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Program Educational Objectives

       Within a few years after graduation, graduates of Artificial Intelligence and Machine Learning will be able to:

  1. Apply appropriate theory, practices, and tools to the specification, design, implementation, maintenance, and evaluation of computing and artificial intelligence in the workplace, for advanced studies or for societal needs.
  2. Function effectively in the workplace or maintain employment through lifelong learning such as professional conferences, certificate programs or other professional educational activities, ethics, and societal awareness.
  3. Adapt, contribute and innovate new technologies in their computing profession by working in teams to design, implement, and/or maintain in the key domains of Artificial Intelligence & Machine Learning.
Program Outcomes

        Engineering Graduates will be able to:

  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 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, 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 Outcomes
  1. Cognitive Outcome: Ability to solve complex engineering problems in computing by applying the principles in Artificial Intelligence, Machine Learning, Network Engineering, Software Engineering, Data Engineering and Intelligent Systems.
  2. Skill & Design Outcome: Ability to apply technical skills and research skills through professional societies, certification programs, projects, internships and laboratory exercises to design & develop algorithms, programs, and projects using modern software tools to provide the sustainable solutions to Computer Science, Artificial Intelligence and Machine Learning problems related to the society and environment.