Learn how to create an end-to-end data science solution, applying advanced machine learning (ML) approaches to a real-world scenario, variants of which can be found across industry verticals. This crash course in python covers various important machine learning algorithms. You will be using Azure Notebooks to understand the math behind data science and learn best practices for cleansing and manipulating your data to gather insights from it.

You will learn how to do the following:

1. Perform Data Preparation and Feature Engineering with Pandas dataframes

2. Conduct Model Development with the Scikit-Learn ML library

3. Learn essentials of Machine Learning Experimentation (Model Management and Evaluation) with AML service

4. Perform tuning of hyperparameters with HyperDrive on AML Compute

5. Quickly find the best combination of ML algorithm and feature selection with Automated Machine Learning

6. Set up real-time scoring with Azure Kubernetes Services (AKS)