Welcome to Lede 2018: Foundations of Computing
- Instructor: Jonathan Soma, firstname.lastname@example.org
- Dates: Mondays and Wednesdays, 5/21-7/11 (Holidays: Monday 5/28, 7/4)
- Class: 10am-1pm, World Room
- Lab: 2pm-5pm, World Room
- Slack channel: #foundations
By the end of this course you’ll have the flexibility to find and execute solutions to most any coding- or data-related problem you run across. In theory we’re focusing on Python in general, the data package pandas, and comfort with the command line.
On many, many assignments, I will give you:
- More homework than you can reasonably accomplish
- Homework that involves googling answers
- Homework that requires thinking through problems and answers in complicated and specific ways
What’s this mean? It’s going to be hard.
If you find yourself falling down a black hole: just take a break. Or stop altogether! Don’t worry about it - ask people near you or TA’s for guidance.
Oh, and most importantly: if you can’t finish? Not a problem. It’s far more important to not get burned out and discouraged.
This is a rough outline, and will absolutely change very, very often.
Week 1: Introduction to Python and the command line (5/21 + 5/23)
In our first week we’ll take a look at the insides of our computers using the command line, with tools like
cat. Learn to navigate your computer and run basic Python scripts.
Week 2: Navigating APIs (5/30, Wed only)
No class on Monday due to Memorial Day
Become more comfortable with data types in Python by consuming data from APIs - dynamic sources of information that are easily understandable by Python. Learn the joys of Jupyter Notebooks.
Week 3: Analyzing structured data with Pandas (6/4 + 6/6)
Begin work with
pandas, a data analysis library that runs circles around Excel.
Week 4: Obtaining data through scraping (6/11 + 6/13)
Using our Python skills to scrape web sites with BeautifulSoup, along with advanced scraping such as form submission and using the browser automation tool Selenium.
Week 5: Dealing with text-based data in pandas (6/18 + 6/20)
How to take semi-structured text data and clean/extract the parts we’re interested in.
Week 6: Visualization and dealing with missing and dirty data (6/25 + 6/27)
Taming troublesome datasets with format conversation, filling in and ignoring “bad” values.
Week 7: Geographic analysis with QGIS (7/2, Monday only)
No class on Wednesday due to Memorial Day
Become familiar with different geographic data types, geocoding, the limitless power of column and spatial joins.
Week 8: Float (7/9 + 7/11)
Left empty to allowing some cushion in topic coverage. We’ll probably cover more QGIS,