Honors Section (CSE 390HA)

Wednesdays, 3:30-5:20pm, in CSE 403

Instructor: Miya Natsuhara (mnats@cs.washington.edu)

This quarter, we are offering an honors section for students who are interested in exploring additional topics related to technology and computer science. This is a one-unit, CR/NC course that will be offered in a seminar setting. Sessions will consist of group discussions about various topics and ideas along with some activities. There will be a small amount of homework prior to each session, primarily readings or videos that will be discussed in class, along with some short questions to help guide discussion. Students must attend seven (7) of the nine (9) six (6) of the eight (8) scheduled sessions and participate in all discussions and activities to receive credit (changes made to requirements after decision to cancel last in-person meeting).

Each week, we will discuss various topics related to computer science. Our sessions will mostly relate to the societal and cultural impacts of technology and CS, and some exploration of some technical concepts. This course is NOT an opportunity to learn more programming or add more "rigor" to 142, nor is any background or familiarity with computer science required. This is an opportunity to think about computer science and other related topics in a broader context.

In this course, we will be reading chapters from 9 Algorithms That Changed The Future by John MacCormick

Honors students are automatically eligible for the honors section, and should register for CSE 390H (section A) if interested. Non-honors students will be accepted based on available space. If you are a non-honors student interested in joining the section, please fill out this application:

Honors Section Application

Applications are due by 12:00pm noon on Sunday, January 12. Students will be informed whether or not they have been accepted by the evening of Monday, January 13. Our first meeting will take place on Wednesday, January 15 (barring any snow interference).

Week 8 (3/4): Industry, Research, & Education Panel

We had a panel comprised of Robbie Weber (rtweber2@cs.washington.edu), Sami Davies (daviess@cs.washington.edu), Singh Karan (karanbir@uw.edu), Sherdil Niyaz (sniyaz@uw.edu), Tanvi Dighde (tdighde@live.com), and John Thickstun (thickstn@cs.washington.edu). For a voice recording of the session, please email me (mnats@cs.washington.edu).

Homework for next section:

  • None! Since UW will not be holding any in-person meetings next week, we will not have a class. The plan for next week was to have an AMA ("ask me anything") with me, so if you have any parting questions you'd like to ask, feel free to shoot me an email!

Week 7 (2/26): Human-Computer Interaction with Kelly Mack

Guest visit from Kelly Mack, a PhD student doing research in HCI, specifically focused in Accessibility

Homework for next section:

  • Come up with at least two questions for our panelists by the end of the day on Tuesday

Week 6 (2/19): Theory of Computation, What is Computable?

We reviewed the issue of the Halting Problem from the chapter in 9 Algorithms That Changed the Future; we also reviewed the basics of graph theory, and spent the remainder of the class contemplating the graph-coloring problem (answers to the graphs proposed in class here) and introducing the ideas of time complexity (how long an algorithm takes to run), P vs. NP, and NP-completeness. For those interested, here is the page on quines that we talked about at the beginning of class, now that you've seen arrays!

Homework for next section:

Week 5 (2/12): Data Visualization; ML Game

Explored a few different important principles when designing good data visualizations; considered some bad (misleading) data visualizations, explored various interesting data visualizations (wind map, zip decoder", Baby name wizard", Years you have left to live probably, Interpreting confidence intervals"; played "Sticks" game to simulate an ML algorithm

Homework for next section:

Week 4 (2/5): Artifical Intelligence, Machine Learning, Pattern Recognition

Recap on ciphers from last week; Review on Reading: What are the Nearest Neighbors algorithm, Decision Trees and Neural Networks? Biases in Machine Learning Outputs; interesting related link

Homework for next section:

  • Watch this 10 minute video about the future of data visualization by UW's Jeff Heer.
  • Watch this 15 minute video demonstrating how data and its interpretability is important for global planning and reasoning about the current state of the world.

Week 3 (1/29): Public Key Cryptography; Privacy; Security

An incredibly long icebreaker; Review on Reading: How does public key cryptopgraphy work?; Further background on group theory behind RSA and Diffie-Hellman key exchange; KSK Key Signing Ceremony video mentioned in discussion

  • The output from a short encrypting program I wrote, see if you can crack it! (hint: google "Caesar Cipher"): w|shzulwhu lv wkh orqjhvw zrug wkdw |rx fdq zulwh xvlqj wkh ohwwhuv rqo| rq rqh urz ri wkh nh|erdug ri |rxu frpsxwhu
  • The output from another short encrypting program I wrote. This encryption scheme uses a random mapping from letters of the alphabet to other letters of the alphabet. This will be trickier to crack than the Caesar Cipher, but think about what information you have available and what you could try to figure out the mapping (perhaps if given more data): apkxglfkaaka ta pck ybmekap xblf pcgp nbz vgm pnok zatme bmyn pck hkna dbl nbzl ykdp cgmf bm nbzl hknibglf

Homework for next section:

Week 2 (1/22): Search Indexing, PageRank and Google's Impact on Our Beliefs and Behaviors

Discussion of searching algorithms (indexing, word location) and ranking algorithms (hyperlink, authority, random surfer); search history, targeted advertising; personalized search results; autocomplete

Homework for next section:

  • Read chapter 4 (Public Key Cryptography) from 9 Algorithms That Changed the Future
  • Watch this 20-minute video from UW professor Yoshi Kohno describing the internet of things (IoT) and adversarial security

Week 1 (1/15): Welcome!

Course Overview; Get To Know; What is a computer? What is computer science?

Homework for next section: