Duration: 4 Years
Industry Partner
Program Structure
USP: Paid OJT/Work Integration/Internship in Final Year Linked with Placement Opportunities
A UGC and NEP-aligned B.Tech designed to develop strong foundations in Artificial Intelligence, Machine Learning, Data Science, and intelligent systems.
Students learn core AI algorithms, deep learning models, neural networks, and automation techniques that drive modern innovation across industries.
The programme emphasizes practical training through real-world projects, advanced software tools, hackathons, and exposure to the latest AI technologies.
Graduates are equipped with in-demand skills for careers in AI development, data analytics, robotics, predictive modeling, and next-generation computing.
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. Obtained at least 45% marks (40% marks in case of candidates belonging to reserved category) in the above subjects taken together. Whereas Physics & Mathematics are mandatory courses at 10+2 Level.
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 Program.) Whereas Physics & Mathematics are mandatory courses at 10+2 Level.
Ability to design, implement, and optimize intelligent algorithms and data-driven solutions.
Hands-on experience with modern AI tools, frameworks, and real-world projects aligned with industry needs.
Capability to analyze complex datasets and derive meaningful insights for real-world applications.
Ability to collaborate in interdisciplinary teams and present AI-driven solutions professionally.
Skills to conceptualize and build smart systems using machine learning, deep learning, and automation.
Understanding of ethical AI practices, privacy, and responsible development of intelligent systems.
Programming for Problem Solving (Python/Java), Data Structures & Algorithms, Database Management Systems, Discrete Mathematics & Linear Algebra, Probability, Statistics & Optimization, Machine Learning Fundamentals, Deep Learning & Neural Networks, Operating Systems & Computer Networks, Data Mining & Data Warehousing, Software Engineering Principles
Computer Vision & Image Processing, Natural Language Processing (NLP), Generative AI & Large Language Models (LLMs), Reinforcement Learning & AI Agents, Robotics & Automation (ROS), AI for IoT & Edge Computing, Big Data Engineering (Hadoop, Spark), Cloud Computing & MLOps (AWS/Azure/GCP), Cybersecurity for AI Systems, AI in Healthcare, Finance & Smart Cities
Python, R, and C++ Programming, TensorFlow, PyTorch, Keras, Scikit-Learn, Data Analytics Tools: Pandas, NumPy, Tableau, Power BI, Cloud Skills: AWS, Azure, Google Cloud ML Studio, MLOps: Docker, Kubernetes, Git/GitHub, IoT Development with Arduino, Raspberry Pi, NVIDIA Jetson, Robotics Toolkit (ROS, OpenVINO), Hackathons, Industry Internships & Capstone Projects, Problem-Solving, Creativity & Innovation Labs (as per NEP)
Job-ready AI & ML professionals with strong analytical, problem-solving, and industry-relevant.
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