Course Description

This is a self-paced independent learning course that focuses on Python-based machine learning, enabling learners to explore concepts and practice programming skills on their own. Participants will learn key machine learning concepts and practical skills, with hands-on implementation using the Scikit-Learn library.

Course Topics

• Introduction to Machine Learning
• Simple Linear Regression
• Multiple Linear Regression
• Polynomial Regression
• Ridge and Lasso Regression
• Logistic Regression
• K-Nearest Neighbors (K-NN)
• Decision Tress
• Model Evaluation for Classifiers
• K-Means Clustering

Learning Outcomes

Upon successful completion of this course, participants will be able to:

• Describe fundamental machine learning concepts and principles.

• Develop machine learning programs using Python.

Course Prerequisites

Good knowledge on Python

Course Assessment

Assessment for this course is based on one (1) online multiple-choice quiz (20 marks) and a written assignment (30 marks).