- Learning Path Libraries: This path is only available in the libraries listed. To access this path, purchase a license for the corresponding library.
- AI
- Cloud
- Data
Implementing the Data Science Workflow in Microsoft Azure
Microsoft Azure contains a massive offering of services that can be used together to implement the data science workflow. This path walks you through this workflow, as it is implemented in Microsoft Azure.
Content in this path
Beginner
In this section of the path, learners will work through data sourcing and preparation. In addition, the features of Microsoft Azure that help with data exploration are highlighted.
Intermediate
These courses will inform learners on selecting and extracting features using Microsoft Azure services, then building models that consume those features and evaluating their validity.
Advanced
In this final segment of the path, learners will deploy and manage their models in the Microsoft Azure platform, and learn how to use features of the platform to communicate data insights with others.
- Source, clean, and prepare data using Microsoft Azure
- Implement feature selection using Microsoft Azure
- Build models and evaluate their effectiveness in Microsoft Azure
- Use Microsoft Azure services to deploy and manage your model
- Communicate results to the business using the Microsoft Azure platform
- This path is intended for experienced data scientists interested in understanding how their everyday workflows are enabled by Microsoft Azure. It is expected that the learner understand basic data science principles, such as data munging and cleaning, model selection and implementation, and data communication.
- Data Science
- Microsoft Azure
- Python Programming
- Jupyter Notebooks
- Machine Learning
- Statistics
- Data Communication
Learn with the best
