Welcome to the course!
You’re about to learn some highly valuable knowledge, and mess around with a wide variety of data science and machine learning algorithms right on your own desktop! But first, you need to install some stuff.
1. Get the Course Materials
Download all of the scripts and sample data used in this course from this link:
After downloading, decompress this zip file into a folder in a place you’ll remember. On Windows, you can right-click and select “expand all” after moving the file where you want it to go. Linux users may use the “unzip” command, and on MacOS you may need to install a separate utility to decompress ZIP archives.
If you want a copy of the slides for this course, you’ll find them at http://media.sundog-soft.com/Udemy/DataScienceSlides.pdf .
(We have discontinued our Facebook group due to abuse.)
2. Install Enthought Canopy
This course requires a scientific Python 3 installation that includes Jupyter notebook support. I use Enthought Canopy; here’s how to get set up:
Download and install Enthought Canopy (it’s free) at
Be sure to select the Python 3.5 or newer version.
Open up Canopy, and select the Editor button. Then click in the bottom window panel of the screen where there’s a command prompt, and enter:
!pip install pydotplus
That’s it! To see if it works, try double-clicking one of the .ipynb files included in the course materials, for example outliers.ipynb. If everything is set up properly, your web browser should open up with the course materials for that lecture in it. If you get an error – just try opening the file again; sometimes it takes a few tries before everything is up and running.
Optional: Join Our List
Join our low-frequency mailing list to stay informed on new courses and promotions from Sundog Education. As a thank you, we’ll send you a free course on Deep Learning and Neural Networks with Python, and discounts on all of Sundog Education’s other courses! Just click the button to get started.
Optional: Get the Book
A printed companion book is available from Packt Publishing! It’s a great reference to accompany the course, or a way to follow along when you’re not in front of a computer. Check it out at Amazon.