Offered by the Technocraft Centre for Applied AI, IIT Bombay
Certificate in Generative AI
Application closes on
5th Jun 2026
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Certificate in Generative AI
Application closes 5th Jun 2026
Key Course Outcomes
Master practical Generative AI skills
Become a hands-on GenAI builder with prompts, RAG, tuning, agents, and LLMOps.
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Design reliable LLM features and workflows
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Adapt foundation models to enterprise data using Retrieval-Augmented Generation (RAG)
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Build agentic applications that call tools, use memory, and follow workflows for business use-cases
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Deploy and operate Generative AI systems using LLMOps practices
Earn a Certificate of Completion from IIT Bombay
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#28
QS Rankings in Engineering & Technology, 2025
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#3
NIRF India Rankings 2024
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#1
NIRF India Innovation Rankings, 2024
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#3
NIRF India Engineering Rankings, 2024
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#30
QS Rankings in Data Science and AI, 2024
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#63
QS Rankings in Electrical & Electronics, 2024
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#2 in India
QS World University Rankings, 2026
Key Course Highlights
Why choose the Certificate in Generative AI
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IIT Bombay Faculty-led
Learn from experienced IIT Bombay faculty through live sessions, hand-on work, and structured feedback
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Real-world projects
Curriculum and projects focussed on building, adapting, and operating real GenAI features.
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Weekly Live Sessions
Interactive classes, query resolution and practice to keep you on track
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Agentic & RAG tool stack
Gain mastery in LangChain, LangGraph, and other cutting-edge GenAI tools
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Operational focus with LLMOps
Package, deploy, and monitor GenAI apps with CI/CD basics; and security, privacy and governance controls
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Dedicated learner support
Receive personalized assistance from a dedicated programme manager throughout your learning journey
Skills you will learn
Prompt engineering
Retrieval-Augmented Generation (RAG)
LLMOps
Agentic AI
LLM evaluation & guardrails
Lightweight fine-tuning
Transformer & LLM fundamentals
Python for Generative AI
Embeddings & vector databases
Classification and summarization
Model selection
Data preparation & labeling for LLMs
CI/CD for LLM applications
Prompt engineering
Retrieval-Augmented Generation (RAG)
LLMOps
Agentic AI
LLM evaluation & guardrails
Lightweight fine-tuning
Transformer & LLM fundamentals
Python for Generative AI
Embeddings & vector databases
Classification and summarization
Model selection
Data preparation & labeling for LLMs
CI/CD for LLM applications
view more
- Overview
- Learning Path
- Curriculum
- Tools
- Certificate
- Faculty
- Fees
- FAQ
This course is ideal for
This hands-on GenAI certificate is ideal for builders and tech leads seeking practical skills.
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Software and Technology Professionals
who want to add GenAI features to products, stay current with new tools, and unlock career opportunities in software and AI
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Data Scientists and Data Analysts
looking to move beyond prediction into text, image, and code generation to automate reports and extract more value from data
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Tech Consultants and Managers
seeking to evaluate GenAI options, lead cross-functional builds, manage risks, and present ROI cases to clients and stakeholders
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Product Managers and Product Owners
aiming to embed Generative AI into product features and workflows to boost user value and accelerate delivery
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Business Analysts and Consultants
who want to use Generative AI to surface deeper insights and streamline decision-making
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STEM/Engineering Graduates
Hands-on training that positions them at the forefront of an emerging, high-growth industry
Unique Learning Journey
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Weekly live sessions
Interactive classes for concept clarity, hands-on and Q&A with IIT Bombay faculty.
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Peer-to-Peer Learning
Learn with a cohort - discuss and share ideas in class and in discussion forums.
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Industry-Relevant Curriculum
Work on projects - apply concepts & tools to real use cases
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Get personalized assistance
Our dedicated programme managers will support you whenever you need
Comprehensive Curriculum
Designed by IIT Bombay faculty, this hands-on certificate builds practical Generative-AI skills such as prompting & evaluation, RAG, PEFT/LoRA, agentic systems, and LLMOps. Learners are equipped to design, adapt, deploy, and monitor reliable LLM applications.
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5 modules
LLM-first approach
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3–4 hrs/week
live teaching + practice
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12+ AI tools
Key AI & Agentic AI tools
Module 1: Foundations of Generative AI
This module introduces the conceptual building blocks for working with AI systems. Learners set up Python, familiarise themselves with core machine learning concepts, and understand how data flows through modern pipelines. Short primers on deep learning and NLP (embeddings) establish a shared vocabulary. The module also covers how modern models represent language, why embeddings matter, and how these representations power downstream tasks. By the end, learners can explain how meaning is encoded numerically and why this foundation is essential for LLM applications. Topics Covered: - Python for Generative AI - Advanced Python for Generative AI Applications - Introduction to Machine Learning - Introduction to Deep Learning - NLU and NLP: Word Embeddings
Module 2: Natural Language Processing with Generative AI
This module moves from fundamentals to the core mechanics of modern language models. Learners unpack attention mechanisms and transformer architecture before applying these concepts to practical prompting. The module demonstrates how LLMs handle both classification and labelling tasks, as well as open-ended text generation and summarisation, highlighting what changes, what to measure, and how to steer outputs eectively. Topics Covered: - Attention Mechanism and Transformers - Large Language Models and Prompt Engineering - LLMs for Classification and Text Labelling - LLMs for Text Generation and Summarisation
Module 3: Multimodal AI
In this module, learners will explore the evolution from CNNs and VAEs/GANs to diffusion-based foundation models, and how text pairs with images/audio for real tasks. They will learn multimodal prompting patterns and how to build and evaluate simple multimodal apps. Topics Covered: - Evolution of Multimodal Models - from CNNs to VAEs, GANs, Transformers, and Modern Diffusion-based Foundation Models - Applications: Vision-Language Models, Audio-Visual Reasoning, Robotics, etc. - Multimodal Prompting & Interaction - Building & Evaluating Multimodal Applications
Module 4: Designing LLM Workflows and Applications
This module focusses on designing production-ready workflows that ground models in enterprise data. Topics include Retrieval-Augmented Generation (RAG), application blueprints, and selective fine-tuning for accuracy and tone. The module concludes with clear decision-making guides on when to use RAG, when to fine-tune, and how to evaluate performance. Topics Covered: - Retrieval-Augmented Generation - Advanced RAG: Optimisation and Multi-Modal RAG - Designing and Building LLM Workflows - Fine-Tuning Custom LLMs
Module 5: Designing and Building AI Agents
This module translates single-prompt prototypes into multi-step systems that plan, use tools, and manage tasks collaboratively. Agent capabilities and patterns are introduced first, followed by building single-agent flows with memory and tool integration. The module ends with multi-agent collaboration and principled evaluation to support trust in agent behaviour. Topics Covered: - Introduction to AI Agents - Building Single-Agent Systems and Agentic RAG - Multi-Agent Collaboration and Agent Evaluation
Module 6: Deploying, Securing, and Managing LLM Applications
The final module addresses deploying applications responsibly and ensuring their ongoing reliability. The concepts covered include CI/CD for LLM apps, deployment patterns, and live monitoring for latency, cost, drift, and quality. The module also covers vulnerabilities, data governance, and operational controls so that releases are secure, compliant, and observable from day one. Topics Covered: - CI/CD and DevOps for LLM Applications - LLMOps: Generative AI Application Deployment - LLMOps: LLM Application Performance Monitoring - Mitigating LLM Vulnerabilities and Ensuring Data Governance
Languages and Tools covered
Build hands-on expertise with tools and frameworks used across Generative AI systems
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Python
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PyTorch
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Keras
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ChatGPT
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Claude Code
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Gemini
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Hugging Face
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NumPy
Earn a Certificate of Completion from IIT Bombay
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Designed by IITB Faculty
The curriculum is designed and delivered by IIT Bombay faculty
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Gain Mastery in GenAI
Gain mastery in LangChain, LangGraph, and other cutting-edge GenAI tools
* Image for illustration only. Certificate subject to change.
Meet your faculty
Learn from IIT Bombay faculty with deep expertise in GenAI
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Manjesh K. Hanawal
Associate Professor, IEOR, IIT Bombay
Research in communication networks, machine learning, and cybersecurity
Awards from DST/SERB & IITB; active contributor to 3GPP SA1/SA3
Know More
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P Balamurugan
Associate Professor, IEOR, IIT Bombay
Interests span probabilistic, statistical, and learning-theoretic methods
Designs of efficient algorithms rooted in optimization
Know More
LinkedIn Profile
University LinkCourse Fees
The course fee is ₹ 1,80,000
Invest in your career
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Design reliable LLM features and workflows
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Adapt foundation models to enterprise data using Retrieval-Augmented Generation (RAG)
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Build agentic applications that call tools, use memory, and follow workflows for business use-cases
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Deploy and operate Generative AI systems using LLMOps practices
Selection Process
Registrations close once the required number of participants enroll. Apply early to secure your spot.
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Application
Interested candidates can apply by filling out a simple online application form.
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Interview Process
Go through a mandatory screening call with the registration office.
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Offer of Registration
Selected candidates will get an offer letter and must pay the fee to confirm registration.
Eligibility Criteria
- Applicants must hold a Bachelor’s degree (any discipline) with: a minimum aggregate of 50% (or equivalent CGPA) (or) 5+ years of work experience.
Frequently Asked Questions
What is unique about Certificate in Generative AI by IIT Bombay?
The Certificate in Generative AI by IIT Bombay stands out from other Generative AI courses in several ways:
Expert-led learning: Designed and delivered by IIT Bombay faculty, ensuring a rigorous and high-quality curriculum.
Practical industry focus: Includes hands-on projects using advanced Generative AI tools to build real-world applications.
Enterprise-ready approach: Emphasizes adapting Large Language Models (LLMs) to enterprise data through Retrieval-Augmented Generation (RAG) and creating agentic applications.
Interactive learning experience: Participants benefit from weekly live sessions, peer learning, networking opportunities, and dedicated Program Manager support.
Recognized certification: Learners who complete the course receive a Certificate of Completion from IIT Bombay, adding credibility and enhancing career growth.
Responsible AI foundation: The course follows clear standards for security, privacy, and evaluation, preparing learners to build dependable and ethical AI systems.
Holistic skill development: It combines technical applications with leadership, ethics, and AI strategy to prepare learners for real-world business challenges.
What is the format and structure of this Certificate in Generative AI?
The Certificate in Generative AI is a 5-month, online, hands-on certificate.
- The curriculum takes a practical, LLM-first approach across 6 modules.
- Learners will start with the essentials of how AI works, then learn the basics of Large Language Models (LLMs)
- Followed by how to write effective prompts and how to judge the quality of results.
- Learners will also adapt models according to their own data using simple retrieval and light tuning.
- Explore how to build helpful “copilot” tools and multi-step workflows, and finally learn how to launch, secure, and maintain what they have built.
- This learning is reinforced through hands-on projects and practice.
Who is this for?
- Software and Technology Professionals who want to add Generative AI features to products, stay current with evolving tools, and unlock new career opportunities at the intersection of software and AI.
- Data Scientists and Data Analysts looking to move beyond prediction into text, image, and code generation to automate reporting and extract more value from existing data.
- Technology Consultants and Technical Managers seeking to evaluate Generative AI options, lead cross-functional builds, manage risks, and present clear ROI cases to clients and stakeholders.
- Product Managers and Product Owners aiming to embed Generative AI into product features and workflows to boost user value and accelerate delivery.
- Business Analysts and Consultants who want to use Generative AI to surface deeper insights and streamline decision-making.
What are the learning outcomes of the Certificate in Generative AI?
The learning outcomes of the Certificate in Generative AI from IIT Bombay are:
- To design reliable workflows using Large Language Models (LLMs).
- Adapt foundation models to enterprise data with Retrieval-Augmented Generation (RAG).
- Build agentic applications that plan tasks, call tools and APIs, manage memory, and coordinate multi-step workflows for business use-cases.
- Deploy and operate Generative AI systems using LLMOps practices.
- Implement governance and security by embedding privacy controls.
Who teaches the Certificate in Generative AI?
Certificate in Generative AI is designed and delivered by the experienced faculty of IIT Bombay.
Do participants earn a certificate from IIT Bombay after completion?
Yes, participants who successfully complete the Certificate in Generative AI will earn a Certificate from IIT Bombay.
What is the curriculum structure of the Certificate in Generative AI ?
The curriculum takes a practical, LLM-first approach across six modules:
- Foundations of Generative AI
- Natural Language Processing with Generative AI
- Multimodal AI
- Designing LLM Workflows and Applications
- Designing and Building AI Agents
- Deploying, Securing, and Managing LLM Applications
It also includes sample projects such as
- Creating managed projects on open-source Large Language Model (LLM) platforms
- Content, image, and video generation using Generative AI
- Building full-stack applications with Generative AI features
- Developing pipelines for custom content generation using AI
- Deploying private GPTs on personal laptops for private databases
Note: Curriculum review and changes are under the purview of IIT Bombay and will be undertaken from time to time to ensure the curriculum remains aligned with industry requirements.
Who are the faculty members for the Certificate in Generative AI?
The Certificate in Generative AI by IIT Bombay is designed and delivered by highly qualified faculty members who bring a strong blend of academic excellence and industry experience. The faculty members are known for their research contributions and leadership in AI education, providing learners with deep theoretical knowledge as well as real-world applications and case studies. This combination of cutting-edge research, industry insights, and hands-on teaching makes the educational experience comprehensive and impactful for participants.
Prof. Manjesh K. Hanawal
Associate Professor, Indian Institute of Technology, Bombay
Prof. P. Balamurugan
Associate Professor, Indian Institute of Technology, Bombay
Is the curriculum industry-focused?
Yes, it has an industry-relevant curriculum with real-world use cases.
Are hands-on projects included in the curriculum?
Yes, the curriculum features hands-on training and projects using industry-relevant tools such as Python, PyTorch, Keras, TensorFlow, NumPy, ChatGPT, Claude, Gemini, Hugging Face, Ollama, LangChain, and LangGraph.
Is there dedicated support for learners?
Yes, learners receive personalized assistance from a dedicated Programme Manager.
What are the eligibility criteria for the Certificate in Generative AI?
Applicants must hold a Bachelor’s degree (any discipline) with a minimum aggregate of 50% (or equivalent CGPA).
What is the selection process?
The selection process for eligible applicants is as follows:
Step 1: Application
Interested candidates can apply by filling out a simple online application form.
Step 2: Interview Process
Go through a mandatory screening call with the registration office
Step 3: Offer of Registration
Selected candidates will receive an offer letter. They must pay the registration fee to confirm their seat and complete the registration.
What is the total fee for the Certificate in Generative AI?
For the most up-to-date information on the total fee, please refer to the official page here.
Is there any financial assistance provided to candidates?
Financial assistance options are available through partners such as Propelld, Zest, Eduvanz, and Liquiloans.
*Conditions apply. The Financial Assistance options are available through Great Learning.
Please reach out to the admissions once at 080 4680 1927 for more details.
How will a Certificate in Generative AI help me progress in my career?
Certificate in Generative AI will position learners to build and operate dependable Generative AI features grounded with RAG, using agents, with clear standards for security, privacy, and evaluation.
Are there any networking opportunities?
Yes, there are peer-to-peer learning and networking opportunities.
What careers can I pursue after completing an online Generative AI course?
After completing an online Generative AI course, you can pursue a variety of careers across technology, business, and creative industries. Some prominent career paths include:
- Generative AI Engineer or Large Language Model (LLM) Engineer, responsible for designing, developing, and deploying generative AI models for tasks like content creation, automation, and personalization.
- Machine Learning Engineer, focusing on building and optimizing machine learning algorithms and integrating generative models into products.
- Data Scientist or Data Analyst, specializing in training, evaluating, and tuning models using large datasets for innovative AI applications.
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AI Researcher or Scientist, working on advancing generative model architectures and experimenting with new AI techniques.
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Product Manager or Solutions Architect for AI-driven products and features, guiding enterprise adoption and implementation of AI solutions.
- Creative AI Developer, designing applications for content, image, video, music, and digital media generation.
- AI Consultant, providing expertise on how to integrate generative AI into business operations, marketing, and customer experience
Application Closes
5th Jun 2026
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