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Undergraduate

B.Tech in Artificial Intelligence & Machine Learning

B.Tech
Artificial Intelligence and Machine Learning

The B.Tech in Artificial Intelligence and Machine Learning (AI&ML) is a cutting-edge undergraduate program designed to equip students with the knowledge and skills required to excel in the rapidly growing field of AI and ML. This program combines the fundamentals of computer science, mathematics, and engineering with advanced topics in AI and ML, enabling students to build intelligent systems that can learn, reason, and solve complex problems.

Throughout the four-year B.Tech in Artificial Intelligence and Machine Learning program, students delve into core areas such as machine learning, deep learning, natural language processing (NLP), computer vision, reinforcement learning, and big data analytics.

The B.Tech AI and ML syllabus emphasizes hands-on learning through practical labs, projects, and industry internships, ensuring students gain real-world experience in designing and deploying AI solutions. Interdisciplinary in nature, the program integrates ethical AI practices, optimization techniques, and applications of AI in fields like healthcare, finance, robotics, and autonomous systems.

Graduates emerge as industry-ready professionals, adept at leveraging AI/ML to innovate and address global challenges. With a strong foundation in AI principles, problem-solving, and computational thinking, this program prepares students for a wide range of career opportunities in AI research, software development, data science, and entrepreneurship, or for advanced studies in AI/ML.

Curriculum Structure
First Semester
S. No. Course Category Course Code Course Title Contact Hours Credits
L T P Total
1 BSC 15B11MA111 Mathematics-1 3 1 0 4 4
2 BSC 15B11PH111 Physics-1 3 1 0 4 4
3 BSC 15B17PH171 Physics Lab-1 0 0 2 2 1
4 ESC 15B11CI111 Software Development Fundamentals-I 3 1 0 4 4
5 ESC 24B15CS111 Software Development Fundamentals Lab-I 0 0 2 2 1
6 ESC 24B11EC111 Basic Electronics 3 1 0 4 4
7 ESC 24B15EC111 Basic Electronics Lab 0 0 2 2 1
8 HSC 15B11HS112 English 1 0 2 3 2
9 ESC 18B15GE111 Engineering Drawing & Design 0 0 3 3 1.5
Total 28 22.5
Second Semester
S. No. Course Category Course Code Course Title Contact Hours Credits
L T P Total
1 BSC 15B11MA211 Mathematics-2 3 1 0 4 4
2 BSC 15B11PH211 Physics-2 3 1 0 4 4
3 BSC 15B17PH271 Physics Lab-2 0 0 2 2 1
4 ESC 15B11CI121 Software Development Fundamentals-II 3 1 0 4 4
5 ESC 24B15CS121 Software Development Fundamentals Lab-II 0 0 2 2 1
6 HSC 24B16HS111 Life Skills & Professional Communication Lab 0 0 2 2 Qualifying
7 ESC 18B15GE112 Workshop 0 0 3 3 1.5
8 HSC 15B11HS111 Universal Human Values (UHV) 2 1 0 3 3
Total 24 18.5
Third Semester
S. No. Course Category Course Code Course Title Contact Hours Credits
L T P Total
1 PCC 15B11CI311 Data Structures and Algorithms 3 1 0 4 4
2 PCC 15B17CI371 Data Structures and Algorithms Lab 0 0 2 2 1
3 PCC 24B11CS213 Database Management Systems 3 0 0 3 3
4 PCC 24B15CS213 Database Management Systems Lab 0 0 2 2 1
5 PCC XXXXXXX Software Engineering 3 0 0 3 3
6 PCC XXXXXXX Software Engineering Lab 0 0 2 2 1
7 PCC XXXXXXX Object Oriented Programming using Python 2 0 2 4 3
8 HSC 15B11HS211 Economics 2 1 0 3 3
9 PRC XXXXXXX Summer Training-I (4 weeks) 0 0 0 0 4
Total 23 23

\

Fourth Semester
S. No. Course Category Course Code Course Title Contact Hours Credits
L T P Total
1 HSC XXXXXXX HSS Elective – 1 2 1 0 3 3
2 PCC XXXXXXX Machine Learning Fundamentals 3 1 0 4 4
3 PCC XXXXXXX Machine Learning Lab 0 0 2 2 1
4 BSC 24XXXXX Mathematical and Statistical Foundations for Computation Intelligence 3 1 0 4 4
5 PCC XXXXXXX Artificial Intelligence 3 1 0 4 4
6 PCC XXXXXXX Artificial Intelligence Lab 0 0 2 2 1
7 PCC 24B11CS312 Operating Systems 3 0 0 3 3
8 PCC 24B15CS312 Operating Systems Lab 0 0 2 2 1
9 OMC 19B13BT211 Environmental Studies 3 0 0 3 Qualifying
Total 27 21
Fifth Semester
S. No. Course Category Course Code Course Title Contact Hours Credits
L T P Total
1 PCC XXXXXXX Deep Learning Foundations 3 1 0 4 4
2 PCC XXXXXXX Deep Learning Lab 0 0 2 2 1
3 PCC XXXXXXX Natural Language Processing 3 1 0 4 4
4 PCC XXXXXXX Natural Language Processing Lab 0 0 2 2 1
5 PCC XXXXXXX Big Data Analytics 3 0 0 3 3
6 PEC XXXXXXX Discipline Elective – 1 2 0 2 4 3
7 BSC XXXXXXX Science Elective 3 0 0 3 3
8 OMC 20B13HS311 Indian Constitution & Traditional Knowledge 3 0 0 3 Qualifying
9 PRC XXXXXXX Summer Training-II (6 weeks) 0 0 0 0 4
Total 25 23
Sixth Semester
S. No. Course Category Course Code Course Title Contact Hours Credits
L T P Total
1 PCC XXXXXXX Generative AI and Emerging Trends 3 0 0 3 3
2 PCC XXXXXXX Generative AI Lab 0 0 2 2 1
3 PCC 24B11CS322 Advanced Data Structures and Algorithms 3 0 0 3 3
4 PCC 24B15CS322 Advanced Data Structures and Algorithms Lab 0 0 2 2 1
5 PCC XXXXXXX Computer Vision Foundations 2 0 2 4 3
6 PEC XXXXXXX Discipline Elective – 2 2 0 2 4 3
7 OEC XXXXXXX Open Elective – 1 2 0 0 2 2
8 VAC XXXXXXX Selected Value-Added Course 1 0 2 3 Audit
9 HSC 24B15HS311 Soft Skill For Employability 0 0 2 2 1
10 PRC XXXXXXX Minor Project 0 0 4 4 2
Total 29 19
Seventh Semester
S. No. Course Category Course Code Course Title Contact Hours Credits
L T P Total
1 PEC XXXXXXX Discipline Elective – 3 3 0 0 3 3
2 PEC XXXXXXX Discipline Elective – 4 3 0 0 3 3
3 PEC XXXXXXX Discipline Elective – 5 3 0 0 3 3
4 OEC XXXXXXX Open Elective – 2 3 0 0 3 3
5 PRC XXXXXXX Major Project Part – 1 0 0 8 8 4
6 PRC XXXXXXX Summer Training - III (6 weeks) 0 0 0 0 4
Total 20 20
Eighth Semester
S. No. Course Category Course Code Course Title Contact Hours Credits
L T P Total
1 PEC XXXXXXX Discipline Elective – 6 3 0 0 3 3
2 PEC XXXXXXX Discipline Elective – 7 3 0 0 3 3
3 OEC XXXXXXX Open Elective – 3 3 0 0 3 3
4 PRC XXXXXXX Major Project Part – 2 0 0 16 16 8
Total 25 17

Total Credits= 22.5 + 18.5 + 23 + 21 + 23 + 19 + 20 + 17 = 164

General Statistics
Semester Subject Count; Total Hours; and Total Credits
First Subject Count = 9; Total Weekly Hours = 28; and Total Credits = 22.5
Second Subject Count = 8; Total Weekly Hours = 24; and Total Credits = 18.5
Third Subject Count = 9; Total Weekly Hours = 23; and Total Credits = 23
Fourth Subject Count = 9; Total Weekly Hours = 27; and Total Credits = 21
Fifth Subject Count = 9; Total Weekly Hours = 25; and Total Credits = 23
Sixth Subject Count = 10; Total Weekly Hours = 29; and Total Credits = 19
Seventh Subject Count = 6; Total Weekly Hours = 20; and Total Credits = 20
Eighth Subject Count = 4; Total Weekly Hours = 25; and Total Credits = 17
Total Subject Count = 64; Total Weekly Hours = 201; and Total Credits = 164
Category Subject Count; Total Hours; and Total Credits
BSC Subject Count = 8; Total Weekly Hours = 27; and Total Credits = 25
ESC Subject Count = 8; Total Weekly Hours = 24; and Total Credits = 18
HSC Subject Count = 6; Total Weekly Hours = 16; and Total Credits = 12
OEC Subject Count = 3; Total Weekly Hours = 8; and Total Credits = 8
OMC Subject Count = 2; Total Weekly Hours = 6; and Total Credits = 0
PCC Subject Count = 23; Total Weekly Hours = 66; and Total Credits = 54
PEC Subject Count = 7; Total Weekly Hours = 23; and Total Credits = 21
PRC Subject Count = 6; Total Weekly Hours = 28; and Total Credits = 26
VAC Subject Count = 1; Total Weekly Hours = 3; and Total Credits = 0
Total Subject Count = 64; Total Weekly Hours = 201; and Total Credits = 164
Frequently Asked Question
What AI-specific ecosystem supports this programme at JIIT?
The programme is supported by initiatives such as the AI for Education, Centre of Excellence and specialised computing facilities like Ramanujan Supercomputer, cybersecurity lab, AI Skill lab etc. where students work on AI-based projects and applications.
What kind of exposure to emerging AI domains does the programme provide?
How is real-world AI problem-solving built into the programme?
How does JIIT ensure the programme stays aligned with current AI trends?
When and how are internships conducted in the AI & ML programme at JIIT?
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