| PO-1 |
Disciplinary Knowledge: Demonstrate a comprehensive understanding of
the fundamental concepts, theories, and algorithms in artificial intelligence and
machine learning. |
| PO-2 |
Communication Skills: Communicate effectively about AI and ML concepts,
techniques, and solutions to both technical and non-technical stakeholders. |
| PO-3 |
Problem Solving: Design and develop intelligent systems that are robust, adaptable
and effective in solving complex problems. |
| PO-4 |
Analytical Reasoning: Analyze complex data sets, identify patterns, and draw
meaningful insights using AI and ML techniques, contributing to data-driven
decision-making. |
| PO-5 |
Research-related Skills: Collaborate effectively in interdisciplinary teams,
contributing to research projects or industry applications involving AI and ML. |
| PO-6 |
Employability and Entrepreneurship: Develop proficiency in programming
languages, tools, and libraries used for implementing AI and ML models, and
deploying them in real-world applications. |
| PO-7 |
Moral and Ethical Awareness/Reasoning: Demonstrate an understanding of
the ethical, social, and legal implications of AI and ML technologies, and
develop responsible and unbiased systems. |
| PO-8 |
Critical thinking: Apply critical thinking and reasoning skills to evaluate the
strengths and limitations of AI and ML models, and make informed decisions in
various contexts. |
| PO-9 |
Lifelong Learning: Develop a lifelong learning attitude to stay updated with the
rapidly evolving field of AI and ML, and adapt to new technologies, techniques,
and applications. |