DP-604T00: Implement a Data Science and Machine Learning Solution for AI with Microsoft Fabric
Explore practical machine learning in Microsoft Fabric. Learn how to explore, clean, train, track, and deploy ML models for predictive analytics. The course emphasizes Fabric's native tools like Data Wrangler for preprocessing and MLflow for robust model management, preparing you to generate and save production-ready batch predictions.
This course is specifically designed for individuals involved in the practical application of machine learning and data science within an enterprise analytics environment.
- Data Scientists: Professionals who need to leverage Microsoft Fabric's integrated tools (Notebooks, MLflow, Data Wrangler) to perform the complete data science lifecycle, from data exploration to model deployment.
- Machine Learning Engineers: Individuals responsible for training, tracking, managing, and deploying ML models for batch scoring and prediction generation.
- Data Analysts transitioning to Data Science: Professionals seeking to build skills in data preparation, exploratory data analysis (EDA), and machine learning using Python notebooks and Fabric's specialized tools.
- BI Developers/Architects interested in integrating ML models and predictive analytics directly into the Microsoft Fabric ecosystem.
Upon completing the course, participants should be able to:
- Navigate the Data Science Process: Understand and initiate data science projects within the integrated Microsoft Fabric environment.
- Prepare and Explore Data: Utilize Notebooks for advanced data exploration (handling missing data, visualizing charts) and employ Data Wrangler for efficient data preprocessing, cleaning, and feature transformation.
- Develop and Track Models: Train machine learning models and use MLflow and Fabric Experiments to effectively track, manage, and register the models developed.
- Deploy for Prediction: Customize and deploy trained models to generate batch predictions (batch scoring) and save the enriched data directly to a Delta table within Microsoft Fabric.
Module 01: Introduction to end-to-end analytics using Microsoft Fabric
Discover how Microsoft Fabric can meet your enterprise's analytics needs in one platform. Learn about Microsoft Fabric, how it works, and identify how you can use it for your analytics needs.
Topics Covered
- Explore end-to-end analytics with Microsoft Fabric
- Explore data teams and Microsoft Fabric
- Enable and use Microsoft Fabric
- Module assessment
Module 02: 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.
Topics Covered
- 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
- Module assessment
Module 03: 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.
Topics Covered
- 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
- Module assessment
Module 04: 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.
Topics Covered
- Understand Data Wrangler
- Perform data exploration
- Handle missing data
- Transform data with operators
- Exercise: Preprocess data with Data Wrangler in Microsoft Fabric
- Module assessment
Module 05: 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.
Topics Covered
- 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
- Module assessment
Module 06: 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.
Topics Covered
- Customize the model's behavior for batch scoring
- Prepare data before generating predictions
- Generate and save predictions to a Delta table
- Exercise: Generate and save batch predictions
- Module assessment
