Computer Science and Artificial  Intelligence 

Eligibility Criteria  

55% and above (or equivalent grade) in PUC/12th/any other equivalent exam conducted by a recognized authority / institution in India or abroad.

The engineering program at Chanakya University is designed to provide students with a well-rounded education that extends beyond technical knowledge. Internships and research training are integral components of the curriculum, aligning with the university’s mission to develop transformative leaders and create knowledge for holistic development. Internships offer students the opportunity to gain practical experience in their chosen field, allowing them to apply classroom learning to real-world situations. These experiences help students develop problem-solving skills, adaptability, and an understanding of industry practices. Research training is another key aspect of the program, fostering a spirit of objective inquiry and thought leadership. Students engage in research projects, working closely with faculty mentors to address complex engineering challenges. This hands-on approach encourages them to apply interdisciplinary design principles and think innovatively. Combined with a comprehensive curriculum that includes humanities, ethics, and cultural studies, these experiences empower graduates to be not only competent engineers but also complete human beings who are well-connected to society and its needs.

Programme Highlights

The programs at Chanakya University stand out due to their unique features. They are characterized by a top-down, scientifically created curriculum that focuses on both depth of knowledge and experiential learning. The curriculum includes humanities and Indian Knowledge Systems to create holistic graduates. Students receive soft skill training woven into the technical curriculum, and internships and research training opportunities are integral, fostering innovative problem-solving and thought leadership. The program’s structure encourages students to be not just competent engineers but also well-connected, ethical individuals who are sensitive to societal needs.

The program structure at Chanakya University is thoughtfully designed, with a total of 140 credits. Key features include a strong emphasis on professional core courses, constituting 60% of the program, providing students with a solid foundation in their chosen field. The remaining 40% is dedicated to electives, including project work, offering students the flexibility to explore their interests and gain specialized knowledge. Alongside technical coursework, mandatory non-credit courses in areas like ethics, culture, and social service ensure holistic development. This well-balanced credit distribution equips students with a comprehensive education that combines core expertise, interdisciplinary learning, and personal growth.

Engineering Core (48 Credits)
Sl NoCourse NameLTPCredits
1Data Structures and Algorithms2013
2Computer Organisation and Architecture3003
3Theory of Computation (Formal Languages, Automata Theory)2013
4Operating Systems3003
5Design and Analysis of Algorithms2013
6Database Management Systems2013
7Introduction to Artificial Intelligence2103
8Foundations of Machine Learning 2103
9Data Analytics2103
10Deep Learning2013
11Computer Vision2013
13Natural language Processing2013
14ML Engineering3003
15Generative AI2013
16Mathematical Optimization3003


Computer Science Career Paths:

  1. Software Developer:
    • Role: Create software applications and programs.
    • Skills: Programming languages, problem-solving, organizational skills.
  2. Software Engineer:
    • Role: Develop software solutions using languages like C++, Java, or Python.
    • Skills: Coding, communication, teamwork.
  3. Database Administrator:
    • Role: Manage and supervise databases.
    • Skills: Attention to detail, analytical reasoning, communication.
  4. Cloud Solutions Architect:
    • Role: Design and implement cloud-based solutions.
    • Skills: Cloud services, architecture.
  5. Cybersecurity Analyst:
    • Role: Protect systems and data from cyber threats.
    • Skills: Network security, risk assessment.

Artificial Intelligence Career Paths:

  1. Machine Learning Engineer:
    • Role: Develop and optimize machine learning models.
    • Skills: Data science, programming, statistical analysis.
  2. Data Scientist:
    • Role: Analyze large datasets to extract insights.
    • Skills: Machine learning, data visualization.
  3. AI Research Scientist:
    • Role: Conduct research in AI and develop innovative solutions.
    • Skills: Strong theoretical knowledge, research abilities.
  4. Natural Language Processing (NLP) Engineer:
    • Role: Work on language technologies, chatbots, and sentiment analysis.
    • Skills: NLP, programming.

Core engineering major along with minors:

Explore how combining a core engineering degree with specific minors can enhance your career path and influence typical salary packages. I’ll provide insights for each combination.

  1. Core Engineering Degree + VLSI and Embedded Systems Minor:
    • Career Path
      • Become a VLSI Design Engineer or an Embedded Systems Engineer.
      • Work on designing integrated circuits (ICs) or developing firmware for embedded devices.
    • Skills
      • Digital electronics
      • Verilog/VHDL
      • Microcontrollers
  2. Core Engineering Degree + Cyber Security Minor:
    • Career Path
      • Become a Cybersecurity Analyst or a Network Security Engineer.
      • Protect systems, networks, and data from cyber threats.
    • Skills
      • Network security.
      • Risk assessment.
      • Ethical hacking
  3. Core Engineering Degree + Data Science and Economics Minor:
    • Career Path
      • Explore roles as a Data Scientist, Business Analyst, or Economic Analyst.
      • Analyze data, extract insights, and make data-driven decisions.
    • Skills
      • Data analysis
      • Statistical modeling
      • Economics fundamentals
  4. Core Engineering Degree + Artificial Intelligence and Machine Learning Minor:
    • Career Path
      • Become a Machine Learning Engineer, AI Researcher, or Data Scientist.
      • Work on cutting-edge AI algorithms and applications.
    • Skills
      • Python
      • Machine learning frameworks (TensorFlow, PyTorch)
      • Natural language processing (NLP)