This course serves as an introduction to data science from the perspective of statistics. The course begins with an introduction of relevant computational and analytical tools necessary to analyze large data sets (with the understanding that the tools which are most relevant change
over time) including Python, R and SAS. The course will then focus on visualisation tools and exploratory data analysis, high dimensional statistical tools such as LASSO and tensor analysis, as well as causality and propensity scores. The students will learn how these tools are implemented on large data sets through case studies.
Tips: you can drag and drop the boxes to clone them to different sections or groups within a prerequisite equation.
Prerequisite Equation
Edit the prerequisite equation to this course:
note: adding data in this section will override data in the Prerequisite List.
+ add prereq equation
Prerequisite List(Overridden by Prerequisite Equation)
Edit the list of prerequisites to this course:
note: data in this section will be override by the Prerequisite Equation if it exists.
+ add new course
Exclusion List
Edit the list of course cerdit exclusions to this course:
+ add new course
Your name (optional):
Any additional comment (optional):
Thank you for your edit suggestion!
Our staff will review and approve it soon.
You can close this page now.
There might have been an error with the server or your input.
Please check your entry and/or try again later.