Implement a Data Science and Machine Learning Solution for AI with Microsoft Fabric (DP-604T00)

This training dives into how data science and machine learning work in the Microsoft Fabric system. It shows students how to train models with notebooks, track progress with MLflow, and understand data with Data Wrangler. The course includes lab sessions for hands-on practice in data preparation, model training, and making batch predictions. DP-604 training helps students get better at setting up and applying machine learning for AI tasks using Microsoft Fabric's data science tools.

Course Information

Price: $695.00
Duration: 1 day
Certification: 
Exam: 
Learning Credits:
Continuing Education Credits:
Course Delivery Options

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Prerequisites:

 

Target Audience:

  • Data Scientist
  • Data Analyst
  • Data Engineer

 

Course Objectives:

  • 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

 

Course Outline:

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
  • Lab Explore data science in Microsoft Fabric

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
  • Lab Use notebook for data exploration in Microsoft Fabric

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 onehot 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 and track machine learning models with MLflow in Microsoft Fabric

  • Train machine learning models with opensource 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

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
  • Lab Generate and save batch predictions

 

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