Generative AI work now goes beyond prompt writing. Developers are adding LLM features to products, analysts are working with unstructured data, and technology teams need skills in RAG, agents, evaluation, security, and deployment.
For professionals comparing courses, the syllabus matters more than the label. These five programs approach GenAI through application engineering, enterprise automation, model training, and mathematical foundations.
Why Consider a Generative AI Course for Technical Roles?
- Build beyond prompting: Learn RAG, fine-tuning, agents, and evaluation.
- Apply AI to existing roles: Connect GenAI to software, analytics, and technical work.
- Get practical exposure: Use projects and labs to apply concepts.
- Choose the right depth: Compare application, automation, and model-focused learning.
Quick Comparison of the Programs
Program | Fees | Eligibility | Duration | Credentials |
IIT Bombay Certificate in Generative AI | ₹1,80,000 + GST | Bachelor's with 50% or equivalent CGPA, or 5+ years' work experience | 5 months | Certificate of Completion from IIT Bombay |
IIT Delhi Certificate Program in Generative AI | ₹1,95,000 + 18% GST | STEM graduate/postgraduate with programming exposure | 6 months | Certificate from CEP, IIT Delhi |
BITS Pilani Digital Professional Certificate in Generative & Agentic AI | ₹96,000 + GST | Bachelor's, Class 12 Mathematics, 2+ years' relevant experience, Python/AWS foundations | ~30 weeks | Professional Certificate from BITS Pilani Digital |
IIT Madras AI Agents & Gen AI for Enterprise Transformation | ₹80,000 + 18% GST | Any UG/PG degree holder | 3 months | Joint certificate from CODE IIT Madras and FedEx SMART Center |
IISc Generative AI - Principles and Applications | ₹18,054 incl. GST | Undergraduate degree and basic Python | May-July 2026 | IISc Grading Certificate, 3:0 credits |
1. IIT Bombay Certificate in Generative AI
IIT Bombay's generative AI course is built for professionals who want to design and deploy GenAI applications, moving from Python and transformers to RAG, fine-tuning, agents, evaluation, security, and LLMOps.- Curriculum & Focus: Prompt engineering, embeddings, RAG, PEFT/LoRA, agentic AI, guardrails, CI/CD, and LLMOps.
- Key Highlights: Weekly IIT Bombay faculty sessions, guided labs, projects, learner support, and optional campus immersion.
- Why Choose This Course? It connects model adaptation with monitoring, governance, vulnerabilities, and agent evaluation.
- Eligibility: Bachelor's degree with 50% or equivalent CGPA, or 5+ years of work experience.
- Fee Structure: ₹1,80,000 + GST.
- Outcomes: Build RAG workflows, tool-using agents, and deployable GenAI systems.
2. IIT Delhi Certificate Program in Generative AI
IIT Delhi combines technical foundations with applied project work. Its curriculum is intended for STEM graduates and professionals with programming experience who want a deeper understanding of how generative models are built and tuned.- Curriculum & Focus: Mathematics, neural networks, transformers, model tuning, reinforcement learning, RLHF, multimodal AI, and responsible AI.
- Key Highlights: Online technical modules, applied projects, and a final capstone.
- Why Choose This Course? Projects cover neural networks, LLM prompting, reward models, and a final capstone.
- Eligibility: STEM graduates or postgraduates with programming exposure. Prior AI/ML experience is not required.
- Fee Structure: ₹1,95,000 + 18% GST.
- Outcomes: Strengthen model architecture, training, tuning, and applied GenAI skills.
3. BITS Pilani Digital Professional Certificate in Generative & Agentic AI
BITS Pilani Digital connects LLMs with retrieval, agents, workflows, evaluation, and deployment. The program is geared toward technology professionals who want to move from experimenting with AI tools to building complete AI systems.- Curriculum & Focus: LLM application engineering, RAG, evaluation harnesses, agent orchestration, workflow automation, and deployment.
- Key Highlights: About 30 weeks, labs, projects, weekly instructor interaction, TA support, and an enterprise capstone.
- Why Choose This Course? RAG, agents, workflows, testing, and deployment are taught as parts of one AI system.
- Eligibility: Bachelor's degree, Class 12 Mathematics, two years of relevant experience, and Python/AWS foundations. A bridge pathway is available.
- Fee Structure: ₹96,000 + GST.
- Outcomes: Build RAG applications, agent workflows, evaluation frameworks, and deployable AI services.
4. IIT Madras AI Agents & Gen AI for Enterprise Transformation
This CODE IIT Madras and FedEx SMART Center program connects GenAI with enterprise decision workflows. Its emphasis is less on standalone model development and more on using AI to support analytics, decisions, and automated business processes.- Curriculum & Focus: Conversational AI, agents, optimization, simulation, demand intelligence, and automation.
- Key Highlights: Ten modules using tools such as LangGraph, CrewAI, n8n, PandasAI, DSPy, Streamlit, and Gradio.
- Why Choose This Course? It focuses on applying GenAI to enterprise data and operational decisions.
- Eligibility: Any UG or PG degree holder.
- Fee Structure: ₹80,000 + 18% GST for the published 2026 batch.
- Outcomes: Build AI-assisted workflows combining analytics, agents, and business actions.
5. IISc Generative AI - Principles and Applications
IISc takes a mathematical approach, pairing theory with PyTorch implementation. This makes the course particularly relevant to learners who want to understand the mechanics behind generative models rather than concentrate mainly on application development.- Curriculum & Focus: GANs, VAEs, diffusion models, LLMs, sampling, quantization, PPO, DPO, and alignment.
- Key Highlights: Synchronous classes, assignments, 3:0 credits, and IISc faculty instruction.
- Why Choose This Course? It suits learners who want to understand the mechanics of generative models rather than just their application APIs.
- Eligibility: Undergraduate degree and basic Python skills.
- Fee Structure: ₹18,054 including GST for the May-July 2026 offering.
- Outcomes: Build theoretical and implementation knowledge across major generative-model families.
Important Things to Remember Before Enrolling
Compare coding, RAG, agents, tuning, evaluation, and deployment, and project depth, rather than relying solely on duration or institution name. A model-focused course develops different skills from an enterprise application program.Conclusion
Developers may prefer application engineering, RAG, agents, and deployment. Analysts can look for links between GenAI, data, and decision systems, while AI professionals may value model training, tuning, and mathematical foundations.The right choice among generative ai courses depends on the technical layer you want to strengthen. Compare the curriculum, prerequisites, projects, credentials, and time commitment with the work you want to perform after completion.
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