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CS 73 — Decision-Making Under Uncertainty

Quarter: Summer
Day(s): Saturday and Sunday
Course Format: Live Online (About Formats)
Duration: 3 days
Date(s): Aug 8—Aug 15
Time: 9:00 am—12:30 pm (PT)
Refund Deadline: Aug 10
Unit: 1
Tuition: $375
Instructor(s): Charlie Flanagan
Class Recording Available: Yes
Status: Open
Please Note: This course has a different schedule than what appears in the print catalogue. Class will meet on Sundays, August 8 and 15 and Saturday, August 14 from 9:00 am – 12:30 pm (PT).
DOWNLOAD THE SYLLABUS » (subject to change)
Summer
Live Online(About Formats)
Saturday and Sunday
9:00 am—12:30 pm (PT)
Date(s)
Aug 8—Aug 15
3 days
Refund Date
Aug 10
1 Unit
Fees
$375
Instructor(s):
Charlie Flanagan
Recording
Yes
Open
Please Note: This course has a different schedule than what appears in the print catalogue. Class will meet on Sundays, August 8 and 15 and Saturday, August 14 from 9:00 am – 12:30 pm (PT).
DOWNLOAD THE SYLLABUS » (subject to change)
Uncertainty is an uncomfortable position. But certainty is an absurd one. —Voltaire

The decisions we make in our lives (business, saving and spending, health and lifestyle, relationships, parenting, to name a few) involve luck, uncertainty, and risk, but we most often don’t think deeply about how we are actually making these important decisions. In this course, we will explore decision-making cognitive and emotional biases, and investigate the best techniques from computer science, statistics, finance, and gambling for decomposing the elements of our decisions, applying data, and weighing the probabilities of various outcomes. We will look at how artificial intelligence systems make predictions about the future, how stock-trading algorithms manage risk, how dating apps decide who may be a good match, and how the Cold War was the ultimate application of game theory. We will use open source tools and code to model decisions. Students will leave the course with a set of mental models, probabilistic techniques, and statistical tools that they can apply to their own personal and professional decisions.

Some familiarity with Python programming will be helpful but is not required.

CHARLIE FLANAGAN
Data Scientist, Google

Charlie Flanagan spent ten years as a quantitative analyst in the financial industry before coming to Google. He received an MS in software engineering from Harvard and an MBA from Columbia, and is a Chartered Financial Analyst.

Textbooks for this course:

There are no required textbooks; however, some fee-based online readings may be assigned.