Course Code & Number
ADA 442
Course Title
Statistical Learning
Level
BS
Credit Hours/ ECTS Credits
(3+0+0) 3 TEDU Credits, 6 ECTS Credits
Year of Study:
Junior
Semester:
Spring
Type of Course:
Compulsory
Mode of Delivery:
Face-to-face
Language of Instruction:
English
Pre-requisite / Co-requisite:
Pre-requisites: ADA 423
Co-requisites: NONE
Catalog Description
Statistical Learning, Linear Methods and Regularization, Classification, Resampling Methods, Non-linear Methods, Treebased Models, Applications using R.
Course Objectives
Main objective of this course is to introduce fundamental statistical techniques to students and enable them to solve real life problems using these various learning techniques using a statistical computation tool or language
Course Learning Outcomes
Upon successful completion of this course, students will be able to:
1.Classify and distinguish different learning methods,
2.Apply different prediction methods, interpret the results and outputs,
3.Apply different classification methods, interpret the results and outputs,
4.Solve real life problems using learning techniques,
5.Use at least one computational tool or language for learning algorithms.
Course Coordinator:
Dr. Seyit Mümin Cılasun