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TECH 68 — Machine Learning for Business with Python

Quarter: Spring
Day(s): Saturday and Sunday
Course Format: On-campus (About Formats)
Duration: 2 days
Date(s): Apr 27—Apr 28
Time: 10:00 am—4:00 pm (PT)
Refund Deadline: Apr 20
Unit: 1
Tuition: $435
Instructor(s): Charlie Flanagan
Limit: 60
Class Recording Available: No
Status: Open
Saturday and Sunday
10:00 am—4:00 pm (PT)
Apr 27—Apr 28
2 days
Refund Date
Apr 20
1 Unit
Charlie Flanagan
The availability of open source tools and libraries has made it easier to learn and experiment with AI technologies. These tools, including Python and third-party libraries, are the secret to unlocking the hidden value within the data. In this course, we will explore a different business-related problem each week and solve it using the relevant libraries, including Scikit-Learn, TensorFlow, spaCy, and Altair. We will measure the causal impact of a marketing campaign, predict whether a customer is likely to leave, and determine how much to charge for a new product. Students will learn the entire workflow, from identifying a business problem to gathering the data and implementing the solution in code in a scalable and repeatable way. Students will hear from data science guest speakers tackling these same business problems and leave the course knowing how to formulate business problems in a data science setting and possessing the tools needed to solve them. All students will have the option of working on a capstone project, which can be used as part of a more extensive portfolio.

Python programming experience is recommended—specifically with Pandas, NumPy, and Matplotlib libraries—but not required.

Head of Data Science, Balyasny Asset Management

Charlie Flanagan is the head of data science at Balyasny Asset Management, a large multistrategy hedge fund. Earlier, he worked for Google, where he was the data science lead for Google Duplex. He received an MS in software engineering from Harvard and an MBA from Columbia.