The Department of Artificial Intelligence & Data Science, started in the year 2021, offers B.Tech Artificial Intelligence & Data Science to meet the challenges of higher education, research and innovation in key areas of Data Science and AI. The department aims to develop AI and Data Science engineers who are innovative and entrepreneurial to become global leaders in research and technology.
- Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and Artificial Intelligence and Data Science basics to the solution of complex engineering problems.
- Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
- Design/development of solutions: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.
- Conduct investigations of complex problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
- Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.
- The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
- Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
- Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
- Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
- Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
- Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one‘s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
- Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.
Graduates should be able to
- arrive at actionable Foresight, Insight, hindsight from data for solving business and engineering problems.
- apply the theoretical knowledge of AI and Data Analytics, develop data analytics and data visualization skills with practical industrial tools and techniques to solve societal complex projects.
- able to carry out fundamental research to cater for the critical needs of the society through cutting edge technologies of AI.
Value Added Courses
- Hardware & Networking
- Cyber Security
- Fullstack Web Development ( Python / Angular )
- Redhat Certifications
- Cloud Computing (AWS)
- Android App Development
- Java Essentials
Professional Body Membership
Learn from Links
The Artificial Intelligence & Data Science has 312 computers with high end configuration distributed across seven laboratories with four Blade-Mounted Servers.