By Romeo Radanyi
There is so much data out there, just waiting to be analyzed, but have you ever wondered how much easier it could be to interpret if you just had a way to visualize these datasets in an interactive way? If only there was a tool that could help us import a data set, transform it, perform calculations, analyze and visualize it, then document these processes and steps along the way so it can be shared with others. Well, that is exactly what Jupyter Notebook will allow you to do.
In this course, you’ll learn:
- How to set up and use Jupyter Notebooks.
- What data analytics and visualization is, its importance and how it can be harnessed.
- How to take a real dataset and turn it into charts, graphs, interactive elements, predictions, etc.
- How to start leveraging Machine Learning techniques to get even more from your data.
- How to harness cloud service providers like AWS, Google, Azure’s hosted notebook services in your data science and machine learning lifecycles
This course is made for beginners, so if you don’t know anything about data science or machine learning but you’re interested in getting started, you are definitely in the right place. Some Python experience is beneficial but not necessarily required. If you can understand basic coding, you will get along just fine.
Come along and learn all about data science, machine learning, and how to do all kinds of amazing things that look and sound like magic to most developers!
