DP-100 Microsoft Azure Data Scientist Complete Exam Prep

A complete course that covers the DP-100 exam

Course curriculum

1. DP-100 Course Welcome
2. Exam Requirements
1. Create an Azure Machine Learning workspace
2. Azure ML Workspace Settings - Portal
3. Azure ML Studio Settings
1. Datastores and Datasets
2. Create Additional Datasets
1. Create an experiment compute instance
2. Manage multiple compute instances
3. Create compute targets and clusters
1. Creating Our First ML Pipeline
2. Submitting the Pipeline for Training and Evaluation
3. Custom Code in a More Complicated Pipeline
4. Explaining the Complicated Pipeline
5. Evaluating the Execution Results
6. Azure ML Designer Errors
7. Azure ML Designer Modules
1. Setup SDK for Azure ML
2. Create ML Workspace using SDK
3. Hello, World in Python
4. Train a Model using SDK
5. Submit Experiment using SDK
1. Create a pipeline by using the SDK
1. Overview of AutoML
2. Using AutoML with SDK
1. What is Hyperparameter?
1. Register a trained model
1. Create production compute targets
1. Deploy AutoML
2. Create an AutoML Endpoint
3. Deploy ML Designer for Real Time Inference
4. Deploy SDK Models
1. Publish a Pipeline for Batch Inference
1. Thank You!