We often receive questions about our free courses, such as when the next cohort starts, how to prepare, and whether materials are available beforehand. To address these inquiries, we’ve crafted this article as a comprehensive guide for all free DataTalks.Club courses.
The structure of this article is as follows:
- A table with the main information about our courses alongside the start dates of their next cohorts
- How do I participate in the courses? Self-paced mode vs. cohort mode
- Key aspects of our courses
- Brief descriptions of each course
- Information about DataTalks.Club community
Table with the main information about DataTalks.Club courses
| Course | Duration | Next cohort | Article | |
|---|---|---|---|---|
| Machine Learning Zoomcamp | 16 weeks | September 2025 | Article |  |
| Data Engineering Zoomcamp | 9 weeks | January 2026 | Article | |
| MLOps Zoomcamp | 9 weeks | May 2025 | Article | |
| Stock Markets Analytics Zoomcamp | 8 weeks | April 2025 | Article | |
| LLM Zoomcamp | 10 weeks | June 2025 | Article | |
How do I participate in the courses? Self-paced mode vs. cohort mode
All course materials are freely accessible on DataTalks.Club’s GitHub page. You can choose from two modes of learning:
- Self-paced mode: Ideal for individuals who prefer to learn at their own pace or are interested in specific topics from the course. In this mode, you cannot submit homework for review or receive a certificate. For those features, consider the alternative mode.
- Cohort mode: This mode enables participants to earn a certificate by timely completing and submitting the required course project(s). Additional benefits include homework submission for feedback, participation in online office hours to ask your questions, and access to bonus workshops and other online events organized for some cohorts.
Key aspects of our courses
- Blending Theory and Practice: We cover the key concepts of each topic, and then give you the chance to put what you’ve learned into practice.
- Course Materials: Alongside video lectures, we provide code demos to bring the concepts to life. This way, you get to see how these ideas work in practice, not just in theory.
- Homework: After each module, we assign homework. It’s your opportunity to test your understanding.
- The Final Project: At the end of the course, you’ll tackle a final project. This is where you can apply everything from the course to create an end-to-end project and enhance your portfolio.
- DataTalks.Club Community: Our community is here to support you. Through our Slack channel, you can ask questions, share insights, or simply connect with fellow learners and instructors.
Machine Learning Zoomcamp
This course is perfect for those who want to understand the fundamentals of machine learning and learn to use the main ML frameworks and tools. The only requirement for this course is prior programming experience (1+ year) and familiarity with the command line.
You don’t have to have any prior knowledge of machine learning as we’ll guide you from the very basics to advanced topics. The course is divided into two parts:
- Part 1 covers machine learning algorithms implemented in Python, including Linear Regression, Classification, Decision Trees, Ensemble Learning, and Neural Networks.
- Part 2 focuses on deploying models using popular frameworks like Flask, TensorFlow, and Kubernetes.
You can find more information about the course on its GitHub repository. If you’re ready to join, register using this form.
Data Engineering Zoomcamp
This course is suited for people who already know how to code and use basic SQL and want to learn about building data systems.
You’ll spend the first six weeks learning and practicing each part of the data engineering pipeline. In the concluding three weeks, you will apply your acquired knowledge and skills to develop an end-to-end data pipeline from the ground up.
- Week 1: Introduction & Prerequisites
- Week 2: Workflow Orchestration
- Week 3: Data Warehouse
- Week 4: Analytics engineering
- Week 5: Batch processing
- Week 6: Streaming
- Weeks 7, 8, 9: Project
You can find more information about the course on its GitHub repository. If you’re ready to join, register using this form.
MLOps Zoomcamp
This course is useful for people who plan to work with ML services at any stage. It can be useful for data scientists, ML engineers, and software developers who are interested in understanding MLOps, the process of putting machine learning code in production.
The course guides you step-by-step through each stage of the MLOps cycle starting from experimentation and model selection to model deployment to monitoring. In the concluding three weeks, you will apply your acquired knowledge and skills to develop an end-to-end machine learning project.
- Week 1: Introduction & Prerequisites
- Week 2: Experiment tracking and model management
- Week 3: Orchestration and ML Pipelines
- Week 4: Model Deployment
- Week 5: Model Monitoring
- Week 6: Best Practices
- Weeks 7, 8, 9: Project
You can find more information about the course on its GitHub repository. If you’re ready to join, register using this form.
Analytics in Stock Markets Zoomcamp
This course will teach you data-driven decision-making, using popular Python libraries to work with financial data from data types and cleaning to hypothesis testing and making predictions. Also, it will cover the basics of trading strategies and simulation. As a result, you will build a semi-automatic trading system to systematically generate predictions and execute trades.
You need basic Python knowledge, an analytical mindset to make decisions based on data, and a keen interest in financial markets to apply the knowledge immediately to succeed in this course.
- Week 1: Introduction and Data Sources
- Week 2: Working with the Data (in Pandas)
- Week 3: Analytical Modeling
- Week 4: Trading Strategy and Simulation
- Week 5: Deployment and Automation
- Week 6, 7, 8: Project
You can find more information about the course on its GitHub repository. If you’re ready to join, register using this form.
LLM Zoomcamp
If you’re comfortable with Python and the command line, you can pass this course to learn about real-life applications of LLMs. In 10 weeks you will learn how to build an AI bot that can answer questions about your knowledge base. No previous exposure to AI or ML is required!
This is a work in progress as we just plan to run the course’s first iteration in Summer 2024. We want to cover:
- Introduction to LLMs and RAG
- Open-source and self-hosting LLMs
- Vector databases
- LLM Orchestration
- Monitoring and guardrails
- Tips and tricks
You can find more information about the course on its GitHub repository. If you’re ready to join, register using this form.
DataTalks.Club community
DataTalks.Club has a supportive community of like-minded individuals in our Slack. It is the perfect place to enhance your skills, deepen your knowledge, and connect with peers who share your passion. These connections can lead to lasting friendships, potential collaborations in future projects, and exciting career prospects.
We host multiple types of events: podcasts, webinars, workshops, open-source spotlight, and book-of-the-week. You can check our website and YouTube channel with recordings to learn more about our events.
Use the form below to join DataTalks.Club!