In this course we'll be exploring the history of technology, the impact it has on society, and the different facets of computer science. Throughout the course our goal is to explore these topics through a mix readings out of the book "9 Algorithms That Changed The Future" and articles, small exploratory homework assignments, and weekly discussions.
The readings and activities for this class are not meant to take up a lot of time and you are not being tested on your understanding of the material. The exercises are there to get you thinking about computer science, how you can apply it to your own areas of interesting, and how it impacts your day to day life.
Our meetings will be in GUG 204 on Wednesdays from 4:30-5:50.
In our last section this week we recapped what we have learned in the honors section and looked at some next steps for things to learn on your own.
This week we will hear the experiences of some awesome people who have worked in industry and teaching. We heard their experiences about working at big companies and their strategies for getting their foot in the door to tech. Our panelists:
Have a good thanksgiving!
This week we talked about how data visualization can influence your opinion, how humans interpret data and visuals (like color, position accuracy, etc), and the effects that has on the design of data visualizations. We talked about what makes data visualizations good and bad and how we could maybe deceive people using data. Below is a list of things I showed off in class:
In this section, we discussed the mechanism for public key cryptography and how modern cryptography works. We talked about some of the high level details of how the algorithms worked and the history of their use. We also talked about how these algorithms rely on the difficulty of certain problems and how this relates to the famous P vs NP problem.
In this section, we learned about 2 common machine learning solutions to classification and discussed some of the real world applications. We discussed some of the difficulties when doing machine learning and what to look out for. We introduced what it looks like to write machine learning code in a language called Python.
In this section, we discussed how basic indexing and the PageRank algorithm works. We talked about what matters for indexing including word location and other metadata. For PageRank we talked about the concept that what is important is for other important websites to link to you.
We also briefly covered how the internet works, what webpages are and how the look, and how Google would build up their search indices using web crawlwers
We discussed the implications that Google's decisions have on our society. This discussion ranged from what ads they show us, to autocomplete suggestions, and to the ranking of the search results themselves.
Due at 4:30, right before class
In this section, I introduced the goals of the honors sections
We emphasized that 142 is about how to program computers while computer science (and computational/algorithmic thinking) is a much large scope than just programming. As a group, we discussed: