B.E - Computer Science and Engineering (Artificial Intelligence and Machine Learning) - Curriculum

Sep 22, 2026

Uploaded by Mabel

B.E. Computer Science and Engineering (Artificial Intelligence and Machine Learning) curriculum structured across semesters I to IV with theory and practical components. The syllabus lists course codes, course titles, category tags, weekly contact hours split into L/T/P, assigned credits, and maximum marks for CA, FE, and total assessment. Semester coverage includes foundational sciences and computing, followed by artificial intelligence, data structures and algorithms, operating systems, computer networks, data science, and machine learning, with corresponding laboratory courses.

LanguageEnglish

CategoryExam

FormatPDF

Pages248

Reading Time10 h 25 min

AccessFree to download

Semester I

Theory and practical courses

Semester II

Theory and practical courses

Semester III

Theory and practical courses

Semester IV

Theory and practical courses

Semester V

Theory courses (partially shown)

CURRICULUM B.E – COMPUTER SCIENCE AND ENGINEERING (ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING) CURRICULUM | SEMESTER I | | | | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | S.
No. | Course
Code | Course Title | Cat. | Hours /
Week | | | Credit | Max. Marks | | | | | | | | L | T | P | | CA | FE | Total | | 1 | 22MC101 | Induction Program | MC | - | - | - | 0 | - | - | - | | THEORY | | | | | | | | | | | | 2 | 22EN101 | Communicative English (Theory cum Practical) | HS | 2 | 0 | 2 | 3 | 50 | 50 | 100 | | 3 | 22MA101 | Matrices, Calculus and Ordinary Differential Equations | BS | 3 | 1 | 0 | 4 | 40 | 60 | 100 | | 4 | 22PH101 | Engineering Physics | BS | 3 | 1 | 0 | 4 | 40 | 60 | 100 | | 5 | 22CY101 | Engineering Chemistry | BS | 3 | 1 | 0 | 4 | 40 | 60 | 100 | | 6 | 22CS101 | Problem Solving and C Programming | ES | 3 | 0 | 0 | 3 | 40 | 60 | 100 | | 7 | 22MC102 | Heritage of Tamils / தமிழர்மரபு | HS
MC | 1 | 0 | 0 | 1 | 100 | - | 100 | | PRACTICAL | | | | | | | | | | | | 8 | 22CS102 | Computer Practice and C Programming Laboratory | ES | 0 | 0 | 3 | 1.5 | 60 | 40 | 100 | | 9 | 22ME102 | Workshop Manufacturing Practices | ES | 0 | 0 | 4 | 2 | 60 | 40 | 100 | | TOTAL | | | | | | | 22.5 | | | 800 | | SEMESTER II | | | | | | | | | | | | S.
No. | Course
Code | Course Title | Cat. | Hours /
Week | | | Credit | Max. Marks | | | | | | | | L | T | P | | CA | FE | Total | | THEORY | | | | | | | | | | | | 1 | 22MA202 | Linear Algebra and Linear Programming Problems | BS | 3 | 1 | 0 | 4 | 40 | 60 | 100 | | 2 | 22HS201 | Universal Human Values | HS | 2 | 1 | 0 | 3 | 40 | 60 | 100 | | 3 | 22AL201 | Digital Principles and Computer Organization | ES | 3 | 0 | 0 | 3 | 40 | 60 | 100 | | 4 | 22EE101 | Basic Electrical and Electronics Engineering | ES | 3 | 1 | 0 | 4 | 40 | 60 | 100 | | 5 | 22ME101 | Engineering Graphics and Design | ES | 1 | 0 | 4 | 3 | 40 | 60 | 100 | | 6 | 22MCIN01 | Engineering Sprints | EE | 0 | 0 | 2 | 1 | 100 | - | 100 | | 7 | 22MC201 | Tamils and Technology/
தமிழரும்ததொழில்நுட்பமும் | HS
MC | 1 | 0 | 0 | 1 | 100 | - | 100 | | 8 | 22NC201 | NCC COURSE – I (Only for NCC Students) | NC | 3 | 0 | 0 | 3* | 40 | 60 | 100 | | PRACTICAL | | | | | | | | | | | | 9 | 22EN102 | Professional Skills Laboratory | HS | 0 | 0 | 2 | 1 | 60 | 40 | 100 | | 10 | 22PH103 | Physics Laboratory | BS | 0 | 0 | 3 | 1.5 | 60 | 40 | 100 | | 11 | 22CY102 | Chemistry Laboratory | BS | 0 | 0 | 3 | 1.5 | 60 | 40 | 100 | | 12 | 22EE102 | Basic Electrical and Electronics Engineering Laboratory | ES | 0 | 0 | 3 | | 1.5 | 60 | 40 | | 100 | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | TOTAL | | | | | | | | 24.5 | | | | 1100 | | | SEMESTER III | | | | | | | | | | | | | | | S.
No. | Course
Code | Course Title | Cat. | Hours /
Week | | | Credit | | Max. Marks | | | | | | | | | | L | T | P | | | CA | FE | | Total | | | THEORY | | | | | | | | | | | | | | | 1 | 22MA307 | Probability, Statistics and Stochastic Processes | BS | 3 | 1 | 0 | 4 | | 40 | | 60 | 100 | | | 2 | 22AL301 | Artificial Intelligence | PC | 3 | 0 | 0 | 3 | | 40 | | 60 | 100 | | | 3 | 22AL302 | Python Programming and Frameworks | PC | 3 | 0 | 0 | 3 | | 40 | | 60 | 100 | | | 4 | 22AL303 | Data Structures and Algorithm Analysis | PC | 3 | 0 | 0 | 3 | | 40 | | 60 | 100 | | | 5 | 22AL304 | Operating Systems | PC | 3 | 0 | 0 | 3 | | 40 | | 60 | 100 | | | 6 | 22MCIN02 | Innovation Sprints | EE | 0 | 0 | 2 | 1 | | 100 | | - | 100 | | | 7 | 22NC301 | NCC Course – II (Only for NCC Students) | NC | 3 | 0 | 0 | 3* | | 40 | | 60 | 100 | | | PRACTICAL | | | | | | | | | | | | | | | 8 | 22AL305 | Operating Systems Laboratory | PC | 0 | 0 | 4 | 2 | | 60 | 40 | | 100 | | | 9 | 22AL306 | Data Structures and Algorit

FAQs

What information is included for each course in this curriculum table?

Each entry provides the course code, course title, category, weekly hours (L/T/P), credits, and maximum marks split into CA, FE, and total.

Which AI- and ML-related courses appear in the syllabus for the early semesters?

Artificial Intelligence is listed in Semester III, and Machine Learning appears in Semester IV, along with supporting courses such as Python programming, data structures, and operating systems.

Are laboratory components included alongside theory courses?

Yes. The document includes practical/laboratory courses for subjects such as computer programming, operating systems, data structures and algorithms, Python programming, data science, and artificial intelligence and machine learning.

Sep 22, 2026

Uploaded by Mabel