This comprehensive course equips you with essential skills for implementing data science and machine learning solutions within the Microsoft Fabric ecosystem. Participants will gain extensive hands-on experience managing data assets, working with notebooks, configuring experiments, and developing machine learning models, enabling seamless data integration across your organization and collaborative work with other data professionals. By course completion, you will be proficient in data exploration and discovery, data preparation and preprocessing, model training and validation, and generating actionable predictions, all utilizing the powerful capabilities of the Microsoft Fabric environment.
Throughout the training, you will engage deeply with the complete data science workflow, explore and analyze datasets using interactive notebooks, prepare data efficiently with Data Wrangler tools, and leverage MLflow for comprehensive model management and tracking. This thorough preparation ensures you can confidently develop and deploy machine learning models to extract meaningful insights and enhance your organization's data science capabilities.
Audience Profile:
This course is ideal for data scientists, data analysts, machine learning engineers, and professionals seeking to advance their skills in implementing data science solutions using Microsoft Fabric. It is also well-suited for professionals responsible for data management and organizational integration who want to leverage sophisticated data science tools and methodologies.
Prerequisites:
Familiarity with fundamental data concepts and standard terminology is required before enrollment.
Course Outline:
Module 1: Get Started with Data Science in Microsoft Fabric
- Understand the complete data science process and workflow
- Explore and process data using Microsoft Fabric capabilities
- Train and score models within the Fabric environment
- Exercise: Explore data science in Microsoft Fabric
Module 2: Explore Data for Data Science with Notebooks in Microsoft Fabric
- Understand notebook features and functionality
- Load and prepare data for exploration
- Analyze data distribution and patterns
- Identify and assess missing data in notebooks
- Apply advanced data exploration and discovery techniques
- Create visualizations and charts in notebooks
- Exercise: Use notebook for data exploration in Microsoft Fabric
Module 3: Preprocess Data with Data Wrangler in Microsoft Fabric
- Understand Data Wrangler capabilities and benefits
- Perform comprehensive data exploration
- Address and handle missing data effectively
- Transform data using a variety of operators and techniques
- Exercise: Preprocess data with Data Wrangler in Microsoft Fabric
Module 4: Train and Track Machine Learning Models with MLflow in Microsoft Fabric
- Understand machine learning model training principles
- Train and track models using MLflow and experiment tracking
- Manage and govern models within Microsoft Fabric
- Exercise: Train and track a model in Microsoft Fabric
Module 5: Generate Batch Predictions Using a Deployed Model in Microsoft Fabric
- Customize model behavior for batch scoring applications
- Prepare and validate data before generating predictions
- Generate predictions and save results to a Delta table
- Exercise: Generate and save batch predictions
