Ashoka University

What you'll study

The programme provides a solid grounding in core computer science while developing specialised knowledge in artificial intelligence and machine learning. Early years emphasise programming, data structures and algorithms, discrete mathematics, linear algebra, probability and statistics, and computer systems. Core AI and CS modules typically include:

• Foundations of Programming — imperative and functional programming, software engineering practices and data structures.
• Algorithms and Complexity — algorithm design, analysis, optimisation and computability.
• Mathematics for Computer Science — discrete maths, linear algebra, calculus and probability theory essential for modelling and learning.
• Machine Learning — supervised and unsupervised methods, model evaluation and regularisation techniques.
• Deep Learning and Neural Networks — architectures, training techniques and practical applications in vision and language.
• Natural Language Processing — language models, parsing, semantics and practical NLP pipelines.
• Computer Systems and Architecture — operating systems, concurrency, networks and performance considerations.
• Databases and Information Retrieval — data modelling, query languages and scalable storage.
• Computer Vision — image processing, feature extraction and recognition systems.
• Ethics, Society and Policy of AI — fairness, accountability, interpretability and the social impact of AI technologies.

Beyond core modules, students choose electives across disciplines — for example cognitive science, economics, biology or design — reflecting Ashoka's liberal arts approach. The degree culminates in a substantial capstone project or honours thesis supervised by faculty, alongside lab coursework and opportunities for industry internships and research collaborations.

Entry requirements

Admission is selective and looks for strong quantitative and analytic preparation plus demonstrated interest in computing and problem solving. Typical expectations include:

• High school completion with solid performance in mathematics; credentials may include national boards, A‑levels, IB or equivalent.
• Evidence of programming experience or computer science coursework is desirable (coding projects, competitive programming, online courses or school subjects).
• Applicants are assessed holistically through the university's admissions process, which may include written work, problem‑solving assessments, essays and interviews.
• Proficiency in English for academic study.

International applicants should meet the university's language and credential requirements; specific test scores or equivalents accepted by Ashoka may be considered as part of the application portfolio.

Career prospects

Graduates are prepared for a broad range of technical and research roles. Common career paths include:

• Software Engineer / Developer — building scalable systems and applications across sectors.
• Machine Learning Engineer — deploying models, feature engineering and production ML pipelines.
• Data Scientist / Analyst — extracting insights from data for business, healthcare and government.
• AI Researcher or Research Assistant — continuing to postgraduate research or supporting academic and industry R&D.
• Product and Technical Roles — AI product management, technical consulting and applied research roles in startups and established firms.
• Further Study — many graduates pursue MSc/PhD programmes in machine learning, AI, computer science, computational biology, or related fields.

The programme's emphasis on projects, internships and writing prepares students both for technical employment and interdisciplinary roles that require clear communication and ethical awareness of AI's societal impact.

Why study at Ashoka University

Ashoka combines a liberal arts ethos with research‑oriented science teaching, so students study computer science and AI within a broader intellectual context. Small class sizes and close faculty mentoring support intensive project work and an honours thesis. Highlights include:

• Interdisciplinary learning — the ability to pair CS and AI study with electives in the humanities, social sciences and natural sciences.
• Research and lab opportunities — faculty‑led research projects, summer internships and industry collaborations that give practical exposure.
• Strong student support — career services, entrepreneurship initiatives and peer communities that help with internships and placements.
• Ethical and societal focus — explicit coursework and seminars on the implications of AI, preparing graduates to design responsible technologies.

Overall, the BSc (Hons) in Computer Science and Artificial Intelligence at Ashoka is well suited to students who want rigorous technical training together with the flexibility to explore wider intellectual and societal questions around AI.