B.Sc. in Computer Science – AI
Overview
The programme is designed to equip students with a comprehensive understanding of computer science fundamentals, emphasizing both theoretical knowledge and practical application. It begins by introducing core concepts such as programming logic, data structures, and algorithms, gradually building toward advanced topics like cybersecurity, ethical hacking, and system design. Through a blend of lectures, hands-on labs, and project-based learning, students gain proficiency in languages like C and Python, while also developing analytical thinking and problem-solving skills essential for real-world scenarios.
In addition to technical depth, the curriculum integrates soft skills and professional development modules to prepare students for dynamic roles in academia, industry, and research. Regular assessments, workshops, and certification opportunities foster continuous learning and skill enhancement. The programme also encourages interdisciplinary exploration and holistic growth, aligning with institutional values of excellence, innovation, and integrity. Students emerge not only as competent technologists but also as thoughtful contributors to the rapidly transforming AI-driven digital ecosystem.
Duration & Fees
- Duration: 3 years (6 semesters)
- Eligibility: Pass in 10+2 or equivalent examination from a recognized board (preferable Mathematics, Computer science stream).
- Mode: Full-time (regular)
- Programme Fee: 60,000 Rs Per Year
SAS
Scholarship
SAS provides a range of scholarships and financial aid opportunities to deserving students:
- Merit Scholarships – For students with outstanding academic records.
- Sports & Cultural Scholarships – For achievers in extracurricular activities.
- Need-based Support – Financial assistance for economically weaker students.
- Special Scholarships – For girl students, differently-abled, and minority categories (as per institutional policy).
SAS
Programme Highlights
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Outcome-Based Education (OBE): Focuses on measurable learning outcomes and student-centric teaching.
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Aligned with NEP 2020 & LOCF: Promotes flexibility, multidisciplinary learning, and holistic development.
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Choice-Based Credit System (CBCS): Enables students to tailor their academic journey.
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Intel-NEC program provides hands on training from industry and internship opportunity. As an add on if students wish to study course with Intel-NEC.
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Regular workshops, guest lectures, and industry seminars.
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Emphasis on hands-on labs, project work, and soft skill training.
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Exposure to emerging technologies and real-world applications
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Emphasis on interdisciplinary learning, critical thinking, and practical skills.
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Integration of MOOCs (SWAYAM, NPTEL) for extra credits.
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Internships: Mandatory after Semesters IV & V.
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Dedicated career support through the SAS Placement Cell.
Programme Structure (Semester-Wise)
| Year / Semester | Core Courses (Computer Science-AI) | Ability Enhancement / Language | Skill Enhancement / Electives | Credits |
|---|---|---|---|---|
| Year 1 – Semester I | Programming Fundamentals using C and C++- theory and lab | English I, Tamil I / Hindi I, Environmental Studies, Indian Knowledge System | Mathematics | 22 |
| Year 1 – Semester II | Programming in Python- theory and lab, Data Structures, Data Structures Lab | English II, Tamil II / Hindi II | R Programming | 23 |
| Year 2 – Semester III | Database Management Systems, Database Management Systems Lab, Programming in Java, Programming in Java Lab | English III, Tamil III / Hindi III | UI and UX, Descriptive Statistics /Differential Integral Calculus/ Operation Research | 26 |
| Year 2 – Semester IV | Fundamentals of Artificial Intelligence, Fundamentals of Artificial Intelligence Lab, Operating System, Operating System Lab | Tamil -IV/ Hindi –IV & English-IV | AI Tools, Internet of Things & Internet of Things Lab, Introduction to Indian Knowledge System | 25 |
| Year 3 – Semester V | Fundamentals of Machine Learning, Fundamentals of Machine Learning Lab, Neural Networks, Neural Networks Lab | English for Communication | Sustainable Development Goals, Disaster Management Course, Constitution of India, Research Methodology | 22 |
| Year 3 – Semester VI | Natural Language Processing, Big Data Technologies, Big Data Technologies Lab, Project Work | Emotional Intelligence | Data Analytics / Robotics and its Applications / Pattern Recognition, Organic Farming / Fabrication of Solar Cell / Wastes Management | 22 |
- Career Prospects
- Programme Outcomes
- Placements & Recruiters
A B.Sc Computer science - Artificial Intelligence degree from SAS opens multiple career pathways across industries:
- Software Developer
- System Analyst
- Database Administrator
- Network Engineer
- Web Developer
- Mobile App Developer
- AI/ML Engineer
- Data Scientist
- IoT Developer
- Cyber security Analyst
- AI Engineer
- Machine Learning Specialist
- Data Scientist
- Computer Vision Developer
- Natural Language Processing (NLP) Analyst
By the end of the B.Sc Computer science (Artificial Intelligence) at SAS, graduates will be able to:
- Acquire core computer science principles, including programming, data structures, algorithms, and mathematical reasoning, specialized knowledge in artificial intelligence domains such as machine learning, deep learning, natural language processing, and computer vision, empowering them to develop innovative solutions for real-world challenges across industries.
- Understand the ethical, legal, and societal implications of AI technologies, fostering responsible development and deployment of intelligent systems integrating
- Analyze complex problems, apply computational techniques, and leverage AI tools to derive data-driven insights and strategic decisions in dynamic environments.
- Apply AI concepts with other domains such as healthcare, finance, education, and cybersecurity, promoting cross-functional innovation.
- Demonstrate a strong grasp of communication, teamwork, and leadership skills for successful careers in industry, academia, or entrepreneurship, and encourage lifelong learning through advanced studies and certifications.
The SAS Placement & Career Development Cell supports students with training, career counseling, and placement opportunities. Our B.Sc Computer science (Artificial Intelligence) graduates have been placed in reputed organizations across various sectors.
Top Recruiters Include:
- IT & Analytics: TCS, Infosys, Wipro, HCL, Cognizant, Accenture, Capgemini
- Finance & Consulting: Deloitte, KPMG, EY, PwC, HDFC Bank, ICICI Bank
- Research & Education: Indian Statistical Institute (ISI), National Sample Survey Office (NSSO), Educational Technology Firms, EdTech Startups
- Emerging Tech Firms: Startups in AI, Data Science, FinTech, and Business Analytics
Salary Range: Fresh graduates earn between ₹3 LPA – ₹6 LPA, depending on skills and specialization.
FAQs
Absolutely. The curriculum includes Skill Enhancement Courses (SEC) like Digital Marketing, UI/UX, Ethical Hacking, and internships to build real-world skills.
Students can join our INTEL- NEC program to have hands on industry training
Definitely. The program prepares students for M.Sc., MCA, MBA (IT), and other postgraduate programs, as well as competitive exams.
Programme Brochure
| Category | Details |
|---|---|
| Division | Faculty of Science |
| School Name | School of Computing |
| Department Name | Department of Computer Science |
| Programme Name | BACHELOR OF SCIENCE IN COMPUTER SCIENCE WITH ARTIFICIAL INTELLIGENCE (B.Sc CS with AI) |
Course Basket Overviews
| Course Type | Description |
|---|---|
| Programme Core (PC) | Mandatory core subjects that form the foundation of the Computer Science degree, Programming in C, Python, Java, Data Structures, Operating Systems, Machine Learning. |
| Programme Electives (PE) | Allied Mathematics and physics, Artificial Intelligence, Cybersecurity, Cloud Computing, Internet of Things, Blockchain. Specialized or advanced subjects chosen within the discipline. |
| University Core (UC) | Compulsory courses mandated by the university for all students. Leadership, ethics, sustainability, Indian Knowledge System, peace studies, yoga, life skills. |
| University Electives (UE) | Interdisciplinary or skill-based courses offered across departments. Advertising, Emotional Intelligence, Media Management, Organic Farming, Indian Knowledge Systems. |
Programme Structure (Semester-Wise with Credits)
| Sl. No. | Courses | Credits |
|---|---|---|
| SEMESTER-I | ||
| 1 | Tamil-I/Hindi-I Part-I: | 3 |
| 2 | :English-I Part-II | 3 |
| 3 | Programming Fundamentals using C and C++ DSC– I: | 3 |
| 4 | Programming Fundamentals using C and C++ Lab DSC– I: | 2 |
| 5 | Numerical and Statistical Methods DSE 1 | 6 |
| 6 | Environmental Studies AEC-I : | 4 |
| 7 | Multidisciplinary Elective (MDE-I) MDE-I: | 1 |
| 8 | Indian Knowledge System (IKS-I) IKS-I: | 1 |
| SEMESTER-II | ||
| 9 | Tamil-II/Hindi-II Part I | 3 |
| 10 | English-II Part II | 3 |
| 11 | Python Programming DSC–II: | 3 |
| 12 | Python ProgrammingLab DSC–II: | 2 |
| 13 | Data Structures DSC– III | 3 |
| 14 | Data Structures Lab DSC– III | 2 |
| 15 | R Programming SEC I | 3 |
| 16 | Vocational Education Course VEC-I VEC-I : | 1 |
| 17 | Multidisciplinary Elective (MDE-II) MDE-II: | 1 |
| 18 | Design Thinking Course (DTC) DTC : | 1 |
| 19 | New Literacy Program (NLP) NLP: | 1 |
| SEMESTER-III | ||
| 20 | Part-I:Tamil-III/Hindi-III Part I | 3 |
| 21 | Part-II:English-III Part II | 3 |
| 22 | Database Management Systems DSC– IV: | 3 |
| 23 | : Database Management Systems Lab DSC–IV | 2 |
| 24 | Programming in Java DSC–V | 3 |
| 25 | Programming in Java Lab DSC V | 2 |
| 26 | Operation Research DSE-II: | 5 |
| 27 | UI and UX SEC-II: | 3 |
| 28 | Innovation Entrepreneurship Course IEC: | 2 |
| SEMESTER-IV | ||
| 29 | Part-I:Tamil-IV/Hindi-IV Part I | 3 |
| 30 | Part-II:English-IV Part II | 3 |
| 31 | Fundamentals of Artificial Intelligence DSC–VI: | 3 |
| 32 | Fundamentals of Artificial Intelligence Lab DSC–VI: | 2 |
| 33 | Operating System DSC–VII | 3 |
| 34 | Operating System Lab DSC–VII | 2 |
| 35 | Deep Learning DSE-III: | 5 |
| 36 | AI tools SEC-III: | 3 |
| 37 | Indian Knowledge System (IKS-II) IKS-II: | 1 |
| SEMESTER-V | ||
| 38 | Fundamentals of Machine Learning DSC– VIII: | 3 |
| 39 | Fundamentals of Machine Learning Lab DSC– VIII: | 2 |
| 40 | :Neural Networks DSC–IX | 3 |
| 41 | Neural NetworksLab DSC–IX: | 2 |
| 42 | English for Communication AEC-II - | 4 |
| 43 | Sustainable Development Goals (SDG-I) SDG-I: | 1 |
| 44 | Disaster Management Course (DMC-I_ DMC-I: | 1 |
| 45 | Constitution of India (CI-I) CI-I: | 1 |
| 46 | Research Methodology (RMC) RMC: | 2 |
| SEMESTER-VI | ||
| 35 | Natural Language Processing DSC–X: | 6 |
| 36 | Big Data Technologies DCC–XI: | 3 |
| 37 | Big Data Technologies Lab DSC–XI | 4 |
| 38 | Project Work DSC–XII | 5 |
| 39 | Robotics and its Applications DSE-IV: | 5 |
| 40 | Multidisciplinary Elective (MDE-II) MDE-II | 1 |
| Total Credits: 140 | ||
Total Programme Credits
- B.Sc. Mathematics (3 Years) – ~140 Credits
Note: Programme structure is subject to periodic revisions based on academic council decisions, industry requirements, and accreditation standards. Students will be informed of changes in advance.
