DP 100 Data Science Solution on Azure

1. Create an Azure Machine Learning workspace
2. Manage data in an Azure Machine Learning workspace
3. Manage compute for experiments in Azure Machine Learning
4. Implement security and access control in Azure Machine Learning
5. Set up an Azure Machine Learning development environment
6. Set up an Azure Databricks workspace
7. Create models by using the Azure Machine Learning designer
8. Run model training scripts
9. Generate metrics from an experiment run
10. Use Automated Machine Learning to create optimal models
11. Tune hyperparameters with Azure Machine Learning
12. Select compute for model deployment
13. Deploy a model as a service
14. Manage models in Azure Machine Learning
15. Create an Azure Machine Learning pipeline for batch inferencing
16. Publish an Azure Machine Learning designer pipeline as a web service
17. Implement pipelines by using the Azure Machine Learning SDK
18. Apply ML Ops practices
19. Use model explainers to interpret models
20. Describe fairness considerations for models
21. Describe privacy considerations for data

1. Knowledge of Azure platform.

2. Knowledge of Machine learning concepts.

Our Trainers have years of real-time experience implementing Data Science solutions on Azure.
They share their work experience in various domains to help students gain a perspective on the application.

After the completion of the course and the exam, you will be awarded with the course completion certificate.

24 hours