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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

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