Online learning from an accredited institution
DP-100: Azure Data Scientist Associate
Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches
you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation,
model training and deployment, and machine learning solution monitoring with Azure Machine Learning and MLflow
4 Day Instructor-Led
Prerequisites:
As a candidate for this certification, you should have subject matter expertise in applying data science and machine learning to implement and run machine learning workloads on Azure. Additionally, you should have knowledge of optimizing language models for AI applications using Azure AI.
Specifically:
• Azure Machine Learning
• MLflow
• Azure AI services, including Azure AI Search
• Azure AI Foundry
Course Outline
Module 1: Explore and Configure the Azure Machine Learning Workspace
• Explore Azure Machine Learning workspace resources and assets
• Explore developer tools for workspace interaction
• Make data available in Azure Machine Learning
• Work with compute targets in Azure Machine Learning
• Work with environments in Azure Machine Learning
Module 2: Experiment with Azure Machine Learning
• Find the best classification model with Automated Machine Learning
• Track model training in Jupyter notebooks with MLflow
Module 3: Optimize Model Training with Azure Machine Learning
• Run a training script as a command job in Azure Machine Learning
• Track model training with MLflow in jobs
• Perform hyperparameter tuning with Azure Machine Learning
• Run pipelines in Azure Machine Learning
Module 4: Manage and Review Models in Azure Machine Learning
• Register an MLflow model in Azure Machine Learning
• Create and explore the Responsible AI dashboard for a model in Azure Machine Learning
Module 5: Deploy and Consume Models with Azure
Machine Learning
• Deploy a model to a managed online endpoint
• Deploy a model to a batch endpoint
Module 6: Deploy and Consume Models with Azure
Machine Learning
• Plan and prepare to develop AI solutions on Azure
• Choose and deploy models from the model catalog in Azure AI Foundry portal
• Develop an AI app with the Azure AI Foundry SDK
• Get started with prompt flow to develop language model apps in the Azure AI Foundry
• Develop a RAG-based solution with your own data using Azure AI Foundry
• Fine-tune a language model with Azure AI Foundry
• Implement a responsible generative AI solution in Azure AI Foundry
• Evaluate generative AI performance in Azure AI Foundry portal