Artificial Intelligence involves all those things, in which we can make our computers do the job, that human does. The purpose is to imitate natural intelligence to solve complex real world problem. Machine Learning is making a machine learn on its own without being explicitly programmed. It is an application of AI that provides system the ability to automatically learn and advance from experience. As per the Gartner prediction, by 2020, customers will manage 85% of their relationship with the enterprise without interacting with a human.

GLA University offers B Tech CSE in Artificial Intelligence & Machine Learning covering the topics of Data Science, Machine Learning, Artificial Intelligence, Robotics, Data Engineering and Data Science. There is a Government plan for the deployment of AI in 10 sectors in India e.g. Agriculture, Health Care, Manufacturing, Education and Public Utilities. Hence, the students should look forward to a wide variety of careers after graduating from our B Tech Course in Artificial Intelligence.

Program Outcomes (Common to All B.Tech Programmes)

PO1. Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.

PO2. Problem analysis: Identify, formulate, research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.

PO3. 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.

PO4. 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.

PO5. 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.

PO6. 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.

PO7. 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.

PO8. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.

PO9. Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.

PO10. 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.

PO11. 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.

PO12. 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.

Program Educational Objectives (PEOs)

PEO1: Become globally competent computer professionals, researchers or entrepreneurs, for developing sustainable solutions.

PEO2: Attain positions of leadership in an organization and /or on teams.

PEO3: Engage in lifelong learning to improve their professional skills and knowledge to address industrial and societal needs using latest technologies.

Program Specific Outcomes (PSOs)

PSO1: Solve real world problems using competency in computational logic, analytical ability, system design principles and programming skills.

PSO2: Design and develop hardware and software interfaces along with latest tools and technology to meet the needs of industry.

PSO3: Analyze the algorithmic principles, theory of computation, artificial intelligence and mathematical foundations for the modeling and design of computing systems.

PSO4: Apply knowledge to provide innovative solutions to existing problems and identify research gaps.

Apply Admission Help Syllabus

Career Prospect

  • Machine Learning Engineer
  • Big Data Engineer/Architect
  • Research Scientist
  • Business Intelligence Developer
  • Data Scientist
  • Software Engineer
  • AI Engineer
  • Data Analytics Engineer
  • Robotics Scientist
  • Deep Learning Engineer
  • Computer Vision Engineer
  • Robotics Engineer
  • Duration

    4 years
  • Course Fee

    1st Year : 2,01,000/- INR
    2nd Year : 2,04,000/- INR
    3rd Year : 2,07,000/- INR
    4th Year : 2,10,000/- INR

  • Eligibility

    Passed 10+2 examination with Physics and Mathematics as compulsory subjects along with Chemistry /Computer Science. With at least 60% marks in the above subjects, taken together and 50% marks overall.

  • Admission Process

    Applicants will have to go through the following process:

    • On the basis of performance in the online Multiple Choice Question (MCQ) test of 2 hours duration and personal interview.



  • 500

    MNCs with salary packages ranging from 4.5 to 44 lakhs PA(batch 2022) and still counting...

  • 3000

    Placements offers (batch 2022) & still counting...

  • 76

    Average placement over the last 10 years

  • 44

    Highest package offered