DP-100 Designing and Implementing a Data Science Solution on Azure

Consume data assets from the designer

Use custom code components in designer

Evaluate the model, including responsible AI guidelines

Use automated machine learning for tabular data

Use automated machine learning for computer vision

Use automated machine learning for natural language processing (NLP)

Evaluate an automated machine learning run, including responsible AI guidelines

Select and understand training options, including preprocessing and algorithms

Develop code by using a compute instance

Track model training by using MLflow

Evaluate a model

Train a model by using Python SDKv2

Use the terminal to configure a compute instance

Select a sampling method

Define the search space

Define the primary metric
1 2 3 4