AI development tools have moved into everyday engineering work. Chat applications like ChatGPT and Claude, coding assistants like GitHub Copilot and Cursor, project bootstrappers like Bolt and Lovable, agents, and automation platforms like n8n have shifted the way we code and automate our workflows. The ecosystem is broad, and it’s not always clear which tools to adopt or how to use them reliably in real projects.
AI Dev Tools Zoomcamp is a free, project-based course that helps you build a practical toolkit for this stack. Over six modules, you’ll explore vibe coding and the AI tool landscape, ship a simple end-to-end project with React and FastAPI, extend assistants with the Model Context Protocol (MCP), build your own Django coding agent, apply AI to testing and DevOps, and automate workflows with n8n.
By the end, you’ll have hands-on experience applying AI to everyday engineering tasks, plus a small portfolio and a certificate that shows how you work with modern AI dev tools.
Table of Contents
- Who the Course Is For
- Course Curriculum
- How AI Dev Tools Zoomcamp Works
- What is the DataTalks.Club Community?
- How to Join AI Dev Tools Zoomcamp
- Frequently Asked Questions
Who the Course Is For
AI Dev Tools Zoomcamp is designed for people who want to work confidently with today’s AI development stack. It’s a good fit if you want to understand how coding assistants, agents, project generators, and automation tools actually fit into real engineering work.
This course is great for:
- Software developers who want to apply AI tools to everyday tasks like coding, debugging, testing, and project setup.
- Engineers looking to integrate assistants, agents, or workflow automation into their existing stack.
- Learners who prefer building rather than reading documentation, and who want guided, project-based practice with modern AI tooling.
You don’t need any previous experience with AI tools. A basic ability to program (Python, JavaScript, or similar) is enough to follow the materials and complete the projects.
Course Curriculum
What We’ll Cover
| Module | Topic | Focus | Tools You'll Use |
|---|---|---|---|
| 1 | Introduction to Vibe Coding / AI Tools Overview | AI-assisted development with Snake game example (React + JS) | ChatGPT, Claude, GitHub Copilot, Cursor, Bolt, Lovable |
| 2 | End-to-End Project (Snake) | Use a coding assistant for an end-to-end project: build Snake in React/TS, define API with OpenAPI, generate FastAPI server, add CI/CD, and deploy | React/TypeScript, OpenAPI, FastAPI, CI/CD tools |
| 3 | Model-Context Protocol | Enhance AI assistants with tools such as repo triage, PR summarization, scripted edits, and data queries | MCP servers (GitHub, filesystem, DB/SQL, HTTP/API, CI) |
| 4 | Build an AI Coding Agent (for Django) | Build your own coding agent that can scaffold and extend projects using Django templates and agent orchestration frameworks | Django, agent orchestration frameworks |
| 5 | AI for Testing, CI/CD & DevOps | AI-assisted PR reviews, automated test generation, release notes, changelog drafting, incident postmortems, and on-call copilots | CI/CD tools, LLM evaluation frameworks |
| 6 | Automation with Low-Code and No-Code AI (n8n) | Build automation workflows with composable AI tasks and ship lightweight assistants without maintaining servers | n8n, webhooks, connectors (email, Slack, GitHub, Jira, Notion, databases) |
Projects
Every module includes a project that applies the concepts in practice.
At the end of the course, you’ll build a complete application using AI tools throughout the entire development lifecycle.
- Start with AI-assisted project planning and architecture
- Use coding assistants for implementation (React/TypeScript frontend, FastAPI backend)
- Implement AI agents for code reviews and testing
- Set up automated CI/CD pipeline with AI-enhanced workflows
- Deploy and monitor using modern DevOps practices
- Document your AI-powered development journey
How AI Dev Tools Zoomcamp Works
GitHub Repository
All lessons, homework, and cohort updates live in the AI Dev Tools Zoomcamp GitHub repository. The structure mirrors our other Zoomcamps, so you can quickly find weekly folders, homework forms, and project guidelines.
Homework Assignments
Each module includes homework to practice what you’ve learned and track your progress. You can also compete on the course leaderboard, which adds a fun, competitive element.
Learning in Public
A unique feature of our Zoomcamps is our “learning in public” approach, inspired by Shawn Wang’s (@swyx) article on the topic. Instead of keeping your progress private, you’re encouraged to share assignments, reflections, and projects online.
Explaining what you’ve learned helps you understand it better, builds confidence, and creates visible proof of your skills. To encourage this, we award bonus points on the leaderboard for public posts about your work.
This practice has led to real opportunities for learners. For example, Pastor Soto, who joined ML Zoomcamp without a LinkedIn account, began posting his projects publicly. These posts not only accelerated his learning but also attracted attention from recruiters at Meta and DeepLearning.AI. Similarly, Daniel Egbo shared his progress on LinkedIn, which opened the door to collaborations on projects such as deploying models with Intel’s OpenVINO toolkit.
Certificate
To earn your free certificate, you need to complete a final project and review at least 3 other students’ projects. This ensures you demonstrate practical application of the concepts.
What is the DataTalks.Club Community?
DataTalks.Club has a supportive community of like-minded individuals in our Slack. It’s the perfect place to enhance your skills, deepen your knowledge, and connect with peers who share your passion. You’ll be supported by thousands of learners who exchange ideas, ask questions, and provide feedback, making it easier to stay accountable and find study partners. Many learners have turned these connections into collaborations and long-term professional relationships.
How to Join AI Dev Tools Zoomcamp
You can join AI Dev Tools Zoomcamp either by following a live cohort or learning at your own pace.
All materials are freely available in the AI Dev Tools Zoomcamp GitHub repository. Each module has its own folder, and cohort-specific homework and deadlines are in the cohorts directory. Lectures are pre-recorded and available in this YouTube playlist, so you can follow the live cadence or binge-watch at your own pace.
Option 1: Self-Paced Learning
You can start anytime and move at your own speed. You get full access to materials and community support on Slack.
You can complete homework assignments on the course platform and build a project for your portfolio, even outside a live cohort.
With self-paced learning, homework isn’t scored, your project isn’t peer-reviewed, and you can’t earn a certificate.
Option 2: Live Cohort
AI Dev Tools Zoomcamp runs once per year and typically starts in November.
When you join a live cohort, you get:
- Updated homework
- Automatic homework scoring and a leaderboard
- Project peer review
- Eligibility for a certificate after meeting all requirements
Even if you join after the official start date, you can still follow along. Note that some homework forms may already be closed. All active deadlines are listed on the course platform.
Frequently Asked Questions
The AI Dev Tools Zoomcamp is a free, community-driven program by DataTalks.Club that teaches practical applications of AI tools in software development through hands-on project work.
This 6-module course covers a comprehensive curriculum with all materials open and available anytime on GitHub. You’ll work with industry-standard tools including GitHub Copilot, Cursor, Model Context Protocol (MCP), n8n, and various AI coding assistants, and earn a certificate.
“Zoomcamp” is a term that originated from Alexey Grigorev, the founder of DataTalks.Club. It started with his book “ML Bookcamp.” When Alexey decided to create a video course based on the book, he called it “Machine Learning Zoomcamp” - a free, cohort-based course in video format. The name “zoomcamp” is a play on “bookcamp,” referring to the video format of the course. The Zoomcamp series has since expanded to include other free courses like the Data Engineering Zoomcamp, MLOps Zoomcamp, LLM Zoomcamp, and AI Dev Tools Zoomcamp, all following the same community-driven, open-source philosophy.
Yes! The AI Dev Tools Zoomcamp is completely free. There are no hidden costs, no tuition fees, and no paid tiers. All course materials, videos, homework assignments, and access to the Slack community are provided at no cost. Unlike traditional bootcamps that charge $10,000-$20,000+, this course is entirely community-driven and open source.
Basic programming knowledge in Python, JavaScript, or similar languages is recommended. No prior experience with AI tools is required - we’ll teach you everything you need to know about using AI in development workflows. The course is designed for developers who want to explore how AI tools fit into their workflow, engineers aiming to boost productivity with coding assistants, agents, and automation, and learners who prefer project-based practice over theory-heavy tutorials.
Each module includes hands-on projects, so the time commitment depends on your learning style and how much time you can dedicate. Most learners spend around 2 weeks to complete each module. With 6 modules total, expect to spend approximately 5-15 hours per week, depending on your background. This includes watching videos, completing homework, and working on the final project. More time may be needed during the final project weeks.
We’ll guide you through setting up and using various AI tools throughout the course, including GitHub Copilot, Cursor, Model Context Protocol (MCP), and n8n. Some tools may require subscriptions, but we’ll focus on free or low-cost options where possible. The course covers essential AI development tools and platforms that you’ll learn to integrate into real developer workflows.
To earn a certificate, you’ll need to complete a final project that demonstrates practical application of the concepts learned throughout the course. The project is submitted for peer review to ensure quality and understanding. After submitting your project, you must also review at least 3 other students’ projects by the deadline and provide constructive feedback. Learn more about the final project and certificate requirements.
Absolutely! The course is supported by the DataTalks.Club community on Slack, where thousands of learners exchange ideas, ask questions, and provide feedback. You’ll have access to a supportive community throughout your learning journey. We also have an FAQ repository with answers to common questions and a @ZoomcampQABot in Slack for quick help.
This course focuses specifically on integrating AI tools into real developer workflows, not just theory. You’ll build complete projects using AI assistants, create your own coding agents, and automate workflows - giving you practical, job-relevant skills. The course is designed with developer workflows in mind. By the end, you won’t just know what Copilot, Cursor, or n8n are; you’ll have used them to build complete projects and integrate them into real processes. Unlike many AI courses that focus on theory or chatbot development, AI Dev Tools Zoomcamp teaches you to use AI tools to actually ship software faster.
The next cohort of the AI Dev Tools Zoomcamp starts on November 18, 2025. Register here: https://airtable.com/appJRFiWKHBgmEt70/shrpw7rk55Ewr1jCG before the course starts.
The AI Dev Tools Zoomcamp is run by DataTalks.Club, a global online community of data professionals and learners. While the initial idea and most of the content were created by Alexey Grigorev, members of the DataTalks.Club community contribute as instructors and maintainers.
DataTalks.Club is often referred to as “the DataTalks Club”, “data talks club”, or “datatalks club”.
Yes! All course materials, videos, and recordings remain available after the cohort ends, and you can learn at your own pace. You’ll have access to the Slack community for support. However, self-paced learning does not include homework submissions, project evaluations, or the ability to earn a certificate. To receive a certificate, you need to join an active cohort.
No, certificates are only available when completing the course with a live cohort. Self-paced mode does not include homework submissions, project evaluations, or certificates. This is because the certification process requires you to review three projects, and these peer reviews only happen during the active course period. Additionally, the submission form closes after the peer-review list is compiled. Self-paced learners can access all course materials and the Slack community, but must join a live cohort to earn a certificate.
The GitHub repository is https://github.com/DataTalksClub/ai-dev-tools-zoomcamp.
Course videos are available on the DataTalks.Club playlist. For easier navigation, refer to the GitHub repository for course materials and links to video content. We also maintain year-specific playlists for updates.
The course covers essential AI development tools including GitHub Copilot for code generation, Cursor as an AI-first IDE, OpenAI ChatGPT and Anthropic Claude for conversational AI assistance, Model Context Protocol (MCP) for connecting AI to external systems, n8n for workflow automation, and tools for CI/CD, testing, and DevOps. You’ll also learn to build your own coding agents and integrate AI into the complete software development lifecycle.
The DataTalks.Club AI Dev Tools community is a supportive network of 80,000+ data professionals and learners. As part of the AI Dev Tools Zoomcamp, you’ll have access to a dedicated course channel in Slack where you can ask questions, get help from instructors and peers, share your progress, and connect with like-minded individuals. The community provides technical support, peer learning opportunities, and networking that can lead to collaborations and career opportunities. This active community is one of the key differentiators of the course experience.
Yes! This is a completely free AI Dev Tools course, with a certificate available when you complete the course with a live cohort. There are no hidden costs or tuition fees. To earn your certificate, you’ll need to complete the technical modules, build one final project demonstrating practical application of AI tools in development workflows, participate in peer reviews, and follow best practices. This free course provides the same quality training as paid bootcamps but at no cost. Certificates, homework submissions, and project evaluations are only available when participating in a live cohort, not in self-paced mode.
Yes, certificates are available when completing the course with a live cohort. Requirements include completing the technical modules, building one final project that demonstrates practical application of AI tools in development workflows, participating in peer reviews (reviewing at least 3 other students’ projects), and following best practices. Certificates, homework submissions, and project evaluations are not available in self-paced mode.