COMPUTER SCIENCE & ENGINEERING (AI & ML)
AI and ML Fundamentals: Introduce students to the fundamental principles and techniques of artificial intelligence and machine learning, covering areas like supervised and unsupervised learning, deep learning, reinforcement learning, and natural language processing.
The program objectives include:- Core Computer Science Knowledge: Provide a solid understanding of core computer science concepts such as algorithms, data structures, computer organization, and software engineering.
- AI and ML Fundamentals: Introduce students to the fundamental principles and techniques of artificial intelligence and machine learning, covering areas like supervised and unsupervised learning, deep learning, reinforcement learning, and natural language processing.
- Programming Skills: Develop proficient programming skills in languages commonly used in AI and ML applications, such as Python, and ensure the ability to implement algorithms and models.
- Problem Solving and Critical Thinking: Foster problem-solving skills and critical thinking abilities, enabling students to analyze complex problems and devise innovative AI/ML solutions.
- Data Handling and Analytics: Equip students with skills in data preprocessing, cleaning, and analysis, as well as an understanding of big data technologies and tools.
- Specialized AI and ML Applications: Provide in-depth knowledge of specialized AI and ML applications, including computer vision, natural language processing, speech recognition, and robotics.
- Practical Experience: Offer hands-on experience through labs, projects, and internships to ensure that students can apply theoretical concepts to real-world problems.
- Interdisciplinary Perspective: Encourage an interdisciplinary approach, allowing students to integrate AI and ML techniques into various domains such as healthcare, finance, and business.
- Ethical and Responsible AI: Instill ethical considerations in AI and ML development, emphasizing the responsible use of technology, fairness, transparency, and privacy.
- Industry Exposure: Facilitate exposure to industry practices, guest lectures, and industry projects to bridge the gap between academic knowledge and real-world applications.
- By achieving these objectives, the program aims to produce graduates who are well-rounded, technically proficient, and capable of contributing to the advancement of AI and ML in various professional settings.
- Program Objectives
- Program Outcomes
- Program Specific Outcomes
Program Objectives
- The objectives of a B.Tech in AI/ML program are as follows:Develop a solid foundation in computer science, mathematics, statistics, and data analysis: The program aims to provide students with a strong foundation in these key areas to develop the necessary skills to become successful data scientists.Learn advanced techniques and tools in data science: The program aims to teach students the latest techniques and tools used in the field of data science, such as machine learning, data mining, big data analytics, and data visualization.
Program Outcomes
- Engineering Knowledge : Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.Problem Analysis : Identify, formulate, research literature, and analyze complex Engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
Program Specific Outcomes
- PSO1 : Provide Industry led/sponsor Teaching Learning facilities.PSO2 : Provide ability to design and develop solution machine learning via sponsor research project.
Departmental Vision
To become the centre of excellence in teaching, research and innovative practices for computing.
Departmental Mission
- To provide a learning ambience to enhance programming skills for problem solving.
- To integrate the software industry and academia in order to utilise technology for research, innovation and entrepreneurship.
- To develop professionals with a solid foundation who can think outside the box to adapt green computing solution.
- To provide a comprehensive computing environment that meets the highest global standards for higher education and lifelong learning.
- To create ethical, skilled engineers through theoretical understanding and practical implementations.
| S.NO | COURSE | DURATION | ELIGIBILITY |
|---|---|---|---|
| 1 | B.Tech | 4 years | Passed 10+2 examination with Physics and Mathematics as compulsory subjects along with one of the Chemistry/ Biotechnology/ Biology/ Technical Vocational subject/ Computer Science/ Information Technology/ Informatics Practices/Agriculture/ Engineering Graphics/ Business Studies. Obtained at least 45% marks (40% marks in case of candidates belonging to reserved category) in the above subjects taken together. |
TOP RECRUITERS
- Clubs/Societies/ Memberships
- Career Prospects
Clubs/Societies/ Memberships
- Society of Computer Science and Engineering.IEEE Student ChapterIEEE Computer SocietyVibgyor and Victree
Career Prospects
- Machine Learning Engineer: Design, develop, and implement machine learning models and algorithms for specific applications, such as image recognition, natural language processing, and recommendation systems.Data Scientist:Analyze large datasets to extract meaningful insights and trends, and use statistical and machine learning techniques to solve complex business problems.