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Implement a Data Science and Machine Learning Solution for AI with Microsoft (DP-604T00)
Course Description
Overview
Explore the data science process and learn how to train machine learning models to accomplish artificial intelligence in Microsoft Fabric.
Objectives
Students will learn to,
- Get started with data science in Microsoft Fabric
- Explore data for data science with notebooks in Microsoft Fabric
- Preprocess data with Data Wrangler in Microsoft Fabric
- Train and track machine learning models with MLflow in Microsoft Fabric
- Generate batch predictions using a deployed model in Microsoft Fabric
Audience
Students willing to Implement data science and machine learning for AI in Microsoft Fabric
Prerequisites
Students should be familiar with basic data concepts and terminology.
Topics
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
Self-Paced Training Info
Learn at your own pace with anytime, anywhere training
- Same in-demand topics as instructor-led public and private classes.
- Standalone learning or supplemental reinforcement.
- e-Learning content varies by course and technology.
- View the Self-Paced version of this outline and what is included in the SPVC course.
- Learn more about e-Learning
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