In this course, you will learn how to :
Load and manage data in a Lakehouse within Microsoft Fabric.
Utilize notebooks for comprehensive data exploration.
Preprocess data using Microsoft Fabric’s Data Wrangler for optimized model training.
Train and manage machine learning models with MLflow, tracking experiments effectively.
Generate batch predictions to apply AI in practical scenarios.
- BDD & Décisionnel
- Décisionnel
Course Microsoft DP-604 Implement a data science and machine learning solution for AI with Microsoft Fabric
Objectifs
Prérequis
Familiarity with basic data concepts and terminology.
Understanding of the Python programming language and machine learning frameworks like scikit-learn is advantageous.
Public
IT Professional
Dernière mise à jour
Bon à savoir
Evaluez votre niveau
Formations modulables
Travaux pratiques
Les Modules
de formation
Get acquainted with the data science process within Microsoft Fabric, including managing data, notebooks, experiments, and models.
Utilize Microsoft Fabric notebooks for in-depth data exploration, covering loading data, understanding data distribution, handling missing data, and applying advanced exploration techniques.
Learn how to preprocess data effectively using Data Wrangler in Microsoft Fabric, including data cleaning, handling missing values, and feature transformation.
Discover how to train machine learning models in notebooks, track experiments with MLflow, and manage models efficiently within Microsoft Fabric.
Learn to utilize machine learning models deployed in Microsoft Fabric to generate batch predictions, enhancing data enrichment and analysis capabilities.