DP-604T00: Implement a data science and machine learning solution for AI in Microsoft Fabric
Implement Data Science and Machine Learning with Microsoft Fabric: Build Smarter Solutions.
Discover how to implement advanced data science and machine learning models using Microsoft Fabric. This Microsoft Applied Skills credential is designed for data scientists and AI professionals who want to create scalable solutions for real-world applications. Learn to use Microsoft Fabric’s powerful tools to train models, manage data pipelines, and deploy machine learning workflows efficiently.
Whether you’re predicting trends or optimizing business processes, this course provides the skills you need to harness AI for impactful results.
DP-604T00: Implement a data science and machine learning solution for AI in Microsoft Fabric
Implement Data Science and Machine Learning with Microsoft Fabric: Build Smarter Solutions.
Discover how to implement advanced data science and machine learning models using Microsoft Fabric. This Microsoft Applied Skills credential is designed for data scientists and AI professionals who want to create scalable solutions for real-world applications. Learn to use Microsoft Fabric’s powerful tools to train models, manage data pipelines, and deploy machine learning workflows efficiently.
Whether you’re predicting trends or optimizing business processes, this course provides the skills you need to harness AI for impactful results.
In Microsoft Fabric, data scientists can manage data, notebooks, experiments, and models while easily accessing data from across the organization and collaborating with their fellow data professionals.
Learning objectives
In this module, you’ll learn how to:
Understand the data science process
Train models with notebooks in Microsoft Fabric
Track model training metrics with MLflow and experiments
Prerequisites
Before starting this module, you should be familiar with the basic principles of machine learning.
Microsoft Fabric notebooks serve as a comprehensive tool for data exploration, enabling users to uncover hidden patterns and relationships in their datasets.
Learning objectives
In this module, you’ll:
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.
Prerequisites
Before starting this module, you should be familiar with the basic principles of machine learning.
Data Wrangler serves as a comprehensive tool for preprocessing data. It enables users to clean data, handle missing values, and transform features to build machine learning models.
Learning objectives
In this module, you’ll:
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.
Prerequisites
Before starting this module, you should be familiar with the basic principles of machine learning.
To earn this Microsoft Applied Skills credential, learners demonstrate the ability to implement a data science solution by using Microsoft Fabric, including:
Ingesting, loading, exploring, and preparing data
Training, tracking, and scoring a model
Candidates for this credential should be familiar with data science and AI fundamentals, in addition to open-source frameworks, such as scikit-learn and SynapseML. They should also have experience with:
