B.Tech in Computer Science (AI & ML) 2026: Notification, Fees, Eligibility Criteria, Application Form, Syllabus & Top Colleges

B.Tech in Computer Science with a specialization in Artificial Intelligence and Machine Learning (AI & ML) is a four-year undergraduate program that combines the fundamentals of computer science with advanced concepts of data-driven technologies. The course is designed to prepare students for emerging roles in automation, intelligent systems, data analytics, robotics, and deep learning.

Students learn programming, algorithms, database systems, operating systems, as well as specialized subjects such as neural networks, natural language processing, reinforcement learning, and big data technologies. By the end of the course, graduates are skilled in developing smart applications and solutions that can simulate human intelligence.

Top Indian Colleges and Universities Offering B.Tech (CSE with AI/ML)

Several reputed institutions in India offer this specialization either as a dedicated program or as an elective track under Computer Science. Some of the top names include:

• Indian Institute of Technology (IIT) Hyderabad – Offers B.Tech in AI, one of the first of its kind in India.
• Indian Institute of Information Technology (IIIT) Hyderabad – Known for strong research in AI/ML.
• Delhi Technological University (DTU), Delhi – Provides a B.Tech program with AI specialization.
• Vellore Institute of Technology (VIT), Vellore – Offers AI/ML as a specialization under CSE.
• SRM Institute of Science and Technology, Chennai – Provides B.Tech CSE with AI/ML focus.
• Amrita Vishwa Vidyapeetham, Coimbatore – Recognized for its industry-oriented AI curriculum.
• University of Petroleum and Energy Studies (UPES), Dehradun – Offers B.Tech in CSE with AI & ML.
• Lovely Professional University (LPU), Punjab – Provides a specialization in AI and ML under its CSE program.

Admission Process

The admission procedure generally follows two main routes:

1. Entrance Exam based Admission

Most premier institutes admit students based on national or state-level entrance examinations.

• IITs & NITs – Admission through JEE Main and JEE Advanced, followed by JoSAA counselling.
• IIITs & Central Universities – Through JEE Main or CUET-UG depending on the institution.
• State Engineering Colleges – Admission via state-level exams such as MHT-CET (Maharashtra), WBJEE (West Bengal), KEA (Karnataka), etc.

2. Direct/Management Quota Admission

Some private universities admit students based on their 10+2 marks (Physics, Chemistry, and Mathematics) without requiring an entrance exam. Institutions may also conduct their own admission tests (e.g., VITEEE for VIT, SRMJEEE for SRM).

Eligibility Criteria

• Completion of 10+2 with Physics, Chemistry, and Mathematics as compulsory subjects.
• A minimum of 50–60% aggregate marks in 10+2 (varies by institution).
• Qualifying score in relevant entrance examinations (if applicable).

Career Opportunities After B.Tech in Computer Science (AI & ML)

A degree in B.Tech Computer Science with specialization in Artificial Intelligence and Machine Learning opens doors to a wide range of exciting and future-ready careers. AI and ML are at the heart of modern innovation, powering technologies like self-driving cars, intelligent voice assistants, fraud detection systems, and medical diagnosis tools. Below are the detailed career opportunities:

1. Machine Learning Engineer

• Job Responsibility: Focuses on building and deploying ML models that can make predictions or automate tasks.
• Skills Needed: Python, R, TensorFlow, PyTorch, data preprocessing, model optimization.
• Industries: Finance (fraud detection), Healthcare (diagnosis), Retail (customer behavior prediction).

2. Data Scientist

• Job Responsibility: Analyzes complex datasets to uncover patterns, trends, and insights that support decision-making.
• Skills Needed: Statistics, data visualization, big data tools (Hadoop, Spark), programming.
• Industries: E-commerce (recommendation systems), Marketing (customer segmentation), Banking (risk assessment).

3. AI Research Scientist

• Job Responsibility: Works on developing advanced AI models, deep learning algorithms, and exploring new technologies.
• Skills Needed: Strong mathematical background, research skills, proficiency in ML frameworks.
• Industries: Academia, Research Labs, Technology Giants (Google, Microsoft, IBM Research).

4. Business Intelligence (BI) Developer

• Job Responsibility: Designs and develops BI tools, dashboards, and reports to help organizations make data-driven decisions.
• Skills Needed: SQL, Power BI, Tableau, data warehousing, ETL processes.
• Industries: IT Services, Consulting, Retail, Telecommunications.

5. Robotics Engineer

• Job Responsibility: Designs and develops AI-powered robots that can perform human-like tasks.
• Skills Needed: Robotics programming (ROS), computer vision, automation tools, sensors integration.
• Industries: Manufacturing (automation), Healthcare (surgical robots), Defense (autonomous drones).

6. Natural Language Processing (NLP) Engineer

• Job Responsibility: Specializes in enabling machines to understand and process human languages (speech and text).
• Skills Needed: NLP libraries (NLTK, spaCy), linguistics, chatbots, voice recognition systems.
• Industries: Customer Service (chatbots), Social Media (content moderation), Healthcare (voice transcription).

7. Computer Vision Engineer

• Job Responsibility: Develops systems that can process, interpret, and understand visual information from the world.
• Skills Needed: Image recognition, OpenCV, CNNs, deep learning models.
• Industries: Automotive (self-driving cars), Security (surveillance), Retail (visual product recognition).

8. Software Developer (AI-based Applications)

• Job Responsibility: Creates software solutions integrated with AI/ML features like recommendation systems, predictive analytics, or personalization engines.
• Skills Needed: Full-stack development, APIs, cloud platforms (AWS, Azure, Google Cloud).
• Industries: SaaS companies, Startups, IT Services.

9. AI Consultant

• Job Responsibility: Advises organizations on integrating AI solutions into their business processes.
• Skills Needed: Technical knowledge + business strategy, project management, domain expertise.
• Industries: Consulting firms, Enterprises adopting AI transformation.

10. Entrepreneurship & Startups

• Opportunity: Many graduates choose to launch their own AI-based startups in areas such as EdTech, FinTech, HealthTech, and Automation.
• Skills Needed: Innovation mindset, product development, business acumen, AI/ML expertise.

Frequently Asked Questions