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Microsoft Certified: Designing and Implementing a Data Science Solution on Azure (DP-100)
This learning path is for data scientists and machine learning practitioners who need to build, train, and deploy ML models on Azure. Learners will gain hands-on skills with Azure Machine Learning, including experiment management, model training, operationalization, and monitoring to prepare for the DP-100 certification.
This learning path is actively in production. More content will be added to this page as it gets published and becomes available in the library. Planned content includes:
- Design and Prepare a Machine Learning Solution (video course) - Provision and Configure a Complete Azure ML Workspace (hands-on lab) - Register and Share a Dataset and Environment (hands-on lab)
- Explore Data, and Run Experiments (video course) - Run a Quick Experiment with AutoML (hands-on lab) - Submit a Custom Training Script Experiment (hands-on lab)
- Train and Deploy Models (video course) - Deploy a Model as a Real-Time Endpoint (hands-on lab) - Monitor and Automate a Model Pipeline (hands-on lab)
- Optimize Language Models for AI Applications (video course) - Evaluate Model Interpretability with SHAP (hands-on lab) - Assess Fairness and Mitigate Bias (hands-on lab)
Content in this path
Path Courses & Labs
This path is designed to help you prepare for the DP-100 exam and strengthen your skills in building, training, optimizing, and deploying machine learning models using Azure Machine Learning. Throughout the learning path, we’ll explore the key Azure services and ML workflows you need to know for the exam, show you how to apply these capabilities in real-world environments, and give you the opportunity to practice each skill through guided, hands-on lab scenarios.
Try this certification path for free
Build confidence to ace your certification exam with a variety of prep tools, including video courses, labs, and practice exams.
What You'll Learn
- How to design and prepare a machine learning solution
- How to explore data, and run experiments
- How to train and deploy models
- How to optimize language models for AI applications
- As a candidate for this exam, you should have knowledge and experience in data science by using:
- Azure Machine Learning
- MLflow
- Azure AI services, including Azure AI Search
- Microsoft Foundry
- Microsoft Foundry
- Azure Machine Learning
- MLflow
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