REGISTRATION NOTES
Click register and then use your @berkeley.edu or @lbl.gov email address.
If you have trouble, you may need to log out of Zoom and log back in.
For help read more here: https://dlab.berkeley.edu/zoom-troubleshooting-tips
Location: Remote via Zoom.
Recordings: This D-Lab workshop will be recorded and made available to UC Berkeley participants for a limited time. Your registration for the event indicates your consent to having any images, comments and chat messages included as part of the video recording materials that are made available.
Start Time: D-Lab workshops start 10 minutes after the scheduled start time (“Berkeley Time”). We will admit all participants from the waiting room at that time.
Date & Time: This workshop is a 3-part series running from 11:30am-1:30pm each day:
- Part 4: Tue, March 11
- Part 5: Thu, March 13
- Part 6: Tue, March 18
Description
This three-part interactive workshop series is a follow-up to D-Lab’s Python Fundamentals: Parts 1-3 and will complete your introduction to Python programming for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.
Workshop Structure
The complete Python Fundamentals series has 6 parts. Each of the parts takes 2 hours, and is delivered in a lecture-style coding walkthrough interrupted by challenge problems and a break. Instructors and TAs are dedicated to engaging you in the classroom and answering questions in plain language.
In Parts 4-6, we cover loops and conditionals, creating your own functions, analysis and visualization in Pandas, and the workflow of a data science project.
- Part 4: Functions and Conditionals
- Part 5: Data Analysis and Visualization
- Part 6: Project
This workshop does not cover the following:
- Navigating Jupyter Notebooks, assigning variables, data types, and error messages. These are covered in Python Fundamentals: Parts 1-3.
- Advanced DataFrame manipulation. This is covered in Python Data Wrangling.
- Advanced data visualization. This is covered in Python Data Visualization.
Prerequisites: D-Lab's Python Fundamentals: Parts 1-3 (6 hours) series or equivalent introductory Python knowledge.
Workshop Materials: https://github.com/dlab-berkeley/Python-Fundamentals
Software Requirements: Installation Instructions for Python Anaconda
Is Python not working on your laptop?
Attend the workshop anyway, we can provide you with a cloud-based solution until you figure out the problems with your local installation.
Questions? Email: dlab-frontdesk@berkeley.edu