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CS 68 — Machine Learning for Business with Python

Quarter: Summer
Day(s): Saturday and Sunday
Course Format: On-campus (About Formats)
Duration: 2 days
Date(s): Jul 22—Jul 23
Time: 10:00 am—4:00 pm (PT)
Refund Deadline: Jul 15
Unit: 1
Tuition: $430
Instructor(s): Charlie Flanagan
Limit: 60
Class Recording Available: No
Status: Open
DOWNLOAD THE SYLLABUS » (subject to change)
Saturday and Sunday
10:00 am—4:00 pm (PT)
Jul 22—Jul 23
2 days
Refund Date
Jul 15
1 Unit
Charlie Flanagan
DOWNLOAD THE SYLLABUS » (subject to change)
As artificial intelligence (AI) technologies proliferate, they become more accessible. This course explores an amazing array of powerful business insights and analytics using easy-to-use tools. These open-source tools, including Python and a curated set of associated libraries, are the secret to unlocking the hidden value within the data. We explore a different business-related problem each week and solve it using the relevant data science tools and techniques, including Scikit-Learn, TensorFlow, spaCy, and Altair. We measure the causal impact of a marketing campaign that a business has undertaken, predict whether a customer is likely to leave, or determine how much to charge for a new product. Students 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 leave the course knowing how to formulate business problems in a data science setting and the tools needed to solve them. Students also benefit from data science guest speakers tackling these same business problems. Students also have the option of working on a capstone project, which can be used as part of a more extensive portfolio.

Some prior experience with Python will be helpful but is not required.

Head of Data Science, Balyasny Asset Management

Charlie Flanagan is the head of data science at Balyasny Asset Management, a large multi-strategy 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.

Textbooks for this course:

(Recommended) Aurélien Géron , Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems; 2nd Edition (ISBN 978-1492032649)