Descrizione

Explore the data science process and learn how to train machine learning models to accomplish artificial intelligence in Microsoft Fabric.

Become a machine learning expert. DP-604 teaches you how to design, develop, and deploy machine learning solutions in Azure Machine Learning Studio. Learn about machine learning pipelines, model training, evaluation, and deployment to leverage AI for real-world problems.

Target

Students willing to Implement data science and machine learning for AI in Microsoft Fabric

Prerequisiti

You should be familiar with basic data concepts and terminology.

Programma Corso

Module 1: Get started with data science in Microsoft Fabric

• Understand the data science process
• Train models with notebooks in Microsoft Fabric
• Track model training metrics with MLflow and experiments

Module 2: Explore data for data science with notebooks in Microsoft Fabric

• Load data and perform initial data exploration.
• Gain knowledge about different types of data distributions.
• Understand the concept of missing data, and strategies to handle missing data effectively.
• Visualize data using various data visualization techniques and libraries.

Module 3: Preprocess data with Data Wrangler in Microsoft Fabric

• Learn Data Wrangler features, and its role in the data science workflow.
• Perform different types of preprocessing operations in data science.
• Learn how to handle missing values, and imputation strategies.
• Use one-hot encoding and other techniques to convert categorical data into a format suitable for machine learning algorithms.

Module 4: Train and track machine learning models with MLflow in Microsoft Fabric

• Train machine learning models with open-source frameworks
• Train models with notebooks in Microsoft Fabric
• Track model training metrics with MLflow and experiments in Microsoft Fabric

Module 5: Generate batch predictions using a deployed model in Microsoft Fabric

• Save a model in the Microsoft Fabric workspace
• Prepare a dataset for batch predictions
• Apply the model to dataset to generate new predictions
• Save the predictions to a Delta table