Join Miki Tebeka for an in-depth discussion in this video What you should know, part of Data Science Foundations: Python Scientific Stack.
- [Instructor] To get the most out of this course, you should have a working knowledge of Python, but by no means do you need to be an expert. You should have some familiarity with data processing, and you should be comfortable with the command line. To follow along with this course, you'll need a modern computer with an Internet connection. You can use a Mac, a Linux, or a PC. I'm going to work on a Mac, but everything I demonstrate will work the same on other operating systems. If there are any differences, I'll point them out as we go along.
And you should have about five gigabytes of free disk space.
- Working with Jupyter notebooks
- Using code cells
- Extensions to the Python language
- Markdown cells
- Editing notebooks
- NumPy basics
- Broadcasting, array operations, and ufuncs
- Folium and Geo
- Machine learning with scikit-learn
- Plotting with matplotlib and bokeh
- Branching into Numba, Cython, deep learning, and NLP
Skill Level Intermediate
Python: Data Analysis (2015)with Michele Vallisneri2h 16m Intermediate
NumPy Data Science Essential Trainingwith Charles Kelly3h 54m Intermediate
1. Scientific Python Overview
2. The Jupyter Notebook
3. NumPy Basics
Manage environments5m 11s
6. Folium and Geo
7. NY Taxi Data
10. Other Packages
11. Development Process
Next steps1m 33s
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