DP-100T01: Designing and Implementing a Data Science Solution on Azure in Austin
Intermediate Level
NetCom Learning
Austin, TXX2 Training Center
Plaza 7000, 7000 North Mopac Expressway
Austin, TXX2
Virtual Instructor-Led Training
4 Days (32 Hours)Ideal for those pursuing Azure DP-100 in Austin, Azure certification, or looking to advance through Azure training, this Azure Data Science certification course will prepare you to ace the Microsoft Certified: Azure Data Scientist Associate exam. Upgrade your skills in automating and managing data science models with Azure Machine Learning service.
DP-100 Course Objectives in Austin
- Doing Data Science on Azure
- Doing Data Science with Azure Machine Learning service
- Automate Machine Learning with Azure Machine Learning service
- Manage and Monitor Machine Learning Models with the Azure Machine Learning service
NetCom Learning
Austin, TXX2 Training Center
Plaza 7000, 7000 North Mopac Expressway
Austin, TXX2
Upcoming Schedules
Exam and Certification
Exam
DP-100: Designing and Implementing a Data Science Solution on Azure
Certification
Who should attend Azure Data Science Course in Austin
- Data Scientist
- AI Engineer
Prerequisites for Azure DP-100 Course in Austin
Required
- Creating cloud resources in Microsoft Azure.
- Training and validating machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow.
- Working with containers
Data Science Solution on Azure Course Outline in Austin
Design a machine learning solution
- Design a data ingestion strategy for machine learning projects
- Identify your data source and format
- Choose how to serve data to machine learning workflows
- Design a data ingestion solution
- Design a machine learning model training solution
- Design a solution to get and prepare data.
- Choose a service and compute to train a model.
- Prepare for model deployment options.
- Design a model deployment solution
- Understand how a model will be consumed.
- Decide whether to deploy your model to a real-time or batch endpoint.
- Design a machine learning operations solution
- Explore an MLOps architecture.
- Design for monitoring.
- Design for retraining.
Explore and configure the Azure Machine Learning workspace
Experiment with Azure Machine Learning
Optimize model training with Azure Machine Learning
Manage and review models in Azure Machine Learning
Deploy and consume models with Azure Machine Learning
