Learn how to log and register an MLflow model in Azure Machine Learning.

Mimic experiments with the data you already have and measure the effects of treatment even with incomplete data.

A crash course on making ML software more reliable, including best practices on testing and other aspects of defensive programming.

R Markdown is an easy-to-use formatting language for authoring dynamic reports from R code.

This course covers the different data processing tools - including spreadsheets, Python, and relational databases - and deals with data quality issues and visualizing data for insight generation.

Reshape DataFrames from a wide to long format, stack and unstack rows and columns, and wrangle multi-index DataFrames.

Reshaping data is an important step in data management and organization. Statistical methods or data visualization techniques require data to be either wide or long. This course focuses on how to reshape data into wide and long formats using R.

This course equips you with tools to develop responsible AI systems that are fair, transparent, accountable, and beneficial to society as a whole.

This course targets the Business Intelligence (BI) Self Service professional who needs to obtain and shape data from multiple and various sources so that the data can provide useful BI to report viewers. The focus of this course is Power Query.

Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions.

Learn how to convert your code to a script and run it as a command job in Azure Machine Learning.

Learn how to create and use components to build pipeline in Azure Machine Learning. Run and schedule Azure Machine Learning pipelines to automate machine learning workflows.