Course Description
In this 1-day Microsoft Copilot For Power BI training is designed to help students understand how Copilot enhances report development, data modeling, and natural‑language exploration inside Power BI. The training typically assumes intermediate Power BI experience, meaning participants should already understand data preparation, modeling, and analytics concepts.
Purpose of the training
The goal is to help users adopt Copilot as a productivity accelerator in Power BI. Participants learn how Copilot:
- Assists in building and refining semantic models.
- Generates report elements and insights from natural language.
- Supports data exploration through conversational interaction.
- Help automate or speed up repetitive analytical tasks.
Participants Learn
- How Copilot integrates into Power BI Desktop and the Power BI Service.
- Which tasks can Copilot automate or accelerate.
- Generating report pages, visuals, and summaries using natural language.
- Refining visuals, formatting, and narrative explanations with Copilot prompts.
- Ask Copilot questions about their data to uncover insights.
- This foundation helps them understand when and why
- Asking Copilot to write new DAX measures.
Course Summary
Next Public Course Dates | |
| Prerequisites | • To use Copilot in Power BI Desktop, you need at least a member or contributor access to at least a single workspace that is assigned to your orgs paid Fabric capacity (F2 or higher). • Previous knowledge of Power BI is required, ideally taken Microsoft’s or our 3-day PL-300 Power BI Data Analyst Class or used the tool for one year. |
| Duration |
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| Available Formats |
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| Post Training Support | Yes, our certified Microsoft Power Platform and AI trainers will be available for additional questions once you start working on your own data and dashboards. |
Course Modules
Module 1 — Introduction to Copilot in Power BI
Topics:
- Level-Setting Topics
- What Copilot is and how it works inside Power BI
- Where Copilot appears in Desktop & Service
- Supported AI‑assisted experiences
- Requirements, admin settings, and capacity needs (from tutorial prerequisites)
- Overview of use cases for analysts, business users, and enterprise teams
Module 2 — Preparing Data & Models for Copilot
Topics:
- Understanding semantic model requirements for Copilot
- Making data AI‑ready
- Simplifying schemas & ensuring discoverable fields
- Creating Verified Answers (from tutorial content)
- Managing relationships & metadata quality
- Data governance & admin considerations (from tutorial settings)
Hands‑on:
- Reworking a semantic model for improved Copilot responses
- Configure metadata, synonyms, and descriptions
Real‑world use cases:
- AI‑ready model design for sales analytics
- Preparing a model for finance reporting
- Building semantic clarity for customer analytics
Module 3 — Natural Language Interaction & Copilot Chat
Topics:
- How Copilot interprets natural language
- Asking questions and drilling down
- Getting insights using conversational analytics
- Limitations & question‑framing strategies
Hands‑on:
- Ask Copilot to summarize regional sales
- Ask Copilot to identify anomalies in KPIs
- Generate analysis narratives
Expanded Cases:
- Operational analytics example: “What caused today’s drop in production output?”
- Marketing analytics example: “Summarize leads by channel and suggest insights.”
Module 4 — AI‑Assisted Report Creation
Topics:
- Generating visuals from natural language
- Automatically creating page layouts
- AI suggestions for charts, filters, and summaries
- DAX assistance concepts
- Automated reporting & DAX creation
Hands‑on:
- Generate a full report using Copilot prompts
- Improve the report layout suggested by Copilot
- Use Copilot to explain visuals
Extended Cases:
- Executive dashboard creation
- HR attrition report automation
- Inventory optimization visuals
Module 5 — Advanced Copilot Features & AI Instructions
Topics:
- Authoring AI instructions in Power BI Desktop
- Custom instructions for tailored insights
- Enhancing Copilot’s responses using metadata
- Multi‑workspace AI readiness
Hands‑on:
- Add instructions for business definitions
- Improve Copilot’s narrative quality with refined schemas
Expanded Use Cases:
- Industry‑specific instructions for retail, healthcare and manufacturing
- Enforcing terminology compliance using AI instructions.
Module 6 — Practical End‑to‑End Copilot Scenario
Activities:
- Build a semantic model
- Prepare AI instructions
- Create insights using Copilot
- Generate reports
- Publish and validate in workspace
Scenario Options:
- Sales performance analytics (tutorial sample)
- Customer churn analysis
- Financial forecasting (AI‑assisted visuals + external model inputs)
Module 7 — Copilot Limitations, Best Practices & Governance
Topics:
- Avoiding misleading instructions
- Ensuring accuracy in AI responses
- Responsible AI usage
- Workspace & capacity management
Discussion:
- Comparing Copilot vs manual analysis
- How to validate AI‑generated insights
- Common pitfalls and troubleshooting
Testimonials
The trainers clear and obvious enthusiasm for number crunching, analytics, and teaching others is infectious. He doesn’t waste time, shows exactly what you need to know and is genuinely hilarious.
Every one of my employees had tons of positive stuff to say.
- Benjamin G, MXSG Analysis and Integration Chief, US Air Force
“Steve was a great instructor and was able to articulate the course material in a way that promoted learning.”
- Ben Ruddock, Analyst, GSP International Airport
“ExistBI, Thank you again for the great Microsoft Power BI, PowerApps and Power Automate courses, our team was very happy”
- Kerry Urofsky, Systems Manager, Service, Avantik
“Mahesh was an EXCELLENT trainer. Very gifted instructor. Able to clearly communicate and teach objectives. Very engaging made you want to keep learning, and was so patient and kind to all students. Would love to be taught by him anytime.
- Jackie Calvo, Quality Improvement Manager, Horizon Health Center
