PROJECT 01
Question-answering assistant over course documents
Example hands-on exercise
GENERATIVE AI
Generative AI.
Explore large language models, prompt engineering, and building applications powered by generative AI.
LLMsPromptingRAG
Bangalore, Karnataka, India · Request fees, duration & batch timings
01 / LEARNCore concepts
Understand the foundations
02 / PRACTICEApplied exercises
Work with practical examples
03 / BUILDProject ideas
Explore hands-on workflows
PROGRAM OVERVIEW
What you could learn.
A suggested progression of topics for Generative AI. The final lesson plan can be confirmed with the institute before enrollment.
01Foundations of LLMs and generative models
02Prompt engineering and structured outputs
03Embeddings, vector search, and retrieval
04Retrieval-augmented generation (RAG)
05Model evaluation, guardrails, and responsible AI
06Building an LLM-enabled application
Recommended starting point
Python basics and familiarity with APIs recommended.
PRACTICAL LEARNING
Learning outcomes.
Explore the capabilities this course aims to develop.
Prototype applications that use LLM APIs
Build a basic document retrieval workflow
Evaluate outputs for quality and safety
PORTFOLIO PRACTICE
Project ideas.
Examples of practice projects that could support the learning journey.
PROJECT 02
Information summarizer with source citations
Example hands-on exercise
LET'S CONNECT
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