You might have realized that I have been neglecting this newsletter. I apologize, but I have been heads down working on developing a new course for doing data analytics and visualization with Python.
I am really excited about it because I tried to focus on the most important data analytics techniques I use as well as the ones students found most valuable in the machine learning course I taught at University.
Data analysis is one of the hottest careers of the 21st century. As an analyst, your goal is to peel back layers of data in order to answer questions of interest; that is the power of analytics. It allows you to take raw data and create meaningful, actionable insights.
In this course, you’ll learn how to use Python, NumPy, SciPy, Pandas, and Seaborn to perform data analysis and visualization. You’ll explore the four crucial steps for any data analysis project: reading, describing, cleaning, and visualizing data. In each step, you will work with the most common and popular tools that data analysts use every day. By the end of the course, you will be able to confidently extract knowledge and answers from data.
You can sign up for the course on the amazing educative platform here. It allows you to easily learn all the techniques because you can run and edit the code right from your browser with no setup.
I was also able to convince them to give me a discount code! Act quick, though, because it will only work for the first 25 people who use it.
Here is the code:
PYTHON-DATA-20
I truly hope you all enjoy the course and I look forward to any feedback you have!
Thanks,
Tyler