About Programme

B. Tech. in Computer Science & Engineering with specialization in Artificial Intelligence & Machine Learning (AI & ML) is a four years undergraduate course, designed to enable students to build intelligent machines, software, or applications with a cutting-edge combination of Artificial Intelligence, Machine learning and Deep Learning technologies after equipping them with the basic fundamentals of Computer Science and Engineering.

The objective is to provide students with the ability to propose resolutions for scientific, technical, and intricate real-world challenges. The aim is to foster the capacity to develop intelligent systems using artificial intelligence (AI) and machine learning (ML) methodologies across diverse disciplines, in order to address societal requirements. The objective is to foster a multidisciplinary approach to design and development.

Application Areas

The major focus of the programme is to create skilled engineers to innovate, design, think and provide intelligent solutions to problems in a variety of domains such as Education, healthcare, security, information forensics, Data virtualization, Agriculture, efficient transportation, smart cities and business applications, in various government and public sectors etc.

Program Education Objectives:

  1. To be able to comprehend, understand and analyse Computer Science Engineering problems related to real life which can be better resolved by artificial intelligence and machine learning.
  2. To impart exhaustive knowledge of Computer Science Engineering, AI and Machine Learning to cater the industrial needs and excel in innovation and management fields by prediction analysis.
  3. To promote collaborative learning and spirit of team work through multidisciplinary AI based projects and diverse professional ethics.
  4. To inculcate a conviction to believe in self, impart professional and ethical attitude and nurture to be an effective team member, infuse leadership qualities, and build proficiency in soft skills and the abilities to relate engineering with the social, political and technical issues as per the current scenario.

Programme Specific Outcomes (PSOs):

  1. The ability to understand, analyse and demonstrate the knowledge of human cognition, Artificial Intelligence and Machine Learning in terms of real world problems to meet the challenges of the future.
  2. The ability to develop computational knowledge and project development skills using innovative tools and techniques to solve problems in the areas related to Artificial Intelligence, Machine learning, Deep Learning.

Programme 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 analyse 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 modelling 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 team work: 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.