Upcoming dates

All times shown in the class's own timezone. 2 of 2 are guaranteed to run, meaning they go ahead regardless of enrollment.

Dates	Starts	Where	Status	Seat	Book
Fri, Aug 28	9:00 AM to 5:00 PM EDT	Live virtual	GUARANTEED	$695
Thu, Dec 24	9:00 AM to 5:00 PM EST	Live virtual	GUARANTEED	$695

About this class

This course is designed to build practical skills in implementing data science and machine learning solutions using Microsoft Fabric. The course explores the complete end-to-end data science process, from understanding and exploring data to preparing and transforming datasets for analysis. Students will learn how to train, evaluate, and track machine learning models, as well as how to deploy those models and generate predictions using Microsoft Fabric tools and capabilities.

Course outline

1 - Introduction to end-to-end analytics using Microsoft Fabric

Explore end-to-end analytics with Microsoft Fabric
Explore data teams and Microsoft Fabric
Enable and use Microsoft Fabric
Module assessment

2 - Get started with data science in Microsoft Fabric

Understand the data science process
Explore and process data with Microsoft Fabric
Train and score models with Microsoft Fabric
Module assessment

3 - Explore data for data science with notebooks in Microsoft Fabric

Explore notebooks
Load data for exploration
Understand data distribution
Check for missing data in notebooks
Apply advanced data exploration techniques
Visualize charts in notebooks
Module assessment

4 - Preprocess data with Data Wrangler in Microsoft Fabric

Understand Data Wrangler
Perform data exploration
Handle missing data
Transform data with operators
Module assessment

5 - Train and track machine learning models with MLflow in Microsoft Fabric

Understand how to train machine learning models
Train and track models with MLflow and experiments
Manage models in Microsoft Fabric
Module assessment

6 - Generate batch predictions using a deployed model in Microsoft Fabric

Customize the model's behavior for batch scoring
Prepare data before generating predictions
Generate and save predictions to a Delta table
Module assessment

Before you attend

You should be familiar with basic data concepts and terminology.

Who this is for

This course is intended for data professionals and practitioners who regularly work with machine learning models and are responsible for building, evaluating, and deploying data science solutions. Students should already be familiar with the data science process, Python, and common open-source machine learning frameworks such as scikit-learn.