Class:
Introductions, syllabus, spreadsheets
Before Class:
Read "French election results: Macron’s victory in charts" and send reading journal.
Watch Google Sheets Tutorial (yeah, it's three hours long, but it is totally worth it).
Class:
Before Class:
Watch "Data is Messy Part 1" and "Data is Messy Part 2"
Optional: Watch Mollie Pettit make amazing visualizations of police data.
Class:
Discussion of videos
San Diego Police Department data use the 2016 dataset.
Before Class:
Read "Confident Data Skills" Chapters 1 & 2 and send reading journal.
Class:
Stephanie Labou, UCSD's Data Science Librarian will give an introduction about library resources.
Finish SDPD project
Before Class:
Watch Mollie Pettit make amazing visualizations of police data.
Optional: Read San Diego Union-Tribune article about faulty SDPD data analysis
Class:
Discussion
SDPD Mapping Project
Before Class:
Read "Confident Data Skills". If you have the first edition, read Ch 3. For the second edition read the intro section of Part 2 ("The data science process" and "getting started"). Send in a reading journal.
Class:
Discussion
Intermediate Python
Before Class:
Watch "Web Scraping"
Watch "Questions and Metrics"
Class:
Web Scraping
Before Class:
Watch "Natural Language Processing"
Read "Confident Data Skills" Ch 4 "Identify the question" and send in reading journal.
Optional: read "She Giggles, He Gallops" (fun article)
Class:
Discussion of NLP video
Text Processing with NLTK
Before Class:
Class:
SQL in 45 Minutes (slides)
Before Class:
Watch "Imposter Syndrome"
Read The media has a probability problem and send reading response.
Class:
Discuss election
Regular expressions
Before Class:
Watch Introduction to LLMs
Class:
Talking about LLMs, including what they are, how they work, ethics, hallucinations, limitations, and the future.
Before Class:
Read How does Spotify know you so well? and send reading journal. Update: if you hit the paywall there is a PDF here.
Class:
Live coding! Colin tries to build an article summarizer while you watch.
Before Class:
Watch "Audio is Data"
Class:
Making noise
Before Class:
Watch "The Cloud"
Read "This is How AI Generators See the World" and send in journal.
Class:
Audio manipulation
Before Class:
You must bring a paper copy of your resume!
Class:
Resume workshop
Finish audio manipulation
No class, no journal. (shhh, be cool).
Before Class:
Watch "Images are Data!"
Class:
Image Processing for Data Scientists
Before Class:
We experiment on human beings! reading response email.
Skim bits of this very long paper: A Picture's Worth... We will be developing one algorithm from the paper together, in class.
Class:
Image Detective
Before Class:
Watch "How Classification Works"
bonus (optional, hard, deep) Why most published research findings are false
Class:
Finish Image Detective
Before Class:
Watch "Final Lecture"
Look, I get that you are more worried about finals than doing reading. So why don't you save this one for over break? To me, this gets at the core of data science: The Truth Continuum
Send me an email on whatever subject you want (feedback on this class, asking for advice, general data science info, etc), and I will try to give a helpful response.
Class:
No class.