DataTalks.Club offers a range of free online courses in Machine Learning, Data Engineering, MLOps, LLMs, and Stock Market Analytics. Each course is designed to provide practical skills and real-world experience, with a focus on hands-on learning and project-based learning.
DataTalks.Club Free Online Courses
| Course | Duration | Next cohort | Register | Article | |
|---|---|---|---|---|---|
| Machine Learning Zoomcamp | 16 weeks | September 2025 | Register | Article |  |
| Data Engineering Zoomcamp | 9 weeks | January 2026 | Register | Article | |
| MLOps Zoomcamp | 12 weeks | May 2025 | Register | Article | |
| Stock Markets Analytics Zoomcamp | 8 weeks | April 2025 | Register | Article | |
| LLM Zoomcamp | 10 weeks | June 2025 | Register | Article | |
Machine Learning Zoomcamp
Machine Learning Zoomcamp is a free 4-month course teaching machine learning engineering. You’ll learn Python ML basics through to production deployment, build real projects, and join a supportive community. Next cohort starts September 2025.
Prerequisites
The only requirement for this course is prior programming experience (1+ year) and familiarity with the command line.
Course Structure
The course is divided into two parts:
Part 1: Machine Learning Fundamentals
- Linear regression and feature engineering
- Classification and model evaluation
- Decision trees and ensemble learning
- Neural networks and deep learning
Key tools: Python, NumPy, Pandas, Scikit-Learn, TensorFlow
Part 2: Model Deployment
- Web services with Flask
- Containerization with Docker
- Cloud deployment on AWS Lambda
- Orchestration with Kubernetes
Key tools: Flask, Docker, AWS Lambda, Kubernetes, TensorFlow Serving
Data Engineering Zoomcamp
Data Engineering Zoomcamp is a free 9-week course teaching data engineering. You’ll learn how to build data pipelines, data warehouses, and analytics engines, and apply your skills to a real-world project. Next cohort starts January 2026.
Prerequisites
- Skilled in coding
- Comfortable with the command line
- Basic SQL knowledge
Course Structure
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
Technologies you’ll learn:
- Docker
- Postgres
- BigQuery
- dbt
- Apache Spark
- Apache Kafka
MLOps Zoomcamp
MLOps Zoomcamp 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.
Prerequisites
- Prior programming experience (at least 1+ year)
- Prior exposure to machine learning (at work or from other courses, e.g. from ML Zoomcamp)
- Being comfortable with the command line
- Python
- Docker (you can check ML Zoomcamp for that)
Course Structure
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
Technologies you’ll learn:
- MLFlow
- Flask
- AWS
- Mage
- Evidently AI
LLM Zoomcamp
LLM Zoomcamp is a free online course to get started with real-life applications of LLMs. In 10 weeks, you will learn how to build an AI system that answers questions about your knowledge base. Next cohort starts June 2025.
Prerequisites
- Comfortable with programming and Python
- Comfortable with command line
- Comfortable with Docker
- No previous exposure to AI or ML is required
Course Curriculum
- Module 1: Introduction to LLMs and RAG
- Module 2: Vector Search
- Module 3: Evaluation
- Module 4: Monitoring
- Module 5: Best Practices
- Module 6: End-to-End Project Example
Technologies you’ll learn:
- OpenAI API
- LangChain
- Hugging Face
- Ollama
- Qdrant
- Elasticsearch
- Streamlit
- Python
Analytics in Stock Markets Zoomcamp
Analytics in Stock Markets Zoomcamp 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.
Prerequisites
- Basic Python knowledge
- An analytical mindset to make decisions based on data
- A keen interest in financial markets
Course Structure
- 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
Course Participation Options
All course materials are hosted on DataTalks.Club’s GitHub repositories and are freely accessible to everyone. We offer two distinct ways to participate in our courses:
Self-paced Learning
This option allows you to access all course materials and learn independently:
- Access to all course content, including videos and code examples
- Freedom to study at your own pace
- Ability to focus on specific topics of interest
- No deadlines or formal assessments
- No certificate of completion
Cohort-based Learning
This structured option runs on a fixed schedule with a group of learners:
- Fixed start and end dates
- Weekly deadlines to keep you on track
- Certificate upon successful completion of course requirements
- Access to additional features:
- Homework assignments
- Weekly live office hours
- Interactive workshops
Course Structure and Components
Core Learning Materials
- Video Lectures: Each module includes recorded lectures explaining key concepts
- Code Examples: Practical demonstrations of concepts in action
- Homework Assignments: Weekly exercises to practice new skills
- Course Projects: End-to-end implementations that integrate all learned concepts
Learning Approach
Our courses follow a practical, hands-on approach:
- Start with fundamental concepts
- Progress to practical implementations
- Focus on industry-standard tools and practices
- Culminate in a comprehensive final project
Tools and Technologies
- All courses use current, industry-relevant tools
- Emphasis on open-source technologies
- Focus on tools commonly used in professional settings
- Regular updates to keep content current
Community and Support
Slack Community
Our Slack workspace serves as the hub for:
- Course discussions and questions
- Technical problem-solving
- Career discussions
- Industry networking
- Job opportunity sharing
Regular Events
We maintain an active community through various events:
- Weekly technical podcasts with industry experts
- Practical workshops on specific topics
- Open-source project discussions
- Book club meetings focusing on technical literature
All events are recorded and available on our YouTube channel, and upcoming events are listed on our website.
Frequently Asked Questions
Are these courses really free?
Yes, all our courses are completely free. The course materials, including videos and code examples, are freely available on GitHub. You only need to invest your time and effort.Do I need to attend live sessions?
Live sessions (office hours and workshops) are optional but recommended for cohort-based participants. All sessions are recorded and made available afterward.Can I switch from self-paced to cohort-based learning?
Yes, you can start self-paced and join a cohort later. Just register for the next cohort when you're ready.How much time should I dedicate per week?
We recommend dedicating 10-15 hours per week for cohort-based learning. Self-paced learners can adjust this according to their schedule.What programming languages do I need to know?
Python is the primary programming language used in all courses. The required proficiency level varies by course and is specified in the prerequisites section.Do I need a powerful computer?
Most exercises can run on any modern computer. For more demanding tasks, we provide instructions for using cloud services, many of which offer free tiers.Can I use Windows for these courses?
Yes, all courses support Windows, macOS, and Linux. We provide specific setup instructions for each operating system.How do I earn a certificate?
Certificates are available for cohort-based participants who complete the final project and peer-review 3 projects.Are the certificates recognized by employers?
While our certificates demonstrate practical skills and project completion, they are not accredited. However, the projects you build during the course can be valuable additions to your portfolio.What happens if I miss a homework deadline?
We understand that life happens. You can still submit homework after the deadline, but it won't be scored if the form is closed. We encourage staying on schedule with the cohort for the best learning experience.How long do I have access to the Slack community?
Access to our Slack community is permanent. You can continue participating in discussions and networking even after completing your course.Can I participate in multiple courses simultaneously?
While it's possible, we recommend focusing on one course at a time to ensure you can dedicate sufficient time and attention to learning the material thoroughly.What if I need help with the course material?
You can get help through multiple channels: course-specific Slack channels, weekly office hours (for cohort-based participants), FAQ section in the course repository.Ready to join our community? Use the form below to get started!