Training tracks

Pick one. The first session sets the level and the project. You are not buying a bundle of videos.

• Data Engineering mentorship

  1-on-1 training on pipelines, warehouses, and the systems that keep production data reliable.

• Data Science mentorship

  Personal training from problem framing through analysis, modeling, and how you present the result.

• Python and SQL training

  The two languages every data role still tests. Sessions are exercises, not slide tours.

• PySpark, Databricks, and Snowflake

  Hands-on mentorship on Spark jobs and the two warehouses hiring managers actually ask about.

• AWS and cloud data platforms

  Training on the cloud data stack: storage, compute, IAM, and how a pipeline actually runs there.

• ETL, ELT, and data warehousing

  How data moves, where it lands, and how you know it is still right tomorrow.

• Machine learning and deep learning

  Mentorship on models you can train, evaluate, and explain. No leaderboard cosplay.

• Generative AI mentorship

  Practical GenAI: what the model is doing, where it fails, and how you put it in a product without handing it your database.

• LLMs, prompt engineering, and RAG

  Training on prompts that are testable, retrieval that is inspectable, and answers you can trace.

• AI agents and agentic systems

  Mentorship on agents that call tools, stop when they should, and leave a log a human can read.

• NLP and AI applications

  From classical text problems to applications that sit on top of modern language models.

• ETL testing

  How to test a pipeline: counts, keys, balances, and the defects that pass a happy-path demo.