Shaping Future Innovators in Artificial Intelligence and Data Science
The Department of Emerging Technologies offers two undergraduate B.Tech. programs — CSE (Artificial Intelligence & Machine Learning) and CSE (Data Science) — each with an intake of 60 students from 2020.
Programs Offered
B.Tech. Computer Science and Engineering (Artificial Intelligence and Machine Learning)
B.Tech. Computer Science and Engineering (Data Science)
Department of Emerging Technologies – Vision
To emerge as a centre of excellence in Emerging Technologies by advancing education and research in Artificial Intelligence, Machine Learning, and Data Science, while fostering innovation, entrepreneurial, and social responsibility to develop future-ready professionals who contribute to technological progress and societal development.
Department of Emerging Technologies – Mission
To cultivate globally competitive engineers with deep expertise in Artificial Intelligence (AI), Machine Learning (ML), and Data Science by fostering innovation, ethical responsibility, and research-driven problem solving, enabling graduates to advance transformative technologies that elevate industry and society.
B.Tech. CSE (AI & ML) – Program Educational Objectives (PEOs)
PEO 1: Prepare graduates with strong fundamentals in AI/ML, computer science, and problem-solving abilities to address industry requirements.
PEO 2: Develop the ability to apply AI/ML tools and technologies for research, innovation, and practical real-world applications.
PEO 3: Promote lifelong learning, ethical values, and teamwork to contribute effectively to industry and society.
Program Specific Outcomes (PSOs)
PSO 1: Apply AI/ML models, algorithms, and data analysis techniques to solve real-world problems across diverse domains.
PSO 2: Leverage AI/ML for innovation and entrepreneurship to design effective and sustainable solutions.
B.Tech. CSE (Data Science) – Program Educational Objectives (PEOs)
PEO 1: Prepare graduates with strong foundations in Data Science and emerging technologies to design innovative and sustainable solutions.
PEO 2: Encourage graduates to pursue higher studies, engage in research, and embrace continuous learning to adapt to evolving technologies.
PEO 3: Develop graduates with ethical values, leadership qualities, and teamwork skills to make meaningful contributions to industry and society.
CSE (Data Science) – Program Specific Outcomes (PSOs)
PSO 1: Apply concepts of data science, machine learning, and statistical techniques to analyse data and develop effective solutions.
PSO 2: Utilize data-driven approaches and emerging technologies to address industry and societal needs with ethical responsibility and sustainability.
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 conclusions using first principles of mathematics, natural sciences, and engineering sciences.
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.
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 modelling 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.
