Learning Outcomes

Bachelor of Artificial Intelligence Program Objectives:

1. Equipping tech-driven problem solvers to unlock real-world potential through innovative and ethical AI solutions.
2. To cultivate data-driven problem solvers with critical thinking skills, extracting knowledge from data and translating it into impactful AI solutions across diverse domains.
3. To nurture future pioneers of AI research, equipped with a strong theoretical foundation and collaborative spirit, who push the boundaries of knowledge and shape the trajectory of this transformative field.

Bachelor of Data Science Program Objectives:

1. Empower aspiring learners with a robust foundational expertise to devise and implement real-world solutions driven by research.
2. Cultivate graduates with advanced proficiency in data science, nurturing critical thinking skills to extract valuable insights and translate them into impactful solutions across diverse domains.
3. Foster graduates with a strong ethical foundation in data science, instilling a commitment to responsible practices.

Graduate Attributes (GA) of BSDS / BSAI degree programs:

1. GA-1: Academic Education : To prepare graduates as computing professionals
2. GA-2: Knowledge for Solving Computing Problems: Apply knowledge of computing fundamentals, knowledge of a computing specialization, and mathematics, science, and domain knowledge appropriate for the computing specialization to the abstraction and conceptualization of computing models from defined problems and requirements.
3. GA-3: Problem Analysis : Identify, formulate, research literature, and solve complex computing problems reaching substantiated conclusions using fundamental principles of mathematics, computing sciences, and relevant domain disciplines.
4. GA-4: Design/ Development of Solutions : Design and evaluate solutions for complex computing problems, and design and evaluate systems, components, or processes that meet specified needs with appropriate consideration for public health and safety, cultural, societal, and environmental considerations.
5. GA-5: Modern Tool Usage : Create, select, adapt and apply appropriate techniques, resources, and modern computing tools to complex computing activities, with an understanding of the limitations.
6. GA-6: Individual and Team Work : Function effectively as an individual and as a member or leader in diverse teams and in multi-disciplinary settings.
7. GA-7: Communication : Communicate effectively with the computing community and with society at large about complex computing activities by being able to comprehend and write effective reports, design documentation, make effective presentations, and give and understand clear instructions.
8. GA-8: Computing Professionalism and Society : Understand and assess societal, health, safety, legal, and cultural issues within local and global contexts, and the consequential responsibilities relevant to professional computing practice
9. GA-9: Ethics : Understand and commit to professional ethics, responsibilities, and norms of professional computing practice
10. GA-10: Life-long Learning : Recognize the need, and have the ability, to engage in independent learning for continual development as a computing professional

MS Data Science Course Catalogue:

The module description of MS Data Science can be downloaded from here