Vision

Impart prime content education to develop technically proficient and socially responsible engineers in the emerging branches of AI.

Mission

1. To provide students with a comprehensive education to prepare them for the rigors in the domain of AI.
2. To establish a platform for academics, innovation, professional growth, and social interaction. 
   
3. To encourage the capacity for lifelong learning necessary for career advancement. 
   
4. To help build relationships with alumni and industry for the betterment of students' overall growth.
   

Artificial Intelligence and Machine Learning : PSO, PO’s & CO’s

Program Specific Outcomes (PSO)

1. Students are exposed to cutting-edge trends and technology to prepare them for challenging work in the industry, higher education, and professional careers.
2. Practice skills learnt in the field of Artificial Intelligence, Data Mining. Machine Learning, Cloud Computing, Optimization, Networking and Security, Deep Learning to different domains such as Healthcare, Education, Agriculture, Finance, Social Media etc.

Program Outcomes (POs)

1. Engineering Knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialisation to the solution of complex engineering problems.
2. Problem analysis: Identify, formulate, research literature, and analyse 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, process to meet the specifications with 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 modelling 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 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. Some of them are, 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 ateam, to manage projects and in multidisciplinary environments.
12. Lifelong Learnings: Recognise the need for, and have the preparation and ability to engage in independent and lifelong learning in the broadest context of technological change.

Course Outcome (CO)

• Course Outcome 2021-22
• Course Outcome R 2019

Artificial Intelligence and Machine Learning : Faculty

Artificial Intelligence & Machine Learning : Technical Staff

•        SE Syllabus
   
•        TE Syllabus

• 2022 - 23
  • How to get internship Opportunity on Feb 28, 2023.
  • Django workshop March 25, 2023.
  • Android app development March 4 & 5, 2023.
  • Advance Python Libraries, June 26 - July 7, 2023

• Department Newsletter FH2023
• Department Newsletter SH2022