Udemy — Agentic AI Bootcamp: Build RAG AI Agents with Generative AI 2026-4

Description

Develop document-based AI assistants by combining retrieval-augmented generation with agent workflows. The course follows document processing, embeddings, vector storage and retrieval before connecting the selected information to a language model. LangChain and FAISS support the implementation, while LLaMA models through Ollama introduce a local-model approach.

Agent lessons address tools, context, prompt design and the orchestration of tasks with more than one step. The projects include Streamlit chat interfaces, resume-analysis tools and research-assistant examples. Learners also examine response evaluation and the integration of external data or tools, linking the retrieval pipeline with application behaviour beyond a single chatbot reply.

Intended audience: Learners seeking project-based introductions to RAG and AI agents. Developers exploring document assistants and AI workflow applications.

What you will learn

• Build a document-retrieval pipeline using embeddings, LangChain and FAISS.
• Connect an application to a local LLaMA model through Ollama.
• Design agent workflows that combine context, tools and multiple task steps.
• Create Streamlit interfaces for document assistants and related example projects.

Course specifications

Publisher

Udemy

Instructors

Metla Sudha Sekhar

Language

English

Level

Beginner to Advanced

Duration

7 hours and 22 minutes

Lecture count

85

Subtitle

None

Quality

1080p

Edition

2026-4

Course topics

View course topics

Prerequisites

• Basic familiarity with computers and software.
• A Windows or macOS computer with internet access.
• Willingness to work through practical AI development exercises.

Introduction video

Download resources

Choose one edition and keep its parts together. Alternate providers are available when listed.

Size

3.1 GB

Leave a Reply

Signed-in member comments appear immediately.

More to explore