- What This Course Is About
- Who Should Enroll
- Course Outline
- Prerequsites
- How To Join The Zoomcamp
- Meet The Instructor
- Quick Links & Resources
- You will master Reflection, a design pattern that powers agentic AI systems
- Software Engineers: Developers who want to apply AI techniques to build autonomous systems that handle multi-step workflows.
- Professionals: Professionals with intermediate-level Python programming skills to be able to follow along with the implementations.
- Practitioners: Professionals with a basic understanding of large language models and APIs who want to deepen their practical skills.
- ✅ 1.Explore what defines an agentic AI system and why leaders often lack a shared understanding of agents.
- ✅ 2.Develop a consistent framework for evaluating opportunities and risks in a rapidly evolving agentic AI landscape.
- ✅ 1.Learn how agentic AI enables a shift from automation to transformation and reshapes how products, services, and workflows are designed and experienced.
- ✅ 2.Master Reflection design pattern where AI critiques its own work annd iterates to improve quality
- Functional knowledge fo Python, data structures and LLMs
- Comfort with command line basics
Agentic AI Zoomcamp 2026 - Free Course on a comprehensive coverage of AI agents & RAG
Go from LLM basics to a production-ready AI assistant in 10 weeks
Learn Retrieval-Augmented Generation, vector search, embeddings, AI agents, function calling, evaluation, monitoring, hybrid search, reranking, and more - all in a free, open-source, hands-on course by Aivarta Consulting.
Table of Contents
About Agentic AI Zoomcamp
Agentic AI represents a new way of building software that leverages LLMs to complete some or all of the steps in complex tasks.
Instead of generating single responses to prompts, agentic workflows enable AI to plan multi-step processes, execute them iteratively, and improve outputs
through reflection and tool use. This course teaches you to build these sophisticated AI systems from the ground up.
👥 Who Should Join?
This course is for people who learn by doing. After completing it, you'll have a working codebase and the hands-on experience to build your own LLM-powered applications.
Course Outline
| Module | Description |
|---|---|
| Module 1: Foundations of Agentic AI and LLM Capabilities. | |
| Module 2: Designing For Agentic AI. | |
| Module 3: Organizational and Agent Architecture | Examine the organizational impact of deploying agentic AI within firms and across value chains |
| Module 4: Measuring the Value of Agentic AI | Develop the value proposition and measurement strategies to quantify the business impact of agentic AI systems. |
| Module 5: AI Governance and Security | Understand how to ensure agentic AI systems operate within legal, regulatory, and security boundaries while building trust and mitigating risk. |
Prerequisites
You'll need:
Technical setup: For machine learning modules, you only need a laptop with an internet connection. For deep learning sections, we'll use cloud resources for more intensive computations.
How to Join
You can join ML Zoomcamp either by following a live cohort or learning at your own pace.
All materials are freely available in this repository. Each module has its own folder directory. Lectures are pre-recorded and available in this YouTube playlist.
Additional Resources
ResourcesSyllabus Overview
The course consists of structured modules, hands-on workshops, and a final project to reinforce your learning. The topics are curated based on key responsibilities within the data engineering capability centre.
