Master Claude API, tool use, agents, and RAG — build production AI apps for data engineering in Python, solo.
Most AI tutorials show you demos. This course ships code you can run on Monday morning.
What you’ll learn
- Build Claude AI apps in Python — chatbots, document extractors, SQL agents, and pipeline reporters — all deployable in production..
- Write system prompts that give Claude a consistent voice and role so every tool your team uses sounds like it was built by a human..
- Use Claude tool use to automate real data engineering tasks: dbt model generation, Snowflake SQL co-pilot, Airflow debugging..
- Build a RAG pipeline that searches your own documents using Claude’s 200K context window — no vector database required..
- Create autonomous agents with memory, routing, and guardrails that run overnight pipelines and send results without human input..
- Ship two complete projects — a SQL/dbt code reviewer and a weekly pipeline report generator — from scratch in under 20 minutes each..
Course Content
- The 3-Line Revolution –> 3 lectures • 9min.
- Your AI Sounds Like You –> 2 lectures • 8min.
- Read, Extract, and Search –> 3 lectures • 10min.
- Claude Does Things –> 3 lectures • 12min.
- Your First Agent –> 3 lectures • 14min.
- Claude for Your Data Stack — Daily Wins –> 3 lectures • 10min.
- Ship and Build — Two Real Projects –> 3 lectures • 10min.
- The Snowbrix Story + What Will You Build? –> 2 lectures • 9min.
- Practice Test — Claude AI: Build What Used to Take Teams –> 0.
Requirements
Most AI tutorials show you demos. This course ships code you can run on Monday morning.
You will build real Claude AI applications from scratch using the Anthropic Python SDK — a SQL agent that talks to your database in
plain English, a RAG pipeline that searches your own documents without a vector database, autonomous agents that run overnight and
send results, and two complete projects you can deploy as internal tools immediately.
The course covers the full Claude toolkit: system prompts, structured outputs, tool use, multi-tool chains, memory, routing, and
guardrails. Every concept is taught with working Python code and a real use case from data engineering — dbt model generation,
Snowflake SQL co-pilot, Airflow pipeline debugging, and automated weekly reporting.
You do not need an AI or machine learning background. If you can read and write basic Python functions, you are ready. The course
starts with three lines of code and builds to production-grade agents by the end.
Every lesson opens with a real story from a data team. You will see exactly where Claude saves hours, what breaks in production and
why, and how to avoid the mistakes that waste API credits.
By the end you will have six working tools, the mental model to build anything with Claude, and a clear path to shipping AI
features without a dedicated ML team.