Course Wiki

Zoomcamps

The DataTalks.Club Zoomcamps: free, open-source cohort courses covering machine learning, data engineering, MLOps, LLM engineering, AI developer tools, and stock market analytics.

The Zoomcamps are the free, open-source course family run by DataTalks.Club. Each course covers one role-shaped slice of the data and AI stack — machine learning engineering, data engineering, MLOps, LLM engineering, AI-assisted software development, and stock market analytics — through pre-recorded videos, homework, and an end-to-end project. All materials live in public GitHub repositories, and every course can be taken self-paced at any time.

The portfolio grew from the first Data Engineering Zoomcamp into a family covering Machine Learning, Data Engineering, MLOps, LLMs, Stock Analytics, and AI Dev Tools. This wiki is the course knowledge layer: each course has a page with its module map, and the concepts taught across the courses are extracted into their own pages and linked together.

The shared course model

Every Zoomcamp follows the same operating model:

• Lectures are pre-recorded and free; materials and homework live in the course repository.
• A live cohort adds shared deadlines, scored homework, a leaderboard, peer review, and certificate eligibility. There are no live classes.
• Self-paced learners can start anytime and use everything for free, but certificates require a live cohort.
• Every course ends in a project: the midterm/capstone pattern in the longer courses, a final project in the rest. Projects are peer-reviewed.
• Learning in public (blogging, posting progress) earns bonus points toward homework and project scores.

The courses

• Machine Learning Zoomcamp — from regression and classification to deploying models as web services with FastAPI, Docker, Kubernetes, and AWS Lambda. Materials
• Data Engineering Zoomcamp — an end-to-end pipeline built from scratch with Docker, Terraform, Kestra, BigQuery, dbt, Spark, and Kafka. Materials
• MLOps Zoomcamp — experiment tracking, orchestration, deployment, monitoring, and best practices around one NY Taxi use case. Materials
• LLM Zoomcamp — building production LLM applications with agentic RAG, vector search, evaluation, and monitoring. Materials
• AI Dev Tools Zoomcamp — AI-native software engineering: coding agents, context engineering, MCP, tests, CI/CD, deployment, and observability for AI-built apps. Materials
• Stock Markets Analytics Zoomcamp — financial data analysis and trading strategy simulation with pandas, time-series models, and automation, run with PythonInvest. Materials

Concept glossary

Every concept taught across the courses is extracted into its own page, and each concept page links the exact units (modules and lessons) that cover it. Start from the Concept Glossary to find where a concept is taught.

Shared concepts across courses

The courses reuse each other’s foundations, and the concept pages in this wiki link them together:

• Docker appears in Machine Learning (packaging model services), Data Engineering (pipeline components), MLOps (deployment and integration testing), and AI Dev Tools (containerizing apps).
• Workflow orchestration is taught with Kestra in Data Engineering and LLM Zoomcamp, and with Prefect in MLOps Zoomcamp.
• dlt data ingestion appears in both the Data Engineering and LLM Zoomcamp workshops.
• FastAPI serves models in Machine Learning Zoomcamp and backs the full-stack app in AI Dev Tools Zoomcamp.
• CI/CD with GitHub Actions closes out MLOps Zoomcamp best practices and the AI Dev Tools deployment pipeline.