Python is one of the most popular and in-demand programming languages. In recent years it has become increasingly popular at universities as many researchers - faculty and students alike - use it for a wide variety of tasks from quantitative data analysis to text analysis, data visualization, machine learning, and more.
Visit the complete guide for suggested installation instructions.
It also serves as a supplemental resource for the Python training opportunities we offer to faculty, staff, postdocs, and students. For more on those opportunities, see below.
The Reproducible Research Team offers regular workshops on Python (as well as on variety of other computational skills that can help your research). Visit our workshop page at: http://dartgo.org/RRADworkshops to see a list of upcoming workshops. Many of these workshops are offered online, so you can attend remotely as long as you are a member of the Dartmouth community.
Some examples of workshops we have or will be offering with Python include:
1. Computational Text Analysis (from the basics of text analysis to employing Large Language Models to summarize texts, Winterim 2023-24)
2. Intro to Python Series (The Basics, Dataframes, Visualization, and Text Analysis, Spring 2023)
3. Text Analysis with Python Series (Winter 2023)
4. Machine Learning with Python (various courses)
5. Software Carpentries in-person training in Unix, GitHub, and Python (last offered March 2023)
6. and more ....
In many of our Python workshops, students get some hands-on practice with Python using Jupyter notebooks. Many of these notebooks also work as standalone instruction materials. Faculty, students, and staff at Dartmouth have access to these notebooks through our JupyterHub. Instructions for getting started with JupyterHub are here.
For people who do not have access to Dartmouth materials or want to download and use these materials on their own machine, you can find our notebooks and other instruction materials at our GitLab page.
On both platforms, you can find coding notebooks and other materials on such topics as: Introduction to Python, Text Analysis in Python, APIs in Python, various machine learning topics in Python, interacting with Large Language Models in Python, and more....