To become a leading center of excellence in Artificial Intelligence and Data Science by providing quality education, promoting research, and collaborating with industries to develop ethical professionals who drive innovation in technology and society.

1. Engineering Knowledge
   Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
2. Problem Analysis
   Identify, formulate, review research literature, and analyze complex engineering problems to reach substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
3. Design/Development of Solutions
   Design solutions for complex engineering problems and design system components or processes that meet specified needs with appropriate consideration for public health, safety, cultural, societal, and environmental issues.
4. Conduct Investigations of Complex Problems
   Use research-based knowledge and research methods including design of experiments, analysis, and interpretation of data, and synthesis of information to provide valid conclusions.
5. 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.
6. The Engineer and Society
   Apply reasoning informed by contextual knowledge to assess societal, health, safety, legal, and cultural issues, and the consequent responsibilities relevant to the professional engineering practice.
7. Environment and Sustainability
   Understand the impact of professional engineering solutions in societal and environmental contexts and demonstrate the knowledge of, and need for sustainable development.
8. Ethics
   Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
9. Individual and Team Work
   Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
10. 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.
11. Project Management and Finance
    Demonstrate knowledge and understanding of 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.
12. 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.

1. Apply AI, Data Science, and related knowledge to solve real-world problems and build successful careers in industry, research, and to become entrepreneurs.
2. Demonstrate ethical values, teamwork, leadership, and strong communication skills.
3. Continue learning and upgrading their skills to stay ahead in AI and Data Science advancements.

1. Gain a strong understanding of AI and Data Science principles, including computational intelligence, statistics, and machine learning, to solve complex real-world problems.
2. Develop practical skills through projects, industry collaborations, and hands-on learning to build intelligent systems while following ethical guidelines.

Teaching Staff