DP-604T00: Implement a Data Science and Machine Learning Solution for AI with Microsoft Fabric is an instructor-led course designed for data scientists and AI professionals looking to build and operationalize machine learning solutions using the Microsoft Fabric platform. This course provides in-depth knowledge of how to explore, prepare, model, and deploy AI solutions using Fabric Data Science experiences, Lakehouse architecture, and Apache Spark environments.
Participants will gain hands-on experience in using Notebooks, ML models, and AutoML in Fabric to streamline machine learning workflows and integrate predictive insights into business applications. The course also explores how to collaborate with other roles in a unified platform, monitor model performance, and ensure scalability and governance in AI projects.
- Explore data using Microsoft Fabric’s Data Science and Lakehouse environments
- Build and train machine learning models using Notebooks and Apache Spark
- Leverage AutoML and custom models for advanced AI solutions
- Deploy, monitor, and manage models within Microsoft Fabric
- Collaborate across roles and integrate AI into real-world applications
This course is ideal for:
- Data Scientists
- AI Engineers
- Machine Learning Specialists
- Professionals interested in operationalizing AI with cloud-scale infrastructure
Before attending this course, learners should have:
- A basic understanding of machine learning principles
- Familiarity with Python and data science tools
- Experience with cloud platforms or data analytics is a plus
- Lesson: Describe end-to-end analytics in Microsoft Fabric
- Lesson: Understand data teams and roles that use Fabric
- Lesson: Describe how to enable and use Fabric
- Lesson: Explore common machine learning models
- Lesson: Understand the data science process
- Demo: Get started with data science in Microsoft Fabric
- Lesson: Understand data distribution
- Lesson: Explore patterns and relationships in the data
- Demo: Explore data for data science with notebooks in Microsoft Fabric
- Lesson: Work with Data Wrangler
- Lesson: Handling missing data
- Lesson: Use one-hot encoding operator
- Lesson: Use min-max scaling operator
- Exercise: Preprocess data with Data Wrangler in Microsoft Fabric
- Lesson: Train a model
- Exercise: Train and track machine learning models with MLflow in Microsoft Fabric
- Lesson: Customize the model's behavior for batch scoring
- Exercise: Generate batch predictions using a deployed model in Microsoft Fabric
This course is ideal for data scientists, machine learning engineers, and AI professionals who want to build and operationalize machine learning solutions using Microsoft Fabric’s integrated data science and analytics capabilities.
Learners should have a basic understanding of machine learning concepts, experience with Python, and familiarity with data science workflows. Prior knowledge of cloud platforms and big data processing is helpful but not mandatory.
You will work with Microsoft Fabric’s Data Science experiences, including Lakehouse, Notebooks, Apache Spark, and AutoML to build, train, and deploy machine learning models.
Yes, this course is highly practical and includes hands-on labs where you will explore data, build models, automate workflows, and deploy AI solutions within the Fabric environment.
Absolutely. The course is designed around real-world scenarios, helping you build scalable, secure, and collaborative AI solutions that can be integrated into business applications and production pipelines.
