multimedia Techniques | 3-0-0 | 3 | 3 |
Basket 5 |
Course Code | Course Title | L-T-P | Hours | Credit |
---|---|---|---|---|
102907/EE701D | Electric Vehicles | 3-0-0 | 3 | 3 |
102907/EE702D | Energy Management And Auditing | 3-0-0 | 3 | 3 |
Basket 6 |
Course Code | Course Title | L-T-P | Hours | Credit |
---|---|---|---|---|
102907/ME701D | Quality Engineering And Management | 3-0-0 | 3 | 3 |
102907/ME702D | Renewable Energy Engineering | 3-0-0 | 3 | 3 |
Basket 7 |
Course Code | Course Title | L-T-P | Hours | Credit |
---|---|---|---|---|
102907/CE703D | Traffic Engineering And Road Safety | 3-0-0 | 3 | 3 |
102907/CE702D | Structural Mitigation Of Natural Disasters | 3-0-0 | 3 | 3 |
102907/CE701D | Public Health Engineering | 3-0-0 | 3 | 3 |
Basket 9 |
Course Code | Course Title | L-T-P | Hours | Credit |
---|---|---|---|---|
102908/MA701D | Mathematical Methods For Engineering | 3-0-0 | 3 | 3 |
102908/MA703D | Computational Calculus And Algebra | 3-0-0 | 3 | 3 |
Course Code | Course Title | L-T-P | Hours | Credit |
---|---|---|---|---|
102908/CO7XXG | Rajagiri Elective | 2-0-0 | 2 | Pass/Fail |
LAB | ||||
102XXX/AD7XXS | Practical Elective | 0-0-3 | 3 | 2 |
102008/AD702S | Computer Networks Lab | 0-0-3 | 3 | 2 |
102008/AD703S | Software Engineering Lab | 0-0-3 | 3 | 2 |
102902/CO701S | Image Processing Lab | 0-0-3 | 3 | 2 |
102008/AD722T | Seminar | 0-0-2 | 2 | 1 |
102008/AD722U | Project Work Phase 1 | 0-0-6 | 6 | 3 |
Course Code | Course Title | L-T-P | Hours | Credit |
---|---|---|---|---|
Elective 4 |
Course Code | Course Title | L-T-P | Hours | Credit |
---|---|---|---|---|
102902/CO802A | Introduction To Embedded System Design | 3-0-0 | 3 | 3 |
102902/CO803A | Edge Computing | 3-0-0 | 3 | 3 |
102008/AD801A | Reinforcement Learning | 3-0-0 | 3 | 3 |
102902/CO801A | Business Intelligence And Analytics | 3-0-0 | 3 | 3 |
Elective 5 |
Course Code | Course Title | L-T-P | Hours | Credit |
---|---|---|---|---|
102008/AD802B | Parameterized Algorithms | 3-0-0 | 3 | 3 |
102008/AD803B | Social Network Analysis | 3-0-0 | 3 | 3 |
102008/AD801B | Introduction To Automata, Languages And Computation | 3-0-0 | 3 | 3 |
102008/AD804B | Computer Networks And Internet Protocols | 3-0-0 | 3 | 3 |
Elective 6 |
Course Code | Course Title | L-T-P | Hours | Credit |
---|---|---|---|---|
102008/MA801C | Introduction To Game Theory | 3-0-0 | 3 | 3 |
102902/CO802C | Introduction To Industry 4.0 And Industrial IoT | 3-0-0 | 3 | 3 |
102903/CO803C | Software Testing | 3-0-0 | 3 | 3 |
102902/CO801C | Computer Vision Essentials | 3-0-0 | 3 | 3 |
102908/CO822I | Internship | 0-0-0 | 0 | 2 |
LAB | ||||
102008/AD822U | Project Work Phase 2 | 0-0-16 | 16 | 8 |
102XXX/XX89XW | Mandatory MOOC | 0-0-0 | 0 | Pass/Fail |
INDUCTION PROGRAMME
Induction Programme Shall Include Fundamentals Of Mathematics, Programme Core And
fundamentals Of Computing, Engineering Science, English And Universal Human Values. The Induction Programme Shall Be Conducted At The Beginning Of The First Semester For 15 Days. Distribution Of Hours: Fundamentals Of Mathematics – 16, Programme Core And Fundamentals Of
Computing – 15 (AE/EC/EE/CE/ME - 10 + 5; AD/CS/CU/IT - 15), Engineering Science – 15,
English – 15, Universal Human Values/external Talks – 12 Hours.
PROGRAMME CORE COURSES
The Core Courses Comprise Mathematics, Basic Sciences And Engineering Courses, And Discipline Level Significant Courses Which Are Framed As Per The Need Of Both Academia And Industry. The Core Courses Include The Fundamentals As Well As The Courses To Understand Recent Developments In The Discipline.
PRACTICAL COURSES
Practical Courses, Mostly Based On The Theory The Students Have Studied, Are Meant For Skill
development And Creative Thinking.
PROGRAMME ELECTIVES
Students Can Enrich Their Knowledge In The Domain Of The Programme By Taking 6 Programme
electives. Electives Are Meant To Bridge The Gap Between Academia And Industry. The Department
may Add More Electives With The Recommendation Of The Board Of Studies And Approval Of The
Academic Council. These Electives Are Offered In 5, 6, 7 And 8 Semesters.
PRACTICAL ELECTIVE
Practical Elective Is Meant To Widen The Domain Of Knowledge. Students Can Choose This Course As A Post Requisite Of Any Of The Electives Offered.
NON-CREDIT COURSES
To Inculcate Human Values And Social Awareness, Overcome Hurdles In Different Walks Of Life Andto Face The Challenges In Career Development Non-credit Courses Are Introduced. The Courses Offered Are English For Engineers, Constitution Of India, Environmental Science And Sustainable Engineering, UHV And Social Work With Community Service, Industrial Safety, Rajagiri Electives And Mandatory MOOC. Students Are Required To Pass All The Courses To Get The Degree.
MINI PROJECT
It Is Introduced In The Sixth Semester With The Specific Objective Of Strengthening The
understanding Of Fundamentals Through Effective Application Of Theoretical Concepts. The Mini
project Helps To Boost The Student’s Skills And Widens The Horizon Of Their Thinking. The Ultimate Aim Of An Engineering Student Is To Resolve A Problem By Applying Theoretical Knowledge. Doing More Projects Increases Problem- Solving Skills. Student Groups With 3 Or 4 Members Should Identify A Topic Of Interest In Consultation With Faculty/Advisor, Review The Literature And Gather Information Pertaining To The Chosen Topic, State The Objectives And Develop A Methodology To Achieve The Objectives, Carry Out The Design/fabrication Or Develop Codes/programs To Achieve The Objectives, And Demonstrate The Novelty Of The Project Through The Results And Outputs. The Progress Of The Mini Project Is Evaluated Based On A Minimum Of Two Reviews. The Review Committee May Be Constituted By The Head Of The Department. A Project Report Is Required At The End Of The Semester. The Product Has To Be Demonstrated For Its Full Design Specifications. Innovative Design Concepts, Reliability Considerations, Aesthetics/ergonomic Aspects Taken Care Of In The Project Shall Be Given Due Credit. The Internal Evaluation Will Be Made Based On The Product, The Report And A Viva-voce Examination, Conducted Internally By A Three-member Committee Appointed By The Head Of The Department Comprising The Head Of The Department Or A Senior Faculty Member, Mini Project Coordinator For That Program And Project Guide.
SEMINAR
To Encourage And Motivate The Students To Read And Collect Recent And Reliable Information About Their Area Of Interest Confined To The Relevant Discipline, Each Student Is Required To Prepare A Report Based On A Central Theme, Drawn From Technical Publications Including Peer Reviewed Journals, Conferences, Books, Project Reports Etc. And Present The Same Before A Peer Audience.Each Student Seminar Shall Be Of 20 Minutes Duration. The Report And The Presentation Shall Be Evaluated By A Team Comprising Academic Coordinator For The Respective Program, Seminar Coordinator And Seminar Guide Based On Style Of Presentation, Technical Content, Adequacy Of References, Depth Of Knowledge And Overall Quality Of The Report.
PROJECT WORK PHASE - I
The Project Topic Must Be Selected Either From Research Literature Or It May Be Proposed By The Students In Consultation With Their Guides. The Objective Of Project Work Phase I Is To Enable The Student To Take Up Investigative Study In The Broad Field Of Computer Science And Engineering,either Fully Theoretical/ Practical Or Involving Both Theoretical And Practical Work. It Will Be Assigned By The Department To A Group Of Three/four Students, Under The Mentoring Of A Project Guide(s). This Is Expected To Be A Good Initiation For The Student(s) In R&D Work. The Assignment Shall Normally Include:
• Survey And Study Of Published Literature On The Assigned Topic
• Preparing An Action Plan For Conducting The Investigation
• Working Out A Preliminary Approach To The Problem Relating To The Assigned Topic
• Block Level Design Documentation
• Conducting Preliminary Analysis/ Modelling/ Simulation/ Experiment/ Design/Feasibility
• Preparing A Written Report On The Study Conducted For Presentation To The Department
• Final Project Presentation Before The Concerned Departmental Committee
PROJECT WORK PHASE -II
The Objective Of Project Work Phase II & Dissertation Is To Enable The Student To Extend Further The Investigative Study Taken Up In Project Phase I, Either Fully Theoretical/practical Or Involving Both Theoretical And Practical Work, Under The Mentoring Of A Project Guide From The Department Alone Or Jointly With A Supervisor Drawn From R&D Laboratory/industry. This Is Expected To Provide A Good Training For The Student(s) In R&D Work And Technical Leadership.
The Assignment Shall Normally Include:
• In Depth Study Of The Topic Assigned In The Light Of The Report Prepared In Phase I
• Review And Finalization Of The Approach To The Problem Relating To The Assigned Topic
• Detailed Analysis/ Modeling/ Simulation/ Design/ Problem Solving/ Experiment As Needed
• Final Development Of Product/process, Testing, Results, Conclusions, And Future Directions
• Preparing A Paper For Conference Presentation/ Publication In Journals, If Possible
• Preparing A Dissertation In The Standard Format For Being Evaluated By The Department
• Final Presentation Before The Concerned Evaluation Committee
MANDATORY INTERNSHIP
The Internship Is Meant To Familiarize The Student With The Needs Of The Industry. The Internship Committee Shall Take The Initiative To Find Suitable Industries. Assessment Will Be Based On The Report And Viva Voce.
ACTIVITY POINTS
All Students Have To Earn A Minimum Of 100 Activity Points From Various Activity Segments
listed To Qualify For The B.Tech. Degree. Two Credits Are Given For This On A Pass/ Fail Basis
and Is Mandatory For Getting The B.Tech. Degree. As No Grade Is Given For These Two Credits,
they Are Not Included In The CGPA Calculation.