Implement a data science and machine learning solution for AI in Microsoft Fabric

Overview

Module 1: Get started with data science in Microsoft Fabric by learning how to train a model in a notebook, and track your metrics with MLflow and experiments.
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
Module 2: Discover how to perform data exploration for data science using Microsoft Fabric notebooks.
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.
Module 3: Explore the process of preparing data for machine learning models using the Data Wrangler tool in Microsoft Fabric notebooks.
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.
Module 4: Learn how to train machine learning models in notebooks and track your work with MLflow experiments in Microsoft Fabric.
In this module, you'll learn how to:
- 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

Syllabus

Module 1: Module 1: Get started with data science in Microsoft Fabric
- Introduction
- Understand the data science process
- Explore and process data with Microsoft Fabric
- Train and score models with Microsoft Fabric
- Exercise - Explore data science in Microsoft Fabric
- Knowledge check
- Summary
Module 2: Module 2: Explore data for data science with notebooks in Microsoft Fabric
- Introduction
- Explore notebooks
- Load data for exploration
- Understand data distribution
- Check for missing data in notebooks
- Apply advanced data exploration techniques
- Visualize charts in notebooks
- Exercise: Use notebook for data exploration in Microsoft Fabric
- Knowledge check
- Summary
Module 3: Module 3: Preprocess data with Data Wrangler in Microsoft Fabric
- Introduction
- Understand Data Wrangler
- Perform data exploration
- Handle missing data
- Transform data with operators
- Exercise: Preprocess data with Data Wrangler in Microsoft Fabric
- Knowledge check
- Summary
Module 4: Module 4: Train and track machine learning models with MLflow in Microsoft Fabric
- Introduction
- Understand how to train machine learning models
- Train and track models with MLflow and experiments
- Manage models in Microsoft Fabric
- Exercise - Train and track a model in Microsoft Fabric
- Knowledge check
- Summary