Artificial Intelligence & Data Science Engineering

VISION

To be a premier hub of Artificial Intelligence and Data Science, fostering innovation, research, and technological advancements for the benefit of society.

MISSION

● To provide a comprehensive education that integrates foundational principles with practical applications, preparing students for global careers in AI and data science.

● To establish state-of-the-art laboratories, computing resources, and digital platforms that support cutting-edge learning and research in AI and data science.

● To promote ethical AI development and responsible data science practices, ensuring technological advancements contribute positively To society and global well-being.

● To strengthen academia-industry partnerships, facilitating internships, collaborative projects, and entrepreneurial initiatives that drive AI-driven solutions for industiral and societal growth.

● To foster a research-driven environment that promotes innovation in Artificial intelligence, To address real-world challenges.

• Database Design and Management
  
• Design and Analysis of Algorithms
  
• Data Exploration and Visualization
  
• Artificial Intelligence
  
• Operating System
  
• Machine Learning
  
• Fundamentals of Data Science and Analytics
  
• Deep Learning

Programme Educational Objectives (PEOs)

PEO 1: To enable graduates to pursue higher education and research, or have a successful career in industries associated with Artificial Intelligence and Data Science, or as entrepreneurs.

PEO 2: To ensure that graduates will have the ability and attitude to adapt to emerging technological changes

PEO 3: To effectively communicate ideas in oral or written and to promote collaboration with other members of engineering teams.

Programme Outcomes(POs)

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 reaching 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 the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.

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 the 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 the 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 the 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 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.

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.

PROGRAM SPECIFIC OBJECTIVES (PSOs)

1. To analyze, design and develop computing solutions by applying foundational concepts of Artificial Intelligence and Data Science.

2. To apply software engineering principles and practices for developing quality software for scientific and business applications.

3. To adapt to emerging Information and Communication Technologies (ICT) to innovate ideas and solutions to existing/novel problems.