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Overview
About the course
Computing is done in R, through tutorial sessions and homework assignments. This math-light Introduction to Statistical Learning course at Stanford University - Summer Sessions is offered remotely only via video segments (MOOC style).
TAs will host remote weekly office hours using an online platform such as Google Hangout or BlueJeans. There are four homework assignments, a midterm, and a final exam, all of which are administered remotely.
Programme Structure
The syllabus includes:
- linear and polynomial regression
- logistic regression and linear discriminant analysis
- cross-validation and the bootstrap
- model selection and regularization methods (ridge and lasso)
- nonlinear models
- splines and generalized additive models
- tree-based methods
- random forests and boosting
- support-vector machines
- principal components and clustering (k-means and hierarchical)
Key information
Duration
- Part-time
- 2 months
Start dates & application deadlines
- Starting
- Apply before
-
Language
English
TOEFL® IBT 100
Credits
3 SCH
Delivered
Online
Disciplines
Applied Mathematics Statistics View 19 other Short Courses in Applied Mathematics in United StatesAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
TOEFL® IBT 100
Other requirements
General requirements
To be eligible to apply, you must:
- Be at least 18 years of age by the start of the program.
- Have graduated from high school or secondary school or equivalent.
- Be a current university student or have some university or post-secondary experience.
Tuition Fee
To always see correct tuition fees
-
International
6860 USD/fullTuition FeeBased on the tuition of 6860 USD for the full programme during 2 months. -
National
6860 USD/fullTuition FeeBased on the tuition of 6860 USD for the full programme during 2 months. -
In-State
6860 USD/fullTuition FeeBased on the tuition of 6860 USD for the full programme during 2 months.
Funding
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