Power BI & Claude : DAX Made Easy. Visuals Reimagined.

Build dashboards, machine learning models, advanced visuals and decision intelligence with Claude

Created bySeaportAi .

Last updated 7/2026

English

What you'll learn

How to create Power BI measures without writing DAX?
How to build executive dashboards using simple prompts?
How to create visuals that Power BI cannot build natively?
How to perform machine learning without knowing Python?
How to build predictive models using natural language?
How to automate repetitive analytics tasks using Claude Skills?
How to business questions into insights faster than ever before?
How can Deneb and Vega-Lite unlock a new class of Power BI visualizations?
How can you move from reporting and dashboards to AI-assisted decision intelligence?

Course content

7 sections • 29 lectures • 2h 45m total length

Was Self-Service BI Ever Truly Self-Service?3:55
What Happens When Claude Connects to Power BI?11:40

Loading the data5:12
Data Transformation7:08
Transform data in Power BI by cleaning and reshaping—rename columns, remove rows or duplicates, adjust data types, and apply changes to load a clean dataset.
Text Box2:27
Build visuals in Power BI using the available visualization options, filter reports by product or country, and create a banner with a formatted text box.
Card Visual5:58
Create a card visual to display total profit, total sales, and total discounts, then format the visual with borders, titles, color, alignment, and data labels for clear, scalable numbers.
Stacked Column Chart4:26
Learn to build and format a stacked column chart in Power BI, aligning data labels, decimals, borders, and date hierarchy to compare sales across product lines and deals.
Stacked Bar Chart3:27
Explore building and formatting a stacked bar chart in Power BI by using product as the axis, sales values as the measure, and legend options.
Multi Row Card4:16
Create a Power BI multi-row card to display the top three products by profit, using basic and advanced filters and top N options, for an editable dashboard.
Tree Map3:21
Pie Chart3:02
Create a pie chart on a new page, assign product to the legend and profit to values, and format the chart with legend size, data labels, title alignment, and colors.
Dual Axis Chart (Line and Stacked Column Chart)6:49
Ribbon Chart2:59
Slicer5:03
Demonstrates building a bar chart of profit by product for ABC company and filtering it with a slicer, explaining multi-select and single-select options, tick boxes, and radio buttons.
Map Visual3:14
Explore creating a map visual in Power BI to compare profit, sales, and discounts across countries, with circle size tied to profit and interactive tooltips.
Page Tool Tip6:14
Funnel Chart2:04
Learn to create a funnel chart in Power BI to compare country performance by profit, highlight top and bottom performers, and customize colors and fonts.

Introduction to DAX9:22
Understanding different types of DAX functions6:57
Discover the six core types of DAX functions—date and time, lookup value, logical, math, percentile, and text—and how to create them with measure, quick measure, or conditional column.
Gage Chart4:14
Learn to build a gauge chart in Power BI by creating target and max measures to visualize profit against a 16.89 million target and a 40 million max.
Conditional Column12:20
Create a conditional column in Power BI with and without DAX, using if, nested if, and switch logic to classify profit or loss and test in Power Query Editor.

Requirements

Knowledge of PowerBI
(Though refresher of PowerBI topics is provided as optional resources)

Description

Business Intelligence has spent decades trying to make analytics accessible to everyone. Self-Service BI was a major step forward, promising to put reporting and analysis directly into the hands of business users. Yet many organizations discovered that true self-service remained elusive. Creating advanced DAX measures, building sophisticated visualizations, and developing predictive models often required specialist skills, while significant time was spent on formatting and dashboard design rather than generating insights.

Today, a new generation of AI tools is transforming that experience. With Claude, Model Context Protocol (MCP), machine learning, and advanced visualization frameworks, users can interact with Power BI in ways that were previously unimaginable. Measures, DAX queries, and analytical insights can now be generated through natural language. Tasks that once required technical expertise can increasingly be accomplished through effective prompting.

This course explores how Power BI is evolving from a reporting platform into an AI-assisted analytics environment.

You will learn:

. How to use Claude with Power BI models,

. Create advanced visualizations using HTML Content and Deneb

. Build Python-powered analytics without extensive programming knowledge and

. Leverage machine learning techniques such as forecasting, clustering, anomaly detection, and predictive modeling.

More importantly, you will discover how AI can help accelerate the journey from business question to actionable insight. The future of analytics is not about replacing human expertise. It is about combining domain knowledge with AI capabilities to make analytics faster, more accessible, and more impactful than ever before.

Who this course is for:

Students
Analysts
CxO's
Machine Learning enthusiasts
Anyone interested in building Business Intelligence Visuals & Dashboards

Power BI & Claude : DAX Made Easy. Visuals Reimagined.

What you'll learn

Explore related topics

Course content

From Self-Service BI to AI-Assisted BI2 lectures • 16min

Beyond Native Visuals2 lectures • 21min

No-Code Advanced Analytics and Machine Learning4 lectures • 20min

Skills1 lecture • 8min

Optional Learning Resource: Power BI Refresher - Data & Visualization15 lectures • 1hr 6min

Optional Learning Resource: Power BI Refresher - DAX4 lectures • 33min

Conclusion and Data Privacy1 lecture • 3min

Requirements

Description

Who this course is for: