Microsoft Fabric – A Deeper Dive

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Microsoft Fabric is Generally Available!

Lecture 3: Exercises and Quizzes in this Course – Please Watch!

Lecture 4: Getting Started with Microsoft Fabric

Chapter 2: Direct Lake and Power BI

Lecture 1: Overview – Part 1

Lecture 2: Overview – Part 2

Lecture 3: XMLA-Write Support

Lecture 4: Putting Direct Lake to the Test – Part 1

Lecture 5: Putting Direct Lake to the Test – Part 2

Lecture 6: Power BI Desktop and Direct Lake

Lecture 7: On-Demand Loading

Lecture 8: Default Semantic Model vs. Custom Model

Chapter 3: Data Science in Microsoft Fabric

Lecture 1: Introduction to Data Science

Lecture 2: Data Science in Microsoft Fabric

Lecture 3: Notebooks

Lecture 4: Experiments

Lecture 5: Models

Lecture 6: Preparing Data – Data Wrangling

Lecture 7: End-to-End Project: Getting Set Up

Lecture 8: End-to-End Project: Ingesting Data

Lecture 9: End-to-End Project: Exploring the Data Part 1

Lecture 10: End-to-End Project: Exploring the Data Part 2

Lecture 11: End-to-End Project: Exploring the Data Part 3

Lecture 12: End-to-End Project: Exploring the Data Part 4

Lecture 13: End-to-End Project: Train and Evaluate the Data Part 1

Lecture 14: End-to-End Project: Train and Evaluate the Data Part 2

Lecture 15: End-to-End Project: Train and Evaluate the Data Part 3

Lecture 16: End-to-End Project: Train and Evaluate the Data Part 4

Lecture 17: End-to-End Project: Reporting Part 1

Lecture 18: End-to-End Project: Reporting Part 2

Chapter 4: Real-Time Analytics in Microsoft Fabric

Lecture 1: Introduction to Real-Time Analytics in Microsoft Fabric

Lecture 2: Event Stream

Lecture 3: Creating a KQL Database

Lecture 4: Creating an Event Stream

Lecture 5: Getting Location Data

Lecture 6: Adding the Data to the Lakehouse

Lecture 7: Exploring the Data

Lecture 8: More Data Exploration

Lecture 9: Real-Time Analytics becomes Real-Time Intelligence

Chapter 5: Data Factory in Microsoft Fabric

Lecture 1: Introduction to Data Factory in Microsoft Fabric

Lecture 2: Building a Pipeline – Part 1

Lecture 3: Building a Pipeline – Part 2

Lecture 4: Building a Pipeline – Part 3

Lecture 5: Building a Pipeline – Part 4

Lecture 6: Building a Pipeline – Part 5

Chapter 6: Data Warehouse in Microsoft Fabric

Lecture 1: Introduction to the Microsoft Fabric Data Warehouse

Lecture 2: Building a Data Warehouse – Part 1

Lecture 3: Building a Data Warehouse – Part 2

Lecture 4: Building a Data Warehouse – Part 3

Lecture 5: Building a Data Warehouse – Visual Query Builder

Lecture 6: Using Shortcuts to Analyze Data in a Lakehouse

Lecture 7: Modeling the Data and Auto-Generating a Power BI Report

Chapter 7: Apache Spark in Microsoft Fabric

Lecture 1: Introduction to Apache Spark in Fabric

Lecture 2: Spark Libraries

Lecture 3: Dataframe Basics – Part 1

Lecture 4: Dataframe Basics – Part 2

Lecture 5: Dataframe Basics – Part 3

Lecture 6: Common Operations with Dataframes

Lecture 7: Filtering Data

Lecture 8: Aggregating Data

Lecture 9: Joining Dataframes

Lecture 10: Working with Dates

Lecture 11: SQL Statements and Spark

Lecture 12: Machine Learning

Lecture 13: Microsoft Fabric 1.1. / Spark Runtime

Lecture 14: Spark Configuration

Lecture 15: Spark Autotuning

Chapter 8: Miscellaneous Topics

Lecture 1: Semantic Link for Power BI – Part 1

Lecture 2: Semantic Link for Power BI – Part 2

Lecture 3: Semantic Link for Power BI – Part 3

Lecture 4: Data Activator – Part 1

Lecture 5: Data Activator – Part 2

Lecture 6: Microsoft Fabric Licensing and Pricing

Lecture 7: Microsoft Fabric Licensing and Pricing July 2024 Update

Chapter 9: Bonus

Lecture 1: Bonus Offer

Lecture 2: DP-600 Exam