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Microsoft generative AI: start with one application

Microsoft’s 21-lesson reference separates learning and building; choose one direction first.

Original course and review scope

Publisher: Microsoft Cloud Advocates · Reviewed entry language: English / en

Introduction, syllabus and prerequisites reviewed; videos and full course exercises not completed.

Open original course ↗
Last checked: Version: 3Event date: Not verified
A quick glossary

Models generate and reason. Agents use tools to work on tasks. A harness manages an agent’s environment. MCP connects tools and data. Skills are reusable task guidance.

Before you start

Prerequisites

  • Basic Python or TypeScript helps for Build labs; start with Learn chapters when reading only.
  • English entry reviewed; our eight-language guide does not guarantee translated chapters in the original course.

Estimated time

Finish one practice page before planning further study; no promised full-course duration.

Implementation steps

  1. Write a small goal first

    Stage practice: Use three sentences you wrote as material. Record one checkable question and expected answer. Avoid work or personal files; turn “learn AI” into one task card.

    Sources for this stage: Microsoft · Generative AI for Beginners

  2. Do one paper exercise

    Stage practice: Write two prompts for the same question: goal only, then material, output format and unknown handling. Compare their answer requirements on paper and mark checkable conditions versus slogans.

    Sources for this stage: Microsoft · Generative AI for Beginners

  3. Check with a counterexample

    Stage practice: Add a question with no answer in your material and require an explicit unknown. Check both cards for traceable answers and stopping when evidence is missing; fluency is not correctness.

    Sources for this stage: Microsoft · Generative AI for Beginners

  4. Decide whether to run a lab

    Stage practice: Finish a one-page record: input, expectation, actual or paper result, one failure and unresolved costs. Then follow the course’s current setup; you choose any account, API or hardware requirements yourself.

    Sources for this stage: Microsoft · Generative AI for Beginners

Validation checks

Practice

Finish a one-page record: input, expectation, actual or paper result, one failure and unresolved costs. Then follow the course’s current setup; you choose any account, API or hardware requirements yourself.

Cost

Not verified

Public materials can be read for free; check accounts, inference allowance, hosting and hardware before running labs. Our paper exercises need no paid service and do not register or call APIs for you.

Limits & boundaries

  • Introduction, syllabus and prerequisites reviewed; videos and full course exercises not completed.
  • Public materials can be read for free; check accounts, inference allowance, hosting and hardware before running labs. Our paper exercises need no paid service and do not register or call APIs for you.

Original sources

  1. Microsoft · Generative AI for Beginners ↗

    github.com · · Official documentation

  2. Microsoft · MIT license ↗

    raw.githubusercontent.com · · Official documentation