Microsoft Power BI – The Complete Masterclass

Course Curriculum

Chapter 1: Introduction

Lecture 1: Welcome!

Lecture 2: What is Power BI?

Lecture 3: Download & Installing Power BI Desktop

Lecture 4: Getting to know the interface

Lecture 5: Quick Interface Tour

Lecture 6: Mini Project: Transform Data

Lecture 7: Mini Project: Visualize Data

Lecture 8: Mini Project: Creating a Data Model

Lecture 9: Course Outline: What will you learn in this course?

Lecture 10: How to lean best with this course?

Lecture 11: All source files & course slides

Chapter 2: Preparing our Project

Lecture 1: Creating our initial project file

Lecture 2: Working with the attached project files

Chapter 3: Data Transformation – The Query Editor

Lecture 1: Exploring the Query Editor

Lecture 2: Connecting to our data source

Lecture 3: Editing rows

Lecture 4: Changing data types

Lecture 5: Replacing values

Lecture 6: Close & Apply

Lecture 7: Connecting to a csv file

Lecture 8: Connecting to a web page

Lecture 9: Extracing characters

Lecture 10: Splitting & merging columns

Lecture 11: Creating conditional columns

Lecture 12: A little note regarding the next lecture

Lecture 13: Creating columns from examples

Lecture 14: Merging Queries

Lecture 15: Pivoting & Unpivoting

Lecture 16: Appending Queries

Lecture 17: Practice & Solution: Population table

Lecture 18: The Fact-Dimension-Model

Lecture 19: Practice: Load the dimension table

Lecture 20: Organizing our queries in groups

Lecture 21: Text to be used in the next lecture

Lecture 22: Entering data manually

Lecture 23: Creating an index column

Lecture 24: Workflow & more transformations

Lecture 25: Module summary

Chapter 4: Data Transformation – Advanced

Lecture 1: Advanced Editor – Best practices

Lecture 2: Performance: References vs. Duplicating

Lecture 3: Performance: Enable / Disable Load & Report Refresh

Lecture 4: Group by

Lecture 5: Mathematical Operations

Lecture 6: Run R Script

Lecture 7: Using Parameters to dynamically transform data

Lecture 8: M formula language: Basics

Lecture 9: M formula language: Values, Lists & Tables

Lecture 10: M formula language: Functions

Lecture 11: M formula language: More functions & steps

Chapter 5: Creating a Data Model

Lecture 1: Why a data model?

Lecture 2: Create & edit relationships

Lecture 3: One-to-many & one-to-one relationship

Lecture 4: Many-to-many (m:n) relationship

Lecture 5: Cross filter direction

Lecture 6: Activate & deactivate relationships

Lecture 7: Module summary

Chapter 6: Data Visualization

Lecture 1: Our first visual

Lecture 2: The format tab

Lecture 3: Understanding tables

Lecture 4: Conditional formatting

Lecture 5: The Pie Chart

Lecture 6: All about the filter visual

Lecture 7: The filter pane for developers

Lecture 8: Cross filtering & edit interactions

Lecture 9: Syncing slicers across pages

Lecture 10: Creating drill downs

Lecture 11: Creating drill throughs

Lecture 12: The tree map visual

Lecture 13: The decomposition tree

Lecture 14: Understanding the matrix visual

Lecture 15: Editing pages

Lecture 16: Buttons & Actions

Lecture 17: Bookmarks to customize your report

Lecture 18: Analytics and Forecasts with line charts

Lecture 19: Working with custom visuals

Lecture 20: R Script to use

Lecture 21: Get data using R Script & R Script visual

Lecture 22: Asking questions – Q&A visual

Lecture 23: Wrap up – data visualization

Chapter 7: Power BI & Python

Lecture 1: Python in Power BI – Plan of attack

Lecture 2: Setting up Python for Power BI

Lecture 3: Transforming data using Python

Lecture 4: Python script I used in the next lecture

Lecture 5: Creating visualizations using Python

Lecture 6: Python script II used in the next lecture

Lecture 7: Violin plots, pair plots & ridge plots using Python

Lecture 8: Python script III used in the next lecture

Lecture 9: Machine learning (BayesTextAnalyzer) using Python

Lecture 10: Performance & Troubleshooting