Department of Emerging Technology

We’re talking about Shaping Future Innovators and Industry Leaders in AI & ML and Data Science

The Department of Emerging Technologies offers Two undergraduate B.Tech. programs in CSE (AI & ML) and CSE (Data Science), each with an intake of 60 seats starting from 2020.

 

The CSE (AI & ML) program provides aspiring engineers with a comprehensive range of courses focused on cutting-edge developments in Artificial Intelligence and Machine Learning, built on a foundation of Computer Science and Engineering. The CSE (Data Science) program teaches algorithms and concepts for creatively managing large datasets to generate business value, combining practical classes with self-study to focus on data preparation, analysis, and visualization for better business decision-making.

The CSE (AI & ML) program aims to produce skilled AI and ML engineers who can create innovative solutions and transform industries. It targets students seeking challenging and rewarding careers, meeting the high demand for well-paid AI and ML professionals worldwide.

Programs Offered

  • B.Tech Computer Science and Engineering (Data Science)
  • B.Tech Computer Science and Engineering (Artificial Intelligence and Machine Learning)

Career paths you can choose after the CSE (AI & ML) program:

  • Machine Learning Engineer
  • Artificial Intelligence Engineer
  • Machine Learning Architect
  • Artificial Intelligence Scientist in research and development industries like IBM, Adobe, Microsoft.

This CSE (Data Science) program aims to train students in utilizing algorithms and concepts to extract valuable insights from large datasets for business purposes. Through practical classes the students learn data analysis, visualization, predictive modelling, and programming skills for data-driven decision-making, complemented by offerings in machine learning, artificial intelligence, and deep learning to meet industry needs.

Career paths you can choose after the CSE (Data Science) program:

  • Data Scientist
  • Data Analytics
  • Data Science Architect
  • Database Administrator
  • Data scientist in research and development industries like; IBM, Adobe, Microsoft.

Department Vision

  • To evolve as a Center of Excellence in the field of Computer Science and to train the students in becoming well equipped computing professionals to serve the needs of Industry and Society.

Department Mission

  • To provide quality education and training in the field of Computer Science and Engineering along with societal and ethical values, to serve the Nation with élan.

Program Educational Objectives (PEOs)

  • Graduates are able to work effectively as an individual and in teams to have a successful career.
  • Graduates have a professional attitude, ethical values and a desire to learn emerging trends and technologies for product development useful to the society.
  • Graduates are able to pursue higher studies in reputed Institutions.

Program Specific Outcomes (PSOs)

  • To analyze, design & develop solutions for real-world problems.
  • Ability to apply the knowledge of emerging technologies of computer science to societal needs.

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.