Welcome to Data Science with Kaggle! 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.
This class is a projects-based class with a machine learning bias. 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.
Note that this is not an easy class. The student facilitators intend to provide you with a comprehensive guide to data analysis with the goal of preparing you for industry and, if demonstrated superb interest, future machine learning competitions.
Early assignments (during the bootcamp and possibly the first week of class) will involve hand-written conceptual based questions to check for understanding.
Afterwards, assignments will involve in-class kaggle competitions where students submit their model predictions on a custom arranged data set separate from lecture. This will give you a chance to apply what you have learned in class. These assignments should be done individually.
Since this is a project-team-based class, attendance is mandatory. We will be keeping track at the beginning of each class. However, you may have two absences for any reason. If you are working with a team, please communicate appropriately.
|Section 1||Phillip Kuznetsov, Humza Iqbal||60||166 Barrows||[M, W] 6:30PM-8:00PM||02/06/2017||