The course Real-Time Analytics with Apache Storm on Udacity covers various topics related to Apache Storm and real-time analytics. The course starts with basic Storm topologies and teaches how to create links between spouts and bolts. It also demonstrates how to connect to the live Twitter API to process real-time tweets. The course then explores open source components and shows how to visualize rolling top tweeted words using a rolling count bolt. Moving beyond the basics, the course delves into multi-language capabilities and demonstrates how to download and parse real-time tweeted URLs using Python and Beautiful Soup. It also covers the integration of complex open source bolts to calculate top-N words and visualize real-time top-N hashtags. The course introduces stream grouping concepts to create streaming joins and dynamically process multiple streams. The final project of the course involves designing a Storm topology and a new bolt that uses streaming joins to calculate top-N hashtags and display real-time tweets containing trending top hashtags. Participants are encouraged to post their visualizations to the forum and share them with their Twitter followers. The course also offers project extensions, allowing participants to explore additional features of the real-time Twitter sample stream or any other data source to drive their real-time d3 visualizations. Additionally, participants can further explore tools like Vagrant, VirtualBox, Redis, Flask, and d3 if they are interested.