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Learning path · Build AI

RAG and evaluation specialist

Make AI answer from your own documents, and measure how good the answers are.

This is you

You want AI to answer questions from the documents of an organization, and you want to prove that the answers are right. You can write some Python, or you will learn it here.

Where you are going

A RAG and evaluation specialist

  • Build a pipeline that finds the right passages and answers from them
  • Measure answer quality with a test set, metrics and judges
  • Find why an answer is wrong: the search, the prompt or the data
  • Handle PDFs, tables and scanned documents
  • 3 stages
  • 9 courses, 9 available now
  • About 136–184 hours of study
  • 9 certificates of completion

How much code you need

  1. No code
  2. Read code
  3. Some code
  4. Code is central

Code is central: you build and test a pipeline. Each step is small, and the lessons show the full code.

Your route, stage by stage

Each stop is a course. Its shape tells you how much of it to take.

  • Full course. The whole course, with its practice. It leads to a certificate of completion.
  • Concepts. Only the concept modules, read without running code. They lead to a concepts certificate.
  • Optional. Useful for some people. You do not need it, and it is not counted in the time.
  1. You, today

  2. Stage 1 Foundationsabout 46–62 h

    1. AI Career Foundations: Roles, Skills and Roadmaps

      Full course4–6 h

      See where this specialty fits in AI work.

    2. Python for Practical AI Engineering

      Full course18–24 h

      Python for every pipeline that you build.

    3. Essential Mathematics and Statistics for AI

      Full course12–16 h

      The statistics behind every quality measure.

      Focus: If you already studied this, do its final assignment instead.

    4. SQL and Data Preparation for AI

      Full course12–16 h

      Clean data and a test set start every evaluation.

  3. Stage 2 Large language modelsabout 30–42 h

    1. LLMs: How They Work and How to Choose One

      Full course8–12 h

      What LLMs can and cannot do with your documents.

    2. Building Reliable Applications with LLM APIs

      Full course22–30 h

      Call LLMs reliably, with structured output.

  4. Stage 3 Your specialtyabout 60–80 h

    1. RAG: Building AI That Uses Your Data

      Full course24–32 h

      The core of this path: answers from your own data.

    2. Evaluating and Testing AI Systems

      Full course20–26 h

      Prove that the answers are good, and keep them good.

    3. Document and Multimodal AI

      Full course16–22 h

      Most real documents are PDFs, tables and scans.

  5. You arriveA RAG and evaluation specialist

Earn certificates as you go

You do not need to finish the whole path to show what you learned. Each full course gives a certificate of completion, and each concepts course gives a concepts certificate. Share each one when you get it.

When you are ready, prepare for the interview: Interview preparation: AI Engineer

Make it my path All learning paths

Choose this goal in your profile. My learning then shows your progress on this route, and the weeks it takes at your pace.