Why Choose This Microsoft Fabric Data Science and ML Course?

Many learners approach data science and machine learning by studying algorithms, notebooks, or Python libraries individually. That helps with foundational knowledge, but it does not fully prepare you for implementing machine learning workflows in a platform environment.

Modern data science work is not just about training a model. It involves:

exploring and understanding data quality
cleaning and transforming datasets
experimenting with models and tracking results
managing model versions
deploying trained models and using them for predictions

This course is structured around that real-world flow.

Instead of focusing only on machine learning theory, it helps you understand how to apply data science in Microsoft Fabric using the tools built for experimentation, preprocessing, model management, and prediction workflows. You begin thinking in terms of practical machine learning pipelines, not just isolated notebooks or algorithms.

DP-604T00 Skills You Will Learn

As you progress through this Microsoft Fabric training, you will develop practical skills across the full data science workflow.

You will learn how to:

Understand the end-to-end data science process in Microsoft Fabric
Explore and analyze datasets using notebooks
Work with data distributions, missing values, and visualizations
Preprocess and transform data using Data Wrangler
Prepare features for machine learning models
Train machine learning models in Microsoft Fabric notebooks
Track experiments and training metrics using MLflow
Manage trained models within Microsoft Fabric
Deploy models and generate batch predictions
Save predictions and enrich data using Delta tables

DP-604T00 Syllabus and Course Modules

This course is structured to reflect the way machine learning solutions are built in real-world data science environments using Microsoft Fabric.

Introduction to End-to-End Analytics Using Microsoft Fabric
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

Microsoft Fabric Tools You'll Use During This Course

This course helps you build practical skills in:

Data science workflows in Microsoft Fabric
Exploratory data analysis with notebooks
Data preprocessing with Data Wrangler
Machine learning model training in notebooks
Experiment tracking and model management with MLflow
Batch prediction workflows in Microsoft Fabric
Delta table integration for storing prediction results

DP-604T00 Prerequisites

Before starting this course, it is recommended that you have:

familiarity with basic data concepts and terminology
basic understanding of the data science process
some exposure to Python and notebook-based workflows
general awareness of machine learning concepts such as training, evaluation, and prediction

This course is suitable for learners who want to build practical machine learning skills in Microsoft Fabric, but having foundational data and machine learning knowledge will help you get more value from the hands-on modules.

Who Should Take the DP-604T00 Course?

This course is ideal for professionals who want to build practical data science and machine learning skills using Microsoft Fabric.

It is especially useful for:

Data Scientists who want to work with Microsoft Fabric for model development and experimentation
Data Analysts who want to expand into machine learning workflows
Data Engineers interested in supporting data science pipelines in Fabric
AI and analytics professionals who want to understand end-to-end machine learning implementation in a unified platform
Microsoft Fabric learners who want to explore the data science and AI side of the platform

What You'll Achieve After Completing DP-604T00

This course is not just about understanding machine learning concepts. It is about learning how to implement those concepts in a platform that supports data ingestion, exploration, preprocessing, experimentation, model tracking, and prediction workflows in one place.

By completing this course, you will be able to:

move from theory to hands-on machine learning implementation
understand how data science workflows fit into Microsoft Fabric
build more confidence working with notebooks, MLflow, and Data Wrangler
structure machine learning tasks more effectively from raw data to prediction output
apply Fabric-based machine learning skills in real analytics and AI projects

Benefits of Learning Microsoft Fabric Data Science

By taking this course, you will be able to:

gain practical experience with Microsoft Fabric for data science and machine learning
understand the complete machine learning lifecycle inside a modern analytics platform
improve your ability to clean, prepare, and transform data for modeling
learn how to track experiments and manage models more effectively
build confidence in deploying trained models for batch prediction scenarios
strengthen your skills for real-world AI and analytics projects using Microsoft Fabric

Why Microsoft Fabric Data Science Skills Matter

Organizations are increasingly looking for ways to bring analytics, data engineering, and machine learning together in a single platform. Microsoft Fabric supports that shift by giving data teams a unified environment for data preparation, experimentation, model management, and prediction workflows.

That means professionals who can work with data science and machine learning inside Microsoft Fabric are becoming more valuable.

These skills are useful for building:

predictive analytics solutions
machine learning pipelines
batch scoring workflows
AI-driven reporting and enrichment processes
collaborative data science projects within enterprise analytics platforms

If you want to move beyond traditional analytics and start building practical machine learning solutions in Microsoft Fabric, this course provides a strong starting point.