
Course introduction
Things to know before getting started
Part 1 of the introduction
Part 2 of the introduction
Part 3 of the introduction
Part 4 of the introduction
Part 5 of the introduction
Creating a Claude account
Checking Copilot access
Explanation of the Contoso dataset used in this course
What is TMDL and why is it useful and necessary?
What is TMDL and why is it useful and necessary?
What is TMDL and why is it useful and necessary?
PBIP projects and why it's important in the world of AI
PBIP projects and why it's important in the world of AI
How to convert the Contoso PBIX to PBIP
The Key Influencers visual
The Key Influencers visual
The Decomposition Tree visual
Decomposition tree - root care analysis
The Narrative visual
Copilot for Power BI Introduction
Copilot for Power BI Introduction
Copilot for Power BI Introduction
Copilot for Power BI Introduction
We're going to obfuscate our semantic model
Using Copilot in DAX Query View
Copilot in DAX Query View - Part 2
Copilot in DAX Query View - Part 3
One step in preparing your data model for Copilot and other AI tools.
Copilot in Fabric
Creating Report Pages using Copilot
Asking Questions About Your Data using Copilot
What is MCP?
What is MCP?
Installing VS Code
Installing the Power BI Modeling MCP Server
Installing Power BI Report Authoring skills
Installing Power BI Report Authoring Skills
Putting everything we've done to the test
Putting MCP and Authoring Skills Through It's Paces
Putting MCP and Authoring Skills Through It's Paces
Putting MCP and Authoring Skills Through It's Paces
Test your knowledge
Final thoughts
Sequel to this course
Stop building Power BI reports the slow way.
AI has quietly become the most valuable skill in the Power BI ecosystem and many developers are still using a fraction of what's available to them. If you're still hand-writing every measure, manually documenting your models, and starting each report from a blank canvas, you're leaving hours on the table every single week.
This course fixes that.
You'll learn how to put AI to work across the entire Power BI development lifecycle: preparing a semantic model so AI can actually understand it, generating and debugging DAX with AI assistance, using Copilot and Claude to draft report pages and summaries, and deploying AI visuals that surface insights your users may not have thought to ask for.
What you'll learn:
Use Copilot and Claude in Power BI and Microsoft Fabric to accelerate report and model development
Write, explain, optimize, and debug DAX with AI
Prepare semantic models for AI: naming, descriptions, synonyms, and the modeling decisions that make or break any AI tool's accuracy
Build with AI visuals, Key Influencers, Decomposition Tree and Smart Narrative and know when each one earns its place
Apply AI to documentation, data profiling, and the tedious work that eats your day
Recognize where AI gets it wrong, and how to validate output before it reaches a stakeholder
Using MCP servers for semantic modeling and Skills for Fabric for report page generation
Who this course is for:
Power BI developers, data analysts, and BI professionals who already know their way around a report and want to work dramatically faster. You should be comfortable with basic DAX and the Power BI Desktop interface. You don't need any prior AI experience.
What makes this course different:
This isn't a tour of feature announcements. These techniques are demonstrated on a real world dataset (Contoso). We show you what works and what doesn't work, because knowing when not to trust AI output is what separates a professional from someone pasting prompts into a chat window.
By the end, you'll have a repeatable AI-assisted workflow you can apply to every Power BI project you touch.
Enroll now and start building faster today.