Programme Educational Objectives (PEOs)

PEO1: Graduates will demonstrate proficiency in applying Artificial Intelligence and Data Science methodologies to solve complex real-world problems across various domains, utilizing a wide range of techniques such as statistics, machine learning, data analytics and AI.

PEO2: Graduates will excel in pioneering algorithm development, interdisciplinary collaboration, ethical AI practices, data analysis, striving for positive societal impact and personal growth in the realms of Artificial Intelligence and Data Science.

Program Specific Outcomes (PSO’s)

Graduate of the Artificial Intelligence and Data Science program will demonstrate,

PSO1: Graduates will possess the skills to leverage Artificial Intelligence as a foundation, identifying domain-specific requirements and designing effective decision-making processes to drive impactful outcomes across diverse fields.

PSO2: Graduates will apply Artificial Intelligence and Data Science techniques, such as data analytics, machine learning, search algorithms and neural networks, to design novel algorithms for solving practical and social problems, utilizing theoretical knowledge and industrial tools.

Program Outcomes (POs)

  • Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
  • Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusion using first principles of mathematics, natural sciences, and engineering sciences.
  • Design/development of solutions: Design solution 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
  • Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
  • 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.
  • 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.
  • 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.

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