Data Science Courses: Python, R, or Predictive Analytics
Winter break term: December 14 - January 11.
Python for Analytics
Review basic Python skills and data structures, move on to loading data from different sources, rearrange and aggregate it, then analyze and visualize it to create high-quality products. Homework consists of short answer questions to test concepts, guided exercises in writing code and data analysis problems. This course provides example software codes, supplemental readings available online, and a data analysis project.
R Programming - Intro 1
Power into R from first steps, learn file formats and basic R syntax, and start using text editors to write code. Learn how to read in files, use symbols and assignments, and iterate simple loops. The course closes with a discussion of data structures and subsetting. The assignments are guided exercises in writing code. In addition, assigned readings, practice exercises, and supplemental readings are provided.
Predictive Analytics 1 - Machine Learning Tools
Learn how to use algorithms to predict and classify numeric and categorical data. Test concepts, study guided data analysis problems using software, and tackle a data modeling project. There are assigned readings, supplemental video lectures, and a final data modeling project.
Earn 3 credits via credit transfer from the American Council on Education (ACE)
And at a very affordable rate! (<$200 per credit.) Make sure to list your school in the "academic affiliation" field on the registration form for even more savings. More information on ACE CREDIT®
Not seeing what you're looking for? Take a look at our course catalog. If you'd like to recommend another course for winter break, let us know! You can reach us via email at ourcourses(at)statistics(dot)com. Please include your school and whether or not this is just for you or if you can recruit nine (9) others to fill the course.