The Department of Computer Science & Engineering (Artificial Intelligence and Machine Learning) was formed in the Academic Year 2020-2021. The department has started B.Tech programme with an initial intake of 30 in the year 2020 and 60 from 2022 onwards.

The curriculum of B. Tech. Computer Science and Engineering (Artificial Intelligence and Machine Learning) program offered by the Department of Computer Science and Engineering under Academic Regulation 2020 is prepared in accordance with the curriculum framework of AICTE, UGC and Andhra Pradesh State Council of Higher Education (APSCHE). Further this Outcome Based Curriculum (OBC) is designed with Choice Based Credit and Semester System (CBCSS) enabling the learners to gain professional competency with multi-disciplinary approach catering the minimum requirement (Program Specific Criteria) of Lead Societies like ACM and other Professional Bodies as per the Engineering Accreditation Commission (EAC) of ABET and NBA. In addition, the curriculum and syllabi are designed in a structured approach by deploying Feedback Mechanism on Curriculum from various stakeholders viz. Industry, Potential Employers, Alumni, Academia, Professional Bodies, Research Organizations and Parents to capture their voice of the respective stakeholders.

The Curriculum design, delivery, and assessment, the three major pillars of academic system are completely aligned in line with Outcome Based Education (OBE) to assess and evaluate the learning outcomes to facilitate the learners to achieve their Professional and Career Accomplishments. As the institute is registered in ABC, the students have academic flexibility as per ABC in earning the total credits for the award of B. Tech Degree in Regular, Honors and Minors with specialization.


To become Centre of excellence for technically competent, innovative computer engineers.


  1. To provide quality education and spread professional & technical knowledge, leading to a career as computer professionals in different domains of industry, governance and academia.
  2. To provide state-of-art environment for learning and practices.
  3. To impart hands on training in latest methodologies and technologies.


The PEOs are the educational goals that reflect Professional and Career Accomplishments that a graduate should attain after 4 – 5 years of his/her graduation.

The graduates of Computer Science and Engineering (Artificial Intelligence and Machine Learning) of NSRIT will

  1. Be Engineering professionals/innovators/entrepreneurs by adapting and engaging themselves in technology deployment and implementation in the industry
  2. Have a sustained satisfactory professional career in their chosen profession as an individual and/or as a team member/team lead in an IT or allied industry
  3. Engage themselves in life-long learning in advanced studies based on the demand driven need of the industries for their professional and career accomplishments

The POs are the transactional statements of graduate attributes (GAs) that each graduating engineer should possess in terms of knowledge, skill and behavior with a minimum target performance level at the time of graduation as fixed by the program of study seeking continuous improvement year on year.The graduates of Computer Science and Engineering of NSRIT will be able to demonstrate the following outcomes in terms knowledge, skill and behavioral competencies at the time of graduation with the expected target performance level

  1. Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.(Engineering knowledge)
  2. Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences. (Problem Analysis)
  3. 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. (Design/Development of Solutions)
  4. 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. (Conduct investigations of complex problems)
  5. 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.(Modern Tool Usage)
  6. 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.(The engineer and society)
  7. Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development. (Environment and Sustainability)
  8. Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice. (Ethics)
  9. Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings. (Individual and Team Work)
  10. 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. (Communication)
  11. 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. (Project management and finance)
  12. 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. (Life-Long Learning)


  1. Apply the conceptual knowledge of computer science, machine learning and deep learning to solve real world problems
  2. Develop skills to design and develop systems/applications to provide AI based solutions