One of my favorite things about DataTalks.Club Zoomcamps is that they are completely free and community-driven. Different Zoomcamp cohorts run throughout the year, covering areas such as data engineering, machine learning, MLOps, LLMs, and AI development. When a cohort is active, you can learn alongside other participants, follow deadlines, complete homework and projects, and participate in the DataTalks.Club community instead of learning everything alone. The course materials also remain available on GitHub, so you can take them at your own pace.
In this article, we will explore five free DataTalks.Club Zoomcamps that can help you learn data engineering, machine learning engineering, MLOps, LLM application development, and AI-assisted software development.
1. Data Engineering Zoomcamp
The Data Engineering Zoomcamp is a free nine-week course that teaches you how to build an end-to-end data pipeline from scratch.
You will work with technologies such as Docker, PostgreSQL, Terraform, Kestra, BigQuery, dbt, DuckDB, Bruin, Spark, and Kafka while learning data warehousing, workflow orchestration, analytics engineering, batch processing, and streaming. The course finishes with a project where you put these concepts together into a complete data engineering pipeline.
I like this course because you are not just learning individual data tools. You get to see how these technologies connect to form a modern data engineering stack.
2. Machine Learning Zoomcamp
The Machine Learning Zoomcamp takes you from learning core machine learning concepts to actually deploying machine learning applications.
You will learn regression, classification, model evaluation, decision trees, ensemble methods, deep learning, and deployment, while working with technologies such as Docker, FastAPI, Kubernetes, and AWS Lambda.
This is one of the courses I would recommend if you already know some Python but want to understand the complete machine learning workflow. Instead of stopping after model.fit(), you learn what it takes to turn a model into an actual application.
The course can be completed independently, or you can join a live cohort when one is running. The 2026 cohort, for example, starts on September 14, 2026.
3. MLOps Zoomcamp
Training a machine learning model is only one part of building a production machine learning system. The MLOps Zoomcamp focuses on what happens after the model has been developed.
You will learn about experiment tracking with MLflow, workflow orchestration, model deployment, monitoring, testing, CI/CD, GitHub Actions, Terraform, Prometheus, Grafana, and Evidently.
I particularly like this course because MLOps can be difficult to learn from theory alone. Here, you get to understand how experiment tracking, deployment, monitoring, and automation fit together to keep a machine learning system running in production.
There is no live MLOps cohort planned for 2026, but the entire course remains available for free as a self-paced program.
4. LLM Zoomcamp
The LLM Zoomcamp is probably the course I would recommend most if you want to learn how modern LLM applications are actually built.
The free 10-week course covers RAG, vector search, embeddings, AI agents, function calling, orchestration, evaluation, monitoring, hybrid search, and reranking. You eventually build a complete LLM application rather than simply experimenting with prompts or calling an LLM API.
What I like most about this course is the focus on the complete system around the LLM. You learn retrieval, evaluation, monitoring, and search, which are often just as important as choosing the model itself.
You also do not need a GPU to get started, although the course notes that some API exercises may require a small amount of API credit.
5. AI Dev Tools Zoomcamp
The AI Dev Tools Zoomcamp is different from the other courses on this list. Instead of teaching you how to train AI models, it focuses on using modern AI coding assistants and agents as part of the software development process.
You will learn how to use AI for planning, implementation, testing, code review, API development, Docker, deployment, CI/CD, DevOps, and security. It also explores newer coding-agent capabilities such as MCP, skills, plugins, hooks, and subagents.
I think this is especially useful because AI coding is quickly moving beyond asking a chatbot to generate a function. The course focuses on using agents throughout a structured engineering workflow while still keeping testing, review, security, and deployment in the loop.
The 2026 cohort starts on August 31, 2026, and the repository notes that some of the new course materials are still being finalized.
Final Thoughts
What I like most about Zoomcamps is that they have kept the spirit of free, community-driven learning alive since the COVID-19 era. Years later, DataTalks.Club is still providing complete bootcamp-style courses that anyone can join, follow, and learn from without paying tuition.
These are not just collections of videos. You can attend cohorts, complete homework, build projects, interact with the community, and follow a structured learning path similar to a paid bootcamp. Even if you miss the live cohort, the materials remain available for self-paced learning.
Over the years, I have also seen many stories from Zoomcamp participants who used these programs to upskill, move into new technical roles, land jobs, or earn promotions in their current careers. That is what makes these courses valuable: they give people access to practical, job-relevant skills without putting cost in the way.
Abid Ali Awan (@1abidaliawan) is a certified data scientist professional who loves building machine learning models. Currently, he is focusing on content creation and writing technical blogs on machine learning and data science technologies. Abid holds a Master's degree in technology management and a bachelor's degree in telecommunication engineering. His vision is to build an AI product using a graph neural network for students struggling with mental illness.
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