Training Overview
Disclaimer: This course is independently developed and not affiliated with Microsoft. It covers concepts and skills that closely align with the objectives of Microsoft’s DP-604T00: Implement a data science and machine learning solution for AI with Microsoft Fabric training, making it a strong preparatory or complementary learning experience.
Design and Deploy Data Science & ML Workflows for AI in Microsoft Fabric
This One-Day intermediate-level custom training equips participants with practical skills to build and operationalize a data science and machine learning solution using Microsoft Fabric. Learners will ingest, explore, and prepare data using Fabric-native tools; train, track, and deploy machine learning models with MLflow; generate batch predictions from deployed models; and demonstrate their proficiency through a hands-on, lab-based assessment.
Before enrolling in this custom training, participants should ideally be data engineers, analysts, or scientists familiar with Python, MLflow, and open-source machine learning frameworks such as scikit-learn and SynapseML.
Module Breakdown:
Introduction to End-to-End Analytics Using Microsoft Fabric: Understand the architecture and capabilities of Microsoft Fabric for unified analytics workflows.
Get Started with Data Science in Microsoft Fabric: Learn how to set up your environment and navigate Fabric’s data science tools.
Explore Data for Data Science with Notebooks: Use notebooks to inspect, visualize, and understand your data before modeling.
Preprocess Data with Data Wrangler: Clean, transform, and prepare datasets using the intuitive Data Wrangler interface.
Train and Track Machine Learning Models with MLflow: Build models, log experiments, and manage model lifecycle using MLflow in Fabric.
Generate Batch Predictions Using a Deployed Model: Deploy trained models and automate batch scoring workflows for real-world use cases.