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    This post was last updated on       July 13th, 2021

VISION

Produce world leaders in Artificial Intelligence and Machine Learning through excellence in education and research and build an ecosystem to contribute significantly to the society.

MISSION

The Department of Artificial Intelligence and Machine Learning is committed to:

• Impart rigorous training to generate knowledge through the state-of-the-art concepts and technologies in Artificial Intelligence and Machine Learning.
• Transform professionals into technically competent through innovation and socially responsible.
• Inculcate values of professional ethics, leadership qualities and lifelong learning.
• Establish centres of excellence in leading areas of computing and artificial intelligence.
• Transform the Department of Artificial Intelligence and Machine Learning as a leader in imparting Artificial Intelligence & Machine Learning education and research.

OBJECTIVES

After 2/3 years of graduation, the students will have the ability to:

Analyze, design and implement solutions in and adapt to changes in technology by self /continuous learning.
Engage in higher learning and contribute to technological innovations.
Work with professional ethics as an individual or as a team player to realize the goals of the project or the
organization.
Work with respect for societal values and concern for environment in implementing engineering solutions

Program Educational Objectives (PEOs)

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 (POs)

The Artificial Intelligence and Machine LearningGraduates 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 TeamWork: 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 (PSOs)

 

After Artificial Intelligence and Machine Learning graduation, graduates will be able to:

  1. Cognitive Outcome: 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: 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.