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

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

Duration: 1.0 day

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Objectives

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

Content

1. Get started with data science in Microsoft Fabric

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.

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2. Explore data for data science with notebooks in Microsoft Fabric

Microsoft Fabric notebooks serve as a comprehensive tool for data exploration, enabling users to uncover hidden patterns and relationships in their datasets.

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3. Preprocess data with Data Wrangler in Microsoft Fabric

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.

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

In Microsoft Fabric, data scientists can train models in notebooks, track their work in experiments, and manage their models with MLflow.

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5. Generate batch predictions using a deployed model in Microsoft Fabric

Save and use your machine learning models in Microsoft Fabric to generate batch predictions and enrich your data.

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Audience

Prerequisites

You should be familiar with basic data concepts and terminology.

Certification

product-certification

Course Benefits

product-benefits
  • Career growth
  • Broad Career opportunities
  • Worldwide recognition from leaders
  • Up-to Date technical skills
  • Popular Certification Badges

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