Data Science With Kaggle
About the Course:
Welcome to Data Science with Kaggle! This class is a projects-based class with a machine learning bias - projects will be in the form of instructor-run kaggle data science competitons released every few weeks. We will cover fundamentals such as data cleaning, interpretation, and visualization, machine learning algorithms such as clustering, random forests, and neural networks, and many other topics related to data science.
Kaggle is home to an abundant source of company-volunteered data that encourage data scientists from around the world to solve proposed, and often business-related, challenges. The platform fosters a great amount of knowledge sharing, competition, and practical relevance where beginners and experts alike benefit from an exponentially expanding field.
You are expected to have some programming or statistics backgrounds and so the material will be of greatest benefit to sophomores or those who have taken CS61A, DATA 8, STAT 133, or equivalent. However, the first two weeks of class will be an optional python bootcamp for those taking the course with absolutely no programming background. By the end, you can determine whether you are comfortable continuing through the course.
How to Enroll:
Enrollment is by application, via the form posted on our website.
EDIT: APPLICATIONS CLOSED THURSDAY 9/1 MIDNIGHT.
Course Contact: jsimonian AT berkeley.edu; jerryc AT berkeley.edu; philkuz AT berkeley.edu
Faculty Sponsor: Nusrat Rabbee
Time & Location:
|Section 1||Jerry Chen|
|60||155 Kroeber||MW 6:30p-8p||9/05||full||—|
|Syllabus: SyllabusFall2016v2.pdf||Jul 29||218kb||Adobe PDF (Viewer)||View Download|
Course info last modified September 4, 2016. This page has been viewed 6636 times.Could not update hit count.
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