
STATISTICAL LEARNING
14.09.2023 |
This introductory-level course in supervised learning covers regression and classification techniques, including linear and polynomial regression, logistic regression, cross-validation, and more. It also touches on some unsupervised learning methods like principal components and clustering. The course emphasizes practical understanding without heavy math, using R for computing and providing detailed tutorials on its usage. Explore modern data analysis essentials with us.
Prerequisites: Foundational knowledge in statistics, linear algebra, and computing is recommended.
Instructors: Learn from Trevor Hastie, Professor of Statistics at Stanford University, and Robert Tibshirani, Professor in Health Research and Policy and Statistics at Stanford University.
Details
Website
Target audience
Digital skills for ICT professionals
Digital technology
Digital skills
Level
Basic
Format of the training
Online
Training fee
Free training
Duration of the training
Type of training
Language of the training
English
Country providing the training
Other
Classification
Single opportunity