Computing has permeated our lives - very few areas in modern society are untouched by computer science. Every field of human endeavor, be it

Transportation, defense, entertainment, healthcare, education, communication, or social interaction, is impacted positively by it.Computer science is the study of computational systems, including the theoretical foundations of computing, the design and development of software systems, and the application of computing to solve complex, challenging problems in all kinds of business, industry, scientific, and social contexts.


Artificial intelligence is shaping the future of humanity across nearly every industry. it is predicted that it will continue to revolutionize how we live and work and drive disruptive technologies for the foreseeable future. Through AI, computers have the ability to harness massive amounts of data and use their learned intelligence to make optimal decisions and discoveries in fractions of the time that it would take humans. As the demand for AI technology grows, so does the need for talent with the skills to develop and deploy it. The computer science & Engineering program with Artificial Intelligence specialization aims to build computing professionals for the rapidly growing field of AI.

The core of the Computer Science & Engineering (AI) curriculum includes programming languages and methodologies, databases, the analysis of algorithms and data structures, and the study of operating systems. The curriculum continues with advanced data structures, data analytics, cloud computing, and artificial intelligence courses. The program emphasizes developing graduates with an in-depth understanding of machine learning, deep learning, Natural language processing, computer vision, and hands-on experience with leading AI tools. Theoretical learning is integrated with hands-on laboratories and course projects to make the courses highly experiential and contextual.

The coursework is complemented with interventions to sharpen or develop soft skills like communication, teamwork, interpersonal skills, and critical thinking, which are essential for a successful career. From the first to the final year, students have opportunities to carry out several projects in which student teams, working with faculty/industry mentors, put their knowledge to work on a real-world issue to find innovative solutions to engineering problems. As part of the courses, students are introduced to coding competition platforms to level up their programming skills and compete with programmers worldwide. The program also offers the option of doing an internship with industry or research labs. The advanced state-of-the-art research laboratories allow students to work on projects in niche technology areas. The program emphasizes developing graduates with an in-depth understanding of machine learning, deep learning, Natural language processing, computer vision, and hands-on experience with leading AI tools.

Course Curriculum
Semester I
Single Variable Calculus 18EMAB101(4-1-0)
Engineering Physics 15EPHB101 (3-0-0)
Engineering Mechanics 15ECVF101 (4-0-0)
C Programming for Problem Solving 18ECSP101 (0-0-3)
Basic Electrical Engineering 18EEEF101 (3-0-0)
Social Innovation. 15EHSP101 (0-1-1)
Engineering Physics Lab (0-0-1)
Credits – 21
Semester II
Multivariable Calculus 18EMAB102 (4-1-0)
Engineering Chemistry 15ECHB102 (3-0-0)
Problem Solving with Data Structures 18ECSP102 (0-0-3)
Engineering Exploration 15ECRP101(0-0-3)
Basic Electronics 18EECF101(4-0-0)
Basic Mechanical Engg.15EMEF101(2-1-0)
Professional Communication(1-1-0)
Credits – 23
Semester III
Graph Theory and Linear Algebra 15EMAB204(4-0-0)
Discrete Mathematical Structures 19ECSC202 (3-1-0)
Computer Organization and Architecture 21ECSC201(3-0-1)
Data Structures and Algorithms 20ECSC205( 4-0-0)
Database Management System 15ECSC208(4-0-0)
Introduction to AI21ECSC212(2-0-0)
DBA Lab 15ECSP204(0-0-1.5)
Data Structures and Algorithms Lab 19ECSP201(0-0-2)
Database Applications Lab 15ECSP204(0-0-1.5)
Credits – 23.5
Semester IV
Probability & Statistics 20EMAB209(3-0-1)
Signals & Systems 21ECSC213(3-0-1)
Object Oriented Programming 20ECSC204(3-0-0)
Operating System Principles and Programming 21ECSC211 (3-0-1)
Principles of Compiler Design 19ECSC203(3-1-0)
Data Mining & Analysis 21ECSC210(4-0-1)
Object Oriented Programming Lab 20ECSP203(0-0-1.5)
Credits – 26.5
Semester V
Software Engineering 15ECSC301(3-0-0)
Computer Networks 21ECSC312(3-0-0)
Machine Learning 21ECSC313(3-0-0)
Systems Biology 21ECSC311(3-0-0)
Web Technologies Lab 21ESCP304(0-0-2)
CN lab 21ECSP320(0-0-1.5)
Professional Elective-1 XXECSE3XX(3-0-0)
Mini Project 15ECSW301(0-0-3)
Credits – 23
Semester VI
NN & Deep Learning 21ECSC314(3-0-0)
Embedded Intelligent Systems 18ECSC302 (0-0-3)
NN & DL Lab 21ECSP322(0-0-1.5)
Ethics in AI 21ECSC316(2-0-0)
Professional Aptitude & Logical Reasoning 16EHSC301 (3-0-0)
Professional Elective-2XXECSE3XX(3-0-0)
Professional Elective-3 XXECSE3XX(3-0-0)
Minor Project 15ECSW302(0-0-6)
Credits – 24.5
Semester VII
Big Data & Analytics 17ECSC401(2-0-1)
Information Security 20ECSC402(2-0-1)
Professional Elective-4 XXECSE4XX(3-0-0)
Professional Elective-5 XXECSE4XX(3-0-0)
Senior Design Project 20ECSW401(0-0-6)
Credits – 18
Course - Semester VIII
Professional Elective-6 XXECSE4XX(3-0-0)
Open Elective XXECSO4XX(3-0-0)
Capstone Project 20ECSW402 / Industry Project 20ECSI494(0-0-11)
Industry Training18ECSI493(0-0-6)
Credits -17
Programme Educational Objectives (PEOs)

Graduates will demonstrate peer-recognized technical competency to solve, analyze, design, develop, deploy and maintain computing solutions for contemporary problems.

Graduates will demonstrate leadership and initiative to advance professional and organizational goals with a commitment to ethical standards of profession, teamwork, and respect for diverse cultural backgrounds.

Graduates will be engaged in ongoing learning and professional development through pursuing higher education and self-study.

Graduates will be committed to the creative practice of engineering and other professions in a responsible manner contributing to the socio-economic development of society.

Programme Outcomes (POs)
  • Engineering knowledge

    Apply the knowledge of mathematics, science, engineering fundamentals and an engineering specialization for the solution of complex engineering problems.

  • Problem analysis

    Identify, formulate, 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 public health and safety, and 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 complex engineering activities, with an understanding of the limitations.

  • 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 t h e 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 t h e 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

    Recognise the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.

  • Eligibility Criteria

    Karnataka B.Tech applicants must have passed PUC (Class 12) with at least 45% of marks.

    The applicants must have studied Class 12 with Mathematics, Physics and Chemistry/ Biotechnology/ Biology/ Computer Science as the main subjects.

    The applicants must have a valid KCET or COMEDK UGET or JEE Main score to secure B.Tech admission in Karnataka.

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Program Specific Outcomes (PSO)
  • Domain-specific knowledge: An ability to apply techniques to develop computer based solutions in the domain of data, system and network engineering.
  • Software System Construction: Apply design and development principles in the construction of software systems of varying complexity.