DP-100 Designing and Implementing a Data Science Solution on Azure
Czas trwania kursu: 3 dni
Cena: 2399 zł netto
CERTYFIKACJE ZAWODOWE
| Certyfikacja podstawowa |
CertyfIkacja specjalistyczna |
Certyfikacja ekspercka |
| FUNDAMENTALS |
ASSOCIATE |
EXPERT |
POZIOM SZKOLENIA
| podstawowy |
średniozaawansowany |
zaawansowany |
ekspercki |
| 100 |
200 |
300 |
400 |
TEMATYKA ZAJĘĆ
- Module 1: Getting Started with Azure Machine Learning
Introduction to Azure Machine Learning
Working with Azure Machine Learning
Lab: Create an Azure Machine Learning Workspace
- Module 2: Visual Tools for Machine Learning
Automated Machine Learning
Azure Machine Learning Designer
Lab: Use Automated Machine Learning
Lab: Use Azure Machine Learning Designer
- Module 3: Running Experiments and Training Models
Introduction to Experiments
Training and Registering Models
Lab: Train Models
Lab: Run Experiments
- Module 4: Working with Data
Working with Datastores
Working with Datasets
Lab: Work with Data
- Module 5: Working with Compute
Working with Environments
Working with Compute Targets
Lab: Work with Compute
- Module 6: Orchestrating Operations with Pipelines
Introduction to Pipelines
Publishing and Running Pipelines
Lab: Create a Pipeline
- Module 7: Deploying and Consuming Models
Real-time Inferencing
Batch Inferencing
Continuous Integration and Delivery
Lab: Create a Real-time Inferencing Service
Lab: Create a Batch Inferencing Service
- Module 8: Training Optimal Models
Hyperparameter Tuning
Automated Machine Learning
Lab: Use Automated Machine Learning from the SDK
Lab: Tune Hyperparameters
- Module 9: Responsible Machine Learning
Differential Privacy
Model Interpretability
Fairness
Lab: Explore Differential provacy
Lab: Interpret Models
Lab: Detect and Mitigate Unfairness
- Module 10: Monitoring Models
Monitoring Models with Application Insights
Monitoring Data Drift
Lab: Monitor Data Drift
Lab: Monitor a Model with Application Insights