Our primary goal is to teach you how to think like a computer scientist. You might assume that thinking like a computer scientist is all about learning how to write programs, but really the key is learning techniques for problem solving. This involves developing the ability to express solutions using algorithms, or step-by-step instructions for how to tackle problems. Learning how to use algorithms is an incredibly useful skill that will serve you well in any discipline. We've heard from former students that it even helped them write better papers.
In the schedule below there are reading assignments given in the announcements column. For a given date, you should complete the reading before coming to class on that day. Many of the readings are available online as PDFs or as web pages, and have been linked to. We will also be reading some chapters from the book entitled Failure: Why Science is so Successful, by Stuart Firestein. And, when Amy Volmer leads class on July 19, you should have read The Checklist Manisfesto: How to get Things Right by Atul Gawande.
WEEK | DAY | ANNOUNCEMENTS | TOPICS | LAB WORK |
1 | Jun 26 | Read | Introduction
| Lab1: Jupyter Notebooks Lab2: Functions (Rubric) Lab2 solutions |
Jun 27 | Read
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Jun 28 | Read
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2 | Jul 03 | Read
| Kevin Webb leading class Introduction to Computer Systems
| Lab3: PC destruction derby Lab4: Create a web page |
Jul 04 | No class: Happy 4th! | |||
Jul 05 | Read | |||
3 | Jul 10 | Read |
| Lab5: Simulating robots Lab6: Experimenting with Sensor Noise (Rubric) |
Jul 11 | Read | |||
Jul 12 | ||||
4 | Jul 17 | Start to read
| Communicating scientific results
| Create a Poster |
Jul 18 | Continue to read
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Jul 19 | Finish reading
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5 | Jul 24 | Be prepared to electronically present your poster in class | ||
Jul 25 | Meet at Beardsley Media Center to print your poster | |||
Jul 26 | Poster Session (Jul 27) |