AC 209B - Advanced Topics in Data Science II
Professional Graduate Data Science Coursework - Spring semester 2017
The course is the second part of a series about advanced data science methods. Topics include the handling of big data and database management with spark, the use of non-linear statistical models such as smoothers and GAM, unsupervised learning, and deep learning with neural networks. The major programming languages are R and Python.
The directory structure is as follows:
||Files such as README and gitignore|
||The homework project files|
||Material from the labs|
||Material from the lectures|
||Videos from the lectures and labs|
You can access all the coursework etc. here.