Now that you are familiar with the fundamentals of Supervised Machine Learning, you can move on to more advanced topics in machine learning, we suggest the following MOOC:

Massive Online Open Course:  AI skills: Introduction to Unsupervised, Deep and Reinforcement Learning

In this course you will learn the basics of several machine learning topics to help you solve real life challenges. Unsupervised learning techniques such as clustering and dimensionality reduction are useful to make sense of large and/or high dimensional datasets that are not annotated. Deep learning is a supervised learning technique that is useful to train neural networks to solve more complicated classification and regression tasks. Finally, reinforcement learning techniques can be used to train AI agents that interact with an environment. More information.

Other courses that you may be interested in are:

Data Creation and Collection for Artificial Intelligence via Crowdsourcing

A one-stop shop to get started on the key considerations about data for AI! Learn how crowdsourcing offers a viable means to leverage human intelligence at scale for data creation, enrichment and interpretation, demonstrating a great potential to improve both the performance of AI systems and their trustworthiness and increase the adoption of AI in general. Starts Aug 29.

AI Skills for Engineers: Data Engineering and Data Pipelines

Good data is central to effective AI applications. This course teaches the basics of data for AI, covering what data is needed, how to extract data from existing databases and basic data skills including setup of a Python notebook environment, basic data exploration and simple data visualizations.