Program Overview

Affiliated to	Duration	Academic Year	Sanctioned Intake	Exam Structure	Theory Exam
Mumbai University	4 years, Full Time	2 semesters each	60	Theory, Practical, Oral, Term Work	Conducted by University of Mumbai

The Department of Artificial Intelligence and Data Science (AI & DS) is a newly established center of excellence committed to shaping the future of intelligent technology. Launched with the vision to equip students with cutting-edge skills in AI, machine learning, and big data analytics, the department bridges the gap between theory and real-world applications. It offers a multidisciplinary curriculum designed to address the growing demand for AI professionals in industry and research. Through hands-on learning, research projects, and industry collaborations, the department prepares students to build innovative solutions for complex problems. With a strong focus on ethical AI, innovation, and data-driven decision-making, the department aims to develop globally competent technologists and researchers ready for the digital era.

To emerge as a center of excellence in Artificial Intelligence and Data Science, nurturing globally skilled professionals who drive innovation for societal advancement.

1. To nurture continuous learning and research in Artificial Intelligence, Machine Learning, and Data Science to address fundamental and emerging challenges.
2. To inculcate analytical thinking, ethical practices, teamwork, innovation, and entrepreneurial mindset among learners to solve real-world problems.
3. To promote collaboration and knowledge sharing with industries, academia and research organizations at the national and international level to develop impactful AI & DS solutions for societal needs.

Program 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 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 Educational Objectives (PEOs)

1. To acquire strong foundational knowledge in Artificial Intelligence, Machine Learning, Data Science and emerging technologies to solve complex engineering and societal problems.
2. To exhibit professionalism, ethical values, teamwork, communication and leadership skills to excel in multidisciplinary environments.
3. To engage in research, innovation and product development to address global challenges and contribute to technological advancements.
4. To collaborate with industries, academic institutions and research organizations to develop impactful solutions for societal needs.
5. To pursue lifelong learning, entrepreneurship and adapt to evolving technologies to stay globally competent and socially responsible.

Program Educational Objectives (PSOs)

The program aims to develop essential skills and competencies in AIDS Engineering graduates to:

1. Apply foundational concepts of mathematics, statistics, programming, and core computer science to understand the principles of Artificial Intelligence and Data Science.
2. Analyze complex datasets and develop predictive models using machine learning algorithms, statistical techniques, and appropriate data processing tools.
3. Leverage AI and Data Science knowledge for entrepreneurial ventures and contribute to global development through responsible innovation.
4. Demonstrate professional integrity, teamwork, and ethical responsibility in developing AI-driven solutions while considering privacy, fairness, and societal impact.