IIT Bombay ePGD in Computer Science and AI for Tech Professionals

e-Postgraduate Diploma (ePGD) in Computer Science and Artificial Intelligence (CS & AI)

Application closes on 10th Nov 2026

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e-Postgraduate Diploma (ePGD) in Computer Science and Artificial Intelligence (CS & AI)

Application closes 10th Nov 2026

ePGD Outcomes

Build, secure and scale enterprise AI systems

Master agentic AI, RL, NLP, and Generative AI, backed by security and data systems.

Architect and build agentic AI systems that automate complex workflows for business use cases.
Make informed AI architecture decisions grounded in a deep understanding modern AI and ML models
Leverage NLP and Generative AI to build solutions that turn unstructured text into business value.
Secure applications, networks and data against evolving threats as AI expands the attack surface.
Engineer scalable, reliable data systems that serve as the foundation for enterprise AI.
Strengthen computational problem-solving and build secure, decentralised applications on blockchain platforms.

Earn an e-Postgraduate Diploma from IIT Bombay

#2 in India

QS World University Rankings, 2026
#2

NIRF India Rankings 2025: Innovation
#28 Globally

QS Rankings in Engineering & Technology, 2025
#3

NIRF India Rankings 2025

ePGD Highlights

Why Choose ePGD in Computer Science and AI?

Learn from the Best: World-Class IIT Bombay CSE Faculty

Learn from distinguished CSE faculty, including ACM/IEEE Fellows and award winners, in weekly live sessions for direct interaction and query resolution.
Shape your ePGD Learning Journey

Choose courses across the AI & ML and Computer Science baskets to make your diploma AI-heavy or technically deep, depending on what your role needs.
Gain Cutting-Edge Depth in AI and Computer Science

Earn 36 credits across six courses, from agentic AI and reinforcement learning to security and data systems, at IIT Bombay’s on-campus standards
Access IIT Bombay’s Lateral Hiring Group

Get access to IIT Bombay’s Lateral Hiring Group to explore new career opportunities as you move into more advanced AI and technology roles.
Flexible Hybrid Learning Built for Working Professionals

Balance a demanding career and advanced study with synchronous and asynchronous sessions, designed for geographically dispersed learners.
Earn the Prestigious IIT Bombay Alumni Status

Elevate your career with official IIT Bombay Alumni status on graduation, connecting you to a global network of engineers and researchers.
In-Person Campus Immersion at IIT Bombay

Visit the campus to meet CSE faculty face-to-face, network with your professional peer group, and experience IIT Bombay’s vibrant academic culture.
On-Campus Graduation Ceremony at IIT Bombay

Celebrate your achievement with classmates and distinguished faculty at an in-person graduation ceremony hosted on the IIT Bombay campus.

Skills you will learn

LLM Frameworks

Autonomous AI Agents

Generative AI & LLMs

Reinforcement Learning

Deep Learning

Computer Vision

RAG

AI architecture

NLP

Cryptographic and network defence principles

LLM Frameworks

Autonomous AI Agents

Generative AI & LLMs

Reinforcement Learning

Deep Learning

Computer Vision

RAG

AI architecture

NLP

Cryptographic and network defence principles

This ePGD is ideal for

Tech professionals who build and run software and AI systems.

Software Development Professionals

For developers shipping enterprise apps who want modern AI and secure design skills to lead AI-native products that withstand evolving threats.
AI and Data Professionals

For ML and analytics practitioners who want generative AI, agents and RL to architect intelligent solutions to complex business problems.
IT and Technology Professionals

For professionals managing infrastructure or networks who want AI, security and data skills to build secure AI infrastructure or move into AI roles.
STEM Graduates

For working technical professionals with a STEM degree who want advanced AI and computing skills to move into AI-focused engineering roles.

About Department of CSE, IIT Bombay

Leading CSE Dept in India

Home to 47 faculty members and top achievers of the First 50 ranks (JEE Advanced) and First 100 ranks (GATE CS)
Accolades for Faculty

Faculty honoured with accolades such as the Padma Shri, Fellow of the ACM and IEEE, Bhatnagar Award, Infosys Prize and many others
Cutting-edge Research

100+ publications annually in top-tier conferences and journals, and sponsored research projects worth Rs. 50 crores
Distinguished Alumni

Winners of the President of India Gold Medal and Distinguished eAlumni Awards, leading researchers, entrepreneurs and influential policymakers

Comprehensive curriculum

This ePGD in Computer Science & Artificial Intelligence includes a rigorous six-course curriculum worth 36 IIT Bombay credits. The courses will be organised into the two baskets mentioned below. To complete this ePGD, learners have to complete a minimum of two courses from each of the two baskets, with a total of six courses across both baskets.

Artificial Intelligence & Machine Learning

Foundational Mathematics for Data Science

In this course, you will learn mathematical techniques that are essential in solving problems traditionally considered challenging for computational machines. You will gain a strong understanding of key methods in linear algebra, statistics and multivariate calculus that are widely used in machine learning. By the end of the course, you will be equipped to apply these mathematical concepts to real-world tasks such as automatic face recognition with pose variations, optimising neural networks and generating realistic images. Topics Covered • Linear Algebra • Statistical Techniques • Multivariate Calculus • Machine Learning Applications • Face Recognition • Neural Network Optimization • Image Generation

Reinforcement Learning

This course will equip you with a comprehensive understanding of how agents make optimal decisions under uncertainty. Starting with multi-armed bandits and Markov Decision Processes (MDPs), you will understand problem abstraction, real-world applications, and core solution techniques. The course then develops expertise in value-based methods, including their extension using function approximation and deep learning for complex, high-dimensional environments. It further covers dierent classes of RL methods such as policy-gradient and actor–critic algorithms, along with trust-region approaches that stabilise learning. You will also explore multi-agent RL settings, understand recent advances in gradient-based RL, and study policy search methods and decision-time planning, ultimately gaining both theoretical foundations and practical tools to design and analyse advanced RL systems. Topics Covered • Multi-Armed Bandits • Markov Decision Processes (MDPs) • Value-Based Reinforcement Learning • Function Approximation • Deep Reinforcement Learning • Policy Gradient Methods • Actor-Critic Algorithms • Trust Region Methods • Multi-Agent Reinforcement Learning • Policy Search • Decision-Time Planning

Foundations of Computer Vision

In this course, you will learn the fundamental concepts and challenges in computer vision, starting with image formation and the camera matrix. You will study the techniques of homographies and calibration, stereo vision, image filtering, filter banks, as well as convolutional neural networks (CNNs) and visual transformers. You will also explore various applications of computer vision, such as classification, segmentation, inpainting, style transfer, motion analysis and depth prediction. Topics Covered • Image Formation & Camera Matrix • Homographies • Calibration & Stereo Vision • Image Filtering • Convolutional Neural Networks (CNNs) • Vision Transformers • Image Classification • Segmentation • Inpainting • Style Transfer • Motion Analysis • Depth Prediction

Generative AI: From Foundations to Autonomous Agents

Generative AI and AI agents are rapidly transforming software, knowledge work, and decision-making across industries. This course equips you with end-to-end practical capabilities, from understanding the mathematical foundations of machine learning and Neural Networks to exploring the inner workings of transformer-based Large Language Models and building LLM applications featuring Retrieval-Augmented Generation (RAG), tool calling (MCP and skills), chain-of-thought reasoning, multi-agent orchestration, memory, security, and evaluation. Topics Covered • Machine Learning Fundamentals • Neural Networks • Large Language Models (LLMs) • Retrieval-Augmented Generation (RAG) • AI Agent Tool Calling • AI Agent Reasoning • Agent Orchestration • Memory • Security • AI Evaluation

Natural Language Processing and Generative AI

In this course, you will learn the foundational concepts of machine learning, deep learning and Generative AI. The course will cover Feed-Forward Neural Networks (FFNN) backpropagation techniques, as well as applications of word vectors in Natural Language Processing. You will explore dierent kinds of Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and learn how they are built, trained and used. You will also study LSTM networks, RCNN, Encoder-Decoder architectures, with a focus on autoregression, self-attention and cross-attention mechanisms used in Large Language Models. Topics Covered • Feed-Forward Neural Networks • Backpropagation • Word Vectors • Convolutional Neural Networks • Recurrent Neural Networks • LSTM Networks • Recurrent Neural Networks (RNN) • Encoder–Decoder Architecture • Autoregression • Self-Attention • Cross-Attention

Computer Science

The Program Developer's Toolbox

In this course, you will be introduced to essential tools and programming environments for software development. You will learn the Unix operating system, the C/C++ programming environment, and various software management tools. The course will cover the concepts behind Python programming, its popular libraries such as NumPy and SciPy, Web programming with HTML, CSS and JavaScript, and elements of AI programming. To solidify your understanding, you will complete a course project that demonstrates your grasp of the key concepts covered in the course. Topics Covered • Unix • C/C++ Programming • Software Management Tools • Python • NumPy • SciPy • HTML • CSS • JavaScript • Security & Cryptography • Reliable AI-Enabled Programming

Algorithms and Complexity

In this course, you will explore foundational concepts of algorithms and computational complexity. You will learn fundamental techniques for solving computational problems like induction, recursion, divide and conquer, dynamic programming and greedy algorithms. You will gain a strong understanding of complexity theory, by studying concepts of undecidability, polynomial-time problems, complexity classes, NP-hardness and NP-completeness. Topics Covered • Induction and recursion, divide and conquer • Dynamic programming • Greedy algorithms • Bipartite matching • Network flow and problem reductions • Undecidability, polynomial-time complexity • Complexity classes NP and co-NP, NP-hardness and NP-completeness

Web and Software Security

This course provides a comprehensive overview of web and software security, focusing on key concepts such as web protocols, session management and server internals. You will explore both server-side and client-side vulnerabilities, and also software and OS security, including the fundamentals of Linux security. You will also learn the use of tools and frameworks like OWASP Top 10 vulnerabilities, CVE database and CVSS scoring, integral to understanding and mitigating cybersecurity risks. Topics Covered • Web background (protocols, session management, server/browser internals etc) • Web security tools (Firefox developer tools and OWASP ZAP) • Server-side web attacks (featuring in OWASP top 10; SSRF, SQL injection, authentication/authorisation vulnerabilities etc) • Client-side web attacks (featuring in OWASP top 10; XSS, CSRF, CORS, Web sockets etc) • Web security landscape and overall defense strategies • Basics of Linux security • Software based attacks (buer overflow, format-string, race conditions etc) and best practices

Cryptography and Network Security

In this course, you will learn both cryptography and network security, starting with an overview of confidentiality, crypto-analysis, data integrity, and cryptographic protocols. You will explore various network attacks across dierent layers of the protocol stack, such as Eavesdropping, ARP spoofing and DHCP attacks. The course also covers secure network protocols, firewalls and intrusion detection systems, providing you with the knowledge to secure and defend modern network infrastructures against potential threats. Topics Covered • Confidentiality primitives: symmetric-key and asymmetric key encryption • Integrity primitives: hashes; Message Authentication Codes (MAC) and digital signatures • Cryptographic protocols: key distribution and public key infrastructure, human and cryptographic authentication • Case study of TLS protocol • Overview of computer networks • Attacks at various layers of the network protocol stack (e.g. MAC flooding, ARP spoofing, DHCP/DNS attacks including DOS) • Secure network protocols (IPsec, DNSSEC) • Firewalls and intrusion detection systems

Database and Big Data System Internals

In this course, you will explore the internals of database systems, covering key concepts such as data storage, indexing, query processing and transaction management. You will learn database system architectures, the internals of big data systems and the challenges of parallel and distributed storage and query processing. The course will provide a strong foundation in building and managing real-world database systems through hands-on assignments with open-source databases and big data systems. Topics Covered • Data Storage • Indexing • Query Processing • Query Optimization • Transactions • Concurrency Control • Database Architecture • Big Data Systems • Distributed Storage • Parallel Query Processing • Recovery Mechanisms

Introduction to Blockchains

In this course, you will explore the motivation and real-world applications of blockchain systems. You will gain an understanding of peer-to-peer and distributed systems, and their core concepts such as consensus mechanisms, Byzantine fault tolerance and impossibility results. The course will also introduce cryptographic tools essential for the functioning of blockchains. You will study Bitcoin, its Proof-of-Work consensus and potential attacks like double spending and selfish mining. You will also examine energy eciency in blockchain, comparing Proof of Stake with Proof of Work consensus models. You will also be introduced to layer-2 scalability solutions such as Lightning Network and Rollups. You will develop smart contracts in Solidity for Ethereum and test them on your personal Ethereum blockchain. Topics Covered • Blockchain Applications • Distributed Systems • Consensus Mechanisms • Byzantine Fault Tolerance • Bitcoin • Proof of Work • Proof of Stake • Double Spending • Lightning Network • Rollups • Solidity • Ethereum

Disclaimer: This is the comprehensive list of approved courses and may not be offered simultaneously. The listed courses are subject to revision, and changes are at the discretion of IIT Bombay. The timing and term in which each course is offered will be entirely at the discretion of IIT Bombay.

Languages and Platforms Covered

The courses cover a variety of languages and platforms, such as

Claude
LangChain
LangGraph
Python
JavaScript
Git
Docker
Wireshark
OWASP Threat Dragon
OpenSSL Toolkit
Rust
NumPy
Scipy

Note: The tools listed above are indicative and subject to updates as technology evolves.

Learn from IIT Bombay faculty

Learn from leading IIT Bombay faculty who blends rigorous AI and strategy research with practical delivery.

Prof. Abhiram Ranade

Department of Computer Science and Engineering, IIT Bombay

Yale Ph.D. and IIT Bombay CSE faculty

Research Interest: Algorithms and combinatorial optimisation

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Prof. Amitabha Sanyal

Department of Computer Science and Engineering, IIT Bombay

Ph.D from IIT Kanpur

Research: Functional programming, compilers and programming languages

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Prof. Kameswari Chebrolu

Department of Computer Science and Engineering, IIT Bombay

Ph.D. from UC San Diego; CSE faculty at IIT Bombay

Research Interest: Web technologies, AI & cloud

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Prof. Vinay J. Ribeiro

Department of Computer Science and Engineering, IIT Bombay

Rice University Ph.D.; IIT Bombay CSE faculty

Research Interest: Blockchain, intrusion detection, IoT

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Prof. Sharat Chandran

Department of Computer Science and Engineering, IIT Bombay

Ph.D. from University of Maryland

Research Interest: Computer vision, affective computing and AI

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PROF. SHIVARAM KALYANAKRISHNAN

Department of Computer Science and Engineering, IIT Bombay

Ph.D. from UT Austin

Research: Reinforcement learning and intelligent, learning agents

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Dr. Arpit Agarwal

Assistant Professor, IIT Bombay

Ph.D. from the University of Pennsylvania; PostDoc researcher at Meta.

Research in human–AI interaction, RL, and responsible AI design.

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Prof. Harshad Khadilkar

Ph.D. | Massachusetts Institute of Technology

Bachelor's in Aerospace Engineering from IIT Bombay and a PhD from MIT

His research covers meta-RL sequential decision-making

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Prof. S. Sudarshan

Department of Computer Science and Engineering, IIT Bombay

Ph.D. from University of Wisconsin-Madison

Research: Query processing and optimisation; testing database queries

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Hear from our learners

Hear what our learners have to say about their experience of the program support, faculty & mentors

Watch story

"This program has contributed greatly to my professional growth."

Praneeth Thogarchetti

Site Reliability Engineer , AST SpaceMobile
Watch story

"This program helped me gain deeper technical knowledge and upskill."

Shourya Bhosle

Software Engineer , Avalara

ePGD Fees

Benefits of learning with us

Earn up to 36 Credits from IIT Bombay, which can be saved in the Academic Bank of Credits (ABC)
In-person graduation at IIT Bombay campus and IIT Bombay Alumni status
Designed and delivered by IIT Bombay faculty
Personalised assistance with a dedicated Programme Manager

Take the next step

00 : 00 : 00

Apply to the ePGD now or schedule a call with our advisors

Get started with your application

Application Closes: 10th Nov 2026

Talk to our advisor for further course details

Selection Process

Registrations close once the required number of participants enroll. Apply early to secure your spot.

Application

Interested candidates can apply for the e-Postgraduate Diploma by filling out a simple online application form.
Online Test & Screening Call

Applicants must take an online test to assess their foundational knowledge and suitability for the ePGD. After passing the online test, applicants will go through a mandatory screening call with the Registration Oce.
Offer of Registration

The selected candidates will receive an offer letter to join the ePGD. They will need to pay the registration fee to secure their seat and complete the registration.

Eligibility Criteria

(B.E. / B.Tech / BS (4 years) / M.Sc.) or higher degree in Computer Science/Engineering, Information Technology, Artificial Intelligence, Data Sciences, Mathematics and Computing or equivalent (*) disciplines.
OR (BS (4 years) / B.E. / B.Tech) or higher degree in any engineering discipline AND any one of the following: • Qualifying GATE score in Computer Science or Data Science • Two years relevant work experience in Computer Science, Artificial Intelligence, or Data Sciences • A minor in Computer Science, Information Technology, AI and ML, Data Science or equivalent (*) in programmes which offer such minors
OR MCA (with undergraduate degree BCA or B.Sc. with Mathematics as a subject)

Limited seats available

Learn from IIT Bombay faculty

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FAQ

ePGD Details

Faculty, Curriculum & Projects

Eligibility, Registration, and Fees

Career-Related Queries

ePGD Details

Is this ePGD suitable for working professionals?

Yes. The ePGD is designed for working professionals, software developers, IT professionals,
data scientists, and fresh graduates. The flexible online delivery combines live sessions with
asynchronous learning to support continued employment while studying.

What makes the IIT Bombay ePGD in Computer Science and AI different from short AI courses or bootcamps?

Unlike short AI courses or bootcamps, this ePGD focuses on postgraduate-level technical
depth rather than introductory or tool-based learning. The curriculum mirrors the academic rigor
of IIT Bombay's on-campus standards and emphasizes advanced programming, computing
systems, mathematics, Machine Learning, and hands-on learning through a structured
12-month curriculum.

What is the duration of this ePGD in Computer Science and AI?

The duration of e-Postgraduate Diploma in Computer Science and AI is 12 months, comprising
six courses and 36 IIT Bombay credits.

Will I receive an IIT Bombay credential after completing the ePGD?

Yes. Upon successfully completing all academic requirements and 36 credits, learners receive
an e-Postgraduate Diploma from IIT Bombay. They also become eligible for IIT Bombay
Alumni status and can attend the in-person graduation ceremony on the IIT Bombay campus.
Faculty, Curriculum & Projects

Faculty, Curriculum & Projects

Who teaches the IIT Bombay ePGD in Computer Science and Artificial Intelligence?

The ePGD is designed and delivered by faculty from the Department of Computer Science and
Engineering (CSE), IIT Bombay. The faculty includes experts in Artificial Intelligence, Machine
Learning, reinforcement learning, computer vision, databases, cybersecurity, programming
languages, and distributed systems.

Does the ePGD include Generative AI and AI agents?

Yes. The curriculum includes dedicated courses on Generative AI: From Foundations to
Autonomous Agents and Natural Language Processing and Generative AI, covering Large
Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, tool calling,
orchestration, and evaluation.

Which programming languages and AI tools are covered?

Depending on the courses selected, learners work with technologies such as Python, FastAPI,
LangChain, LangGraph, Docker, JavaScript, Rust, NumPy, SciPy, Big Data platforms,
Ethereum, OWASP, OpenSSL, WireShark, and Model Context Protocol (MCP).

Does the ePGD include hands-on projects?

Yes. The curriculum includes hands-on assignments, practical implementations, and course
projects. For example, The Program Developer's Toolbox requires learners to complete a
course project demonstrating the concepts covered.

How is the curriculum structured?

The ePGD requires learners to complete 36 IIT Bombay credits by successfully finishing six
courses. Candidates must complete at least two courses from both the Artificial Intelligence and
Machine Learning basket and the Computer Science basket.

Eligibility, Registration, and Fees

Who is eligible for the IIT Bombay ePGD in Computer Science and Artificial Intelligence?

The ePGD is open to candidates with a B.E./B.Tech, BS (4 years), or M.Sc. in Computer
Science, Information Technology, Artificial Intelligence, Data Science, Mathematics &
Computing, or equivalent disciplines. MCA graduates with a BCA or B.Sc. with Mathematics
are also eligible.

Is a GATE score required for the IIT Bombay ePGD?

No. A GATE score is not mandatory for registration. Eligible candidates can apply without
GATE if they satisfy the prescribed academic or work experience requirements.

Can candidates from other engineering disciplines apply for the IIT Bombay ePGD?

Yes. Candidates with a B.E./B.Tech or BS (4 years) in any engineering discipline can apply if
they have any one of the following:
● A qualifying GATE score in Computer Science or Data Science
● Two years of relevant work experience in Computer Science, AI, or Data Science
● A minor in Computer Science, IT, AI/ML, Data Science, or an equivalent discipline
The final decision on the equivalency of qualifications rests with the IIT Bombay CSE
Department.

What is the registration process for the IIT Bombay ePGD?

The registration process includes three stages: submitting an online application, completing an
online test and screening call, and receiving an offer of registration upon selection.

What is the fee for the IIT Bombay e-Postgraduate Diploma?

The total fee for the ePGD is ₹6,00,000 + GST. The fee is paid in stages, including a registration
fee followed by course-wise payments.

Do I receive academic credits after completing the ePGD?

Yes. Learners earn 36 IIT Bombay academic credits, which can be saved in the Academic
Bank of Credits (ABC) after successful completion of the ePGD.

Career-Related Queries

How will this ePGD help me prepare for AI and Machine Learning roles?

This ePGD helps you build a strong foundation in Artificial Intelligence and Machine Learning
through postgraduate-level coursework in foundational mathematics, computer vision,
reinforcement learning, Generative AI, natural language processing, and autonomous AI agents.
You also strengthen your expertise in advanced programming and computing systems,
preparing you for AI-focused technical roles.

Can this ePGD help experienced IT professionals without a postgraduate degree?

Yes. This ePGD is designed for IT professionals and experienced technology professionals who
want to formalize their expertise with an IIT Bombay postgraduate qualification. It enables
learners to deepen their understanding of advanced programming, computing systems, AI, and
Machine Learning through a rigorous, concept-based curriculum.

How can I benefit from campus immersion and networking opportunities?

The ePGD combines online learning with campus immersion, allowing you to meet IIT Bombay
CSE faculty, experience the IIT Bombay campus during visits, attend an in-person graduation
ceremony, earn IIT Bombay Alumni status, participate in peer-to-peer learning, and access the
IIT Bombay Lateral Hiring Group for professional networking.

How can IIT Bombay Alumni status support my professional growth?

Upon successfully completing the ePGD, you'll receive IIT Bombay Alumni status, allowing
you to become part of the IIT Bombay alumni community. In addition to expanding your
professional network through peer learning, you'll also gain access to IIT Bombay's Lateral
Hiring Group, helping you connect with career opportunities and fellow professionals while
strengthening your industry presence.

e-Postgraduate Diploma (ePGD) in Computer Science and Artificial Intelligence (CS & AI)