Azure Training Overview
This Microsoft official course (DP-100), Designing and Implementing a Data Science Solution on Azure training, teaches data scientists with existing knowledge of Python how to leverage Python and Machine Learning (ML) to manage data ingestion and preparation, model training and deployment, and monitor an ML solution with Azure ML and MLflow. This course prepares students for the DP-100 exam for which every attendee receives a voucher.
Location and Pricing
Accelebrate offers instructor-led enterprise training for groups of 3 or more online or at your site. Most Accelebrate classes can be flexibly scheduled for your group, including delivery in half-day segments across a week or set of weeks. To receive a customized proposal and price quote for private corporate training on-site or online, please contact us.
In addition, some courses are available as live, instructor-led training from one of our partners.
Objectives
- Operate machine learning solutions at cloud scale using Azure Machine Learning
- Manage data ingestion and preparation
- Model training and deployment
- Implement a machine learning solution in Microsoft Azure
Prerequisites
Before attending this course, students must have:
- Fundamental knowledge of cloud computing concepts and experience in general data science and Machine Learning tools and techniques, including:
- Creating cloud resources in Microsoft Azure
- Using Python to explore and visualize data
- Training and validating machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow
- Working with containers
- To gain these prerequisite skills, participants can take these short, self-paced, free online courses from Microsoft:
- Taken AZ-900: Azure fundamentals or have equivalent knowledge.
Outline
Introduction
Design a data ingestion strategy for machine learning projects
Design a machine learning model training solution
Design a model deployment solution
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
Find the best classification model with Automated Machine Learning
Track model training in Jupyter notebooks with MLflow
Run a training script as a command job in Azure Machine Learning
Track model training with MLflow in jobs
Run pipelines in Azure Machine Learning
Perform hyperparameter tuning with Azure Machine Learning
Deploy a model to a managed online endpoint
Deploy a model to a batch endpoint
Conclusion
Training Materials
All Microsoft Azure training students receive Microsoft official courseware.
For all Microsoft Official Courses taught in their entirety that have a corresponding certification exam, an exam
voucher is included for each participant.
Software Requirements
Attendees will not need to install any software on their computer for this class. The class will be conducted in a remote environment that Accelebrate will provide; students will only need a local computer with a web browser and a stable Internet connection. Any recent version of Microsoft Edge, Mozilla Firefox, or Google Chrome will be fine.
