- Office hours
- Stack Overflow
- RealPython
- FreeCodeCamp
- Crash Course Computer Science
- Data Analysis with Python for Excel Users
- Python for MBAs "and those in business roles that include coding or working with coding teams"
- IBM Data Analyst Course - can jump to specific parts
- Full Stack Python
- GitHub Student Developer Pack
- Includes learning resources and various tools
{% if id == "columbia" -%}
- Python at Columbia Business School self-paced course with videos, open to anyone at Columbia
- Foundations for Research Computing
- Data Science Institute
- Library
{% else -%}
- Wagner Quantitative Support
- Tutoring
- Math Review
- NYU Library Data Services
- Consultation
- Classes
- The Coding Lab
{% endif -%}
There are countless other blog posts, videos, books, etc. out there. There is no "best" resource, as individuals prefer different formats, come in with different experience, and learn at different speeds. Anything that comes up near the top of a Google search will likely be fine.
Want to keep going after this class?
Recommended focusing on fundamentals of Python 3. Many "learn Python" resources will be web development-oriented (they will probably mention Django/Flask), so you might want to look for ones that focus on data science or Python 3 on its own. Some that are data-oriented:
- freeCodeCamp's Scientific Computing with Python class
- DataCamp's Python Fundamentals or Python Programmer tracks
Countless other "learn Python" resources/courses/videos/books out there; there isn't one right choice for everyone.
{% if school_slug == "columbia" -%}
{% else -%}
- Wagner
- Center for Data Science
- Center for Urban Science + Progress (CUSP)
- Applied Data Science
- Machine Learning for Cities
{% endif -%}
We use a cloud-based Jupyter environment ({{coding_env_name}}) for this course to avoid installation issues across student computers. This is the only environment that's supported for course work.
{% if id == "columbia" -%} Some additional options for running Jupyter: {% else -%} After this class, however, you'll no longer have access. To download the files:
- Open a notebook
- In a code cell, run
!tar -czvf ~/python_files.tar.gz ~
- From the file browser, check the box next to
python_files.tar.gz
, then clickDownload
- On your computer, unzip the file.
- On Windows, you may need to install 7-Zip to do so.
Some options for running Jupyter on your own:
- Google Colab {% endif -%}
- Anaconda
- Visual Studio Code
Advanced
Note these instructions won't work in Colab.
-
Install Mamba.
-
Check out the
{{school_slug}}
branch. -
Create the environment. From this directory, run:
mamba env create --file extras/environment.lock.yml
-
Activate the environment:
conda activate python-public-policy
-
Start the Jupyter server:
./extras/scripts/start.sh