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DP-604T00: Implement a data science and machine learning solution for AI with Microsoft Fabric Training

DP-604 teaches you to build data science and machine learning solutions using Microsoft Fabric. You'll learn how to process and analyze data, train predictive models, and deploy them to solve real problems. The course is hands on, so you'll work through the full ML workflow from data to deployment.

📘 Fabric 👥 134 Enrolled ⏱️ 1 Day 💼 Foundation Level ⭐ 5 | 45 Reviews

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| DP-604T00: Implement a data science and machine le

Course Overview

This course covers implementing data science and machine learning workflows in Microsoft Fabric. The focus is on AI model training and deployment. You'll go from processing raw data to building and deploying models that work in production. It's designed for professionals who want practical ML experience, not just theory.

Mode of Training

🏫 Classroom 💻 Live Online 🧪 Blended 👨‍👩‍👧‍👦 Private Group

What you will learn

  • 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

Who Should Attend This Course?

  • Data Scientist
  • Data Analyst
  • Fabric Analytics Engineer

Prerequisites

  • You should be familiar with basic data concepts and terminology.

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📘 DP-604T00: Implement a data science and machine learning solution for AI with Microsoft Fabric Outline

  • Understand the data science process
  • Train models with notebooks in Microsoft Fabric
  • Track model training metrics with MLflow and experiments
  • Lab: Explore data science 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.
  • Lab: Use notebook for data exploration 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.
  • Lab: Preprocess data with Data Wrangler 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
  • Lab: Train and track a 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
  • Lab: Generate and save batch predictions

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