Programs
B. Tech. Computer Science
and Engineering (Artificial Intelligence)
B.Tech Computer Science and Engineering
(Artificial Intelligence)
The B.Tech in Computer Science and Engineering (Artificial Intelligence) at S-VYASA is a rigorous programme. It is designed to cultivate intellectual rigour and advanced technical proficiency in intelligent systems. The curriculum, anchored in core computer science, integrates disciplines such as artificial intelligence, machine learning, and data science. These components address the complexities of a data-driven world.
Students explore neural networks, deep learning, natural language processing, and computer vision. This enables them to design and deploy intelligent, data-driven systems. The programme emphasises algorithmic precision, predictive analytics, and scalable computing. It fosters a deep understanding of how intelligent technologies are conceptualised and operationalised.
Students engage in research-oriented learning, immersive laboratories, and industry-aligned pedagogy. They develop the ability to innovate in sectors transformed by automation and intelligence. Graduates are positioned to contribute to fields such as healthcare, finance, robotics, and smart technologies.
Eligibility
- Passed 10+2 examination with Physics/ Mathematics/ Chemistry/ Computer Science/ Electronics/ Information Technology/ Biology/ Informatics Practices/ Biotechnology/ Technical Vocational subject/ Agriculture/ Engineering Graphics/ Business Studies/ Entrepreneurship as per table 8.4 Agriculture stream (for Agriculture Engineering).
- Obtained at least 45% marks (40% marks in case of candidates belonging to reserved category) in the above subjects taken together. OR Passed D.Voc. Stream in the same or allied sector.
- (The Universities will offer suitable bridge courses such as Mathematics, Physics, Engineering drawing, etc., for the students coming from diverse backgrounds to prepare Level playing field and desired learning outcomes of the programme).
Program Highlights
AI-Centric Curriculum:
Combines core Computer Science Engineering with specialised subjects in Artificial Intelligence, Machine Learning, and Data Science. There is an in-depth focus on neural networks, deep learning, natural language processing, computer vision, and predictive modelling. The approach emphasises data analytics, statistical modelling, and large-scale data processing. This supports intelligent decision-making.
Experiential Learning Ecosystem:
Hands-on training through AI labs, real-world projects, simulations, and case-based methodologies.
Industry-Aligned Pedagogy:
Curriculum structured in alignment with contemporary industry requirements and emerging AI technologies.
Research & Innovation Focus:
Encourages critical inquiry, interdisciplinary research (combining multiple fields), and development of cutting-edge AI-driven solutions (advanced artificial intelligence applications).Students receive guidance from academicians and practitioners in AI, machine learning, and computational intelligence
Future-Ready Skill Development:
Equips students for AI Engineer, Machine Learning Specialist, Data Scientist, and related roles in intelligent systems.
Program Fee
| PROGRAMME | YEAR'S | FEE AMOUNT |
|---|---|---|
| B.Tech Computer Science and Engineering (Artificial Intelligence) | 1st Year | ₹3,50,000 |
| 2nd Year | ₹3,50,000 | |
| 3rd Year | ₹3,50,000 | |
| 4th Year | ₹3,50,000 |
Registration Fee for All Courses – ₹25,000
(Inclusive of Non-Refundable Administrative Charge – ₹10,000 + Application Fee –
₹1,000)
Career Outcome
Artificial Intelligence Roles:
Opportunities as an AI Engineer, Machine Learning Engineer, and AI Research Associate, focusing on intelligent system design and automation.
Data Scientists or Data Analysts:
Graduates can become Data Scientists or Data Analysts. They specialise in predictive modelling, big data analytics, and data-driven decision-making.
Software Engineer and AI Application Developer:
Opportunities include Software Engineer and AI Application Developer roles. These positions involve building intelligent, scalable, and adaptive software systems.
Cross-Industry Demand:
Career prospects in sectors such as healthcare, finance, e-commerce, manufacturing, and smart technologies.
Research & Higher Education Pathways:
Strong foundation to pursue M.Tech, PhD, or specialised certifications in Artificial Intelligence, Machine Learning, and Data Science.
Global Career Opportunities:
Preparedness for roles in multinational organisations, AI-driven enterprises, and research institutions worldwide.
Entrepreneurial Pathways:
Equips graduates to build AI-driven startups and innovative technology solutions in a rapidly evolving digital ecosystem.