Undergraduate Program

Undergraduate – Computer Science

Computer Science Programme

The undergraduate Computer Science (CS) major at Ashoka acknowledges the relevance of computing and information science to every academic discipline and emphasizes exposure to interdisciplinary research that will drive innovation in the future. In addition to courses in traditional CS fields like systems, theory and AI, students will be able to leverage the multidisciplinary interests of the faculty to study newer fields like human-centred computing, social and information networks, digital humanities, data-driven journalism, and cyber law. They will not only develop a diverse set of skills to prepare for graduate school and for employment but will also be encouraged to launch their own startups or venture into new types of careers using their interdisciplinary training.

Our curriculum takes into account the ACM curriculum guidelines for undergraduate degrees in computer science and exposes students to modern advancements and new sub-fields of computer science.

The main goals of the programme are:

  • Develop the core set of technical skills that will prepare students for employment or further studies

  • Gain a deeper understanding of the scientific and relevant mathematical underpinnings of computer science and learn to apply them practically

  • Identify and solve the most challenging computer science problems, and work towards developing new ideas and creating new knowledge in the field of computer science

  • Understand the social context in which students’ knowledge and work of computer science will be used, and engage in collaborative work with members of a team outside the discipline

Apart from a major in CS, students can also opt for a minor in CS, or inter-disciplinary majors in CS and Entrepreneurship, and in CS and Mathematics. CS major students are strongly encouraged to enrol in the Ashoka Scholars Programme, which will confer postgraduate diplomas following a year of advanced study, research, and field work. This unique one-year programme combines a real-life, academically rigorous research project and internship taken alongside a set of electives so that students can enter into successful academic and professional careers with ample experience in their fields.

The Department offers a doctoral program leading to a Ph.D. in Computer Science. Click Here for more information.

Computer Science Major Requirements (3-years)

To receive a B.Sc. degree with a major in Computer Science at Ashoka University, students must accumulate 100 credit points at the end of three years. The course divisions and credit points requirement within three years for a major in Computer Science are as follows: 

  1. Foundation and Critical Thinking courses (28 credits for batches before teh UG ’23 batch; 36 credits from the UG ’23 batch onwards)

    The foundation courses are drawn from multiple disciplines – History, Economics, English etc with the aim to provide students with a strong foundation in the humanities and liberal arts. Visit this page for a complete description of foundation and co-curricular course requirements.

  2. Co-Curricular courses (4 credits)

  3. Computer Science Major courses (60 credits)

    The course division for Computer Science Major courses is given below:

    1. The student must complete 10 core CS courses for 40 credits. The 10 courses are listed below.

    2. In addition to the 40 credits from core courses, students must take at least 20 credits of electives offered by the CS department.

  4. Other courses (8 credits for batches before the UG ‘ 23 batch; not required for UG ’23 batch onwards).

Computer Science Minor

In order to get a Minor in Computer Science, students are required to take

  • Introduction to Computer Programming, and
  • Five more CS courses. Of these five, at least 3 of them must be from CS core courses list.

Computer Science Concentration

In order to get a Concentration in Computer Science, students are required to take any four (16
credits) Computer Science courses.

Computer Science Interdisciplinary Majors

In order to Major in an interdisciplinary degree, students must accumulate 116 credit points at the end of three years – i.e., 16 credit points more than what is required for a pure Major. The Computer Science department offers two interdisciplinary Majors – (i) Computer Science and Mathematics, and (ii) Computer Science and Entrepreneurship. The course divisions and credit points requirement within three years for these two Interdisciplinary Major are as follows :

  1. Foundation and Critical Thinking courses (28 credits for batches before the UG ’23 batch; 36 credits from the UG ’23 batch onwards)
  2. Interdisciplinary Major courses (76 credits)
  3. Co-Curricular courses (4 credits)
  4. Other courses (8 credits for batches before the UG ‘ 23 batch; not required for UG ’23 batch onwards)

Computer Science and Mathematics

1. A minimum of 76 credit points of Interdisciplinary Major courses.
2. Of these 76 credits

  • A minimum of 36 credits must come from the Computer Science department. Of these 36 credits, a minimum of 28 credits must come from the “Computer Science core course list for CS + Math interdisciplinary Major”. The core list is given below.
  • A minimum of 36 credits must come from the Mathematics department. Of these 36 credits, a minimum of 28 credits must come from ”Mathematics core course list for CS +Math Interdisciplinary Major”. The core list is given below.
  • The remaining 4 credits can come from any Computer Science/Mathematics courses.


Computer Science


Compulsory Courses

Introduction to Computer Programing

Linear Algebra

Computer Organization and Systems

Algebra I

Algorithm Design and Analysis


Computer Networks

Real Analysis

Introduction to Machine Learning Calculus I

Computer Security and Privacy

Multivariable Calculus or Linear Programming

Theory of Computation


The core course list for Compute Science pure Major and Interdisciplinary CS-Math Major are not the same. Core courses for a pure Major include a course on “Probability and Statistics”, but it is not included in the CS core list for Interdisciplinary Major.
The CS “Probability and Statistics” will not be considered as a replacement for the Math course “Probability”. The only exception is if a student changes his/her major from a declared CS major to CS+Math interdisciplinary. In that case that student must have already completed the CS offered “Probability and Statistics” and therefore need not take the Math course “Probability” and instead take up another math course.

Computer Science and Entrepreneurship

For this interdisciplinary Major, students, in addition to 4 courses (16 credits) in the Entrepreneurship department, must complete all Computer Science pure Major requirements.

Computer Science and Philosophy (PHICS)

Dimensions of synergy

• Understanding the nature of computational thinking, AI. Questions of cognition and reasoning

• Understanding models and limits of computation – classical, quantum and physical, biological…

• Limits of modelling of natural processes as computations

• Understanding complexity classes and natural complexity of problems and simulations

• Logic – deductive and inductive; reductions and theorem proving; soundness, completeness and
compactness of logical classes; causality; undecidability

• Nature of information and communication

• Ethics of computation and digitisation

• Fairness and discrimination

• Digital autonomy, privacy and security

Program Structure

1. 28 + 28 credits from CS and Philosophy core
2. 4 credits from Theory of Computation (CS) or Computability Theory (Philo)
3. 8 additional credits from CS or Philosophy open electives
4. Remaining from Foundation courses and university-wide open electives

To major in PHICS students must complete the following 17 courses:

  • PHI-1000: Introduction to Philosophy
  • PHI-1060: Symbolic Logic
  • CS-1101: Introduction to Computer Programming
  • CS-1104: Discrete Mathematics
  • CS-1216: Computer Organization and Systems
  • CS-1205: Algorithm Design and Analysis
  • CS-1309: Introduction to Machine Learning
  • CS-1340: Computer Networks
  • CS-1319: Programming Language, Design and Implementation
  • CS-2349/PHI-2070 :Theory of Computation or Introduction to Computability Theory
  • PHI-X600: one course falling into the broader range of Ethics
  • One course from any of the following categories: PHI-X240 (Philosophy of Science), PHI-X299 (Philosophy of Mathematics), PHI-X300 (Philosophy of Language)
  • Any three Philosophy courses
  • Any two Computer Science courses

Semester-wise Break-up of CS Course Structure

An example path through the CS major may look like this:



  • FC 1
  • FC 2
  • FC 3
  • CT 1


  • Introduction to Computer Programming
  • Discrete Mathematics
  • CT 2
  • FC 4


  • Probability and Statistics
  • Computer Organization and Systems
  • Advanced Programming
  • FC 5


  • Algorithm Design and Analysis
  • Operating Systems
  • CS Elective
  • FC 6


  • Computer Networks
  • Introduction to Machine Learning
  • Programming Language Design and Implementation
  • CS Elective


  • CS Elective
  • CS Elective
  • CS Elective
  • FC 7

Core Courses

Discrete Math

Probability and Statistics

Introduction to Computer Programming

Computer Organization and Systems

Advanced Programming

Operating Systems

Algorithm Design and Analysis

Computer Networks

Introduction to Machine Learning

Programming language Design and Implementation 

Elective Courses

The list of computer science elective courses includes, but are not limited to,

Theory of Computation

Computer security and privacy

Introduction to Human-Computer Interaction 

Data Mining and Information Retrieval

Introduction to Data Bases

Unstructured Information Processing

Advanced Algorithms

Advanced Computer Architecture

Advanced Machine Learning

Linear Programming

Linear Algebra

Blockchain and Cryptocurrencies

Data Driven Journalism

Networked and Social Systems

Information and Coding Theory

Computer Graphics

Software Engineering

Cyber Security

Distributed Systems

An Introduction to Computational Linguistics

Practice-oriented courses (Mobile phone platforms, cloud computing, etc.)

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