- Welcome/ Introduction Video
- Introduction to Supervised Machine Learning: What is Machine Learning?
- Introduction to Supervised Machine Learning: Types of Machine Learning
- Supervised Machine Learning for Interpretation and Prediction
- Regression and Classification Examples
- Introduction to Linear Regression
- Linear Regression Demo - Part 1
- Linear Regression Demo - Part 2
- Linear Regression Demo - Part 3
Intermediate
Online
3 Weeks
Free
Quick facts
particular | details | |
---|---|---|
Medium of instructions
English
|
Mode of learning
Self study
|
Mode of Delivery
Video and Text Based
|
Course and certificate fees
Type of course
certificate availability
certificate providing authority
The syllabus
Week 1: Introduction to Supervised Machine Learning and Linear Regression
Videos
Readings
- Course Prerequisites
- Linear Regression Demo (Activity)
- Summary/Review
Practice Exercises
- Check for Understanding
- End of Module Quiz
Week 2: Data Splits and Cross Validation
Videos
- Training and Test Splits
- Training and Test Splits Lab - Part 1
- Training and Test Splits Lab - Part 2
- Training and Test Splits Lab - Part 3
- Training and Test Splits Lab - Part 4
- Cross-Validation
- Cross-Validation Demo - Part 1
- Cross-Validation Demo - Part 2
- Cross-Validation Demo - Part 3
- Cross-Validation Demo - Part 4
- Cross-Validation Demo - Part 5
- Polynomial Regression
Readings
- Training and Test Splits Demo
- Cross-Validation Demo
- Summary/Review
Practice Exercises
- Check for Understanding
- End of Module Quiz
Week 3: Regression with Regularization Techniques: Ridge, LASSO, and Elastic Net
Videos
- Bias Variance Trade off
- Regularization and Model Selection
- Ridge Regression
- LASSO Regression
- Polynomial Features and Regularization Demo - Part 1
- Polynomial Features and Regularization Demo - Part 2
- Polynomial Features and Regularization Demo - Part 3
- Further details of regularization
- Details of Regularization - Part 1
- Details of Regularization - Part 2
- Details of Regularization - Part 3
Readings
- Polynomial Features and Regularization Demo
- Details of Regularization Demo
- Summary/Review
Practice Exercises
- Check for Understanding
- End of Module Quiz
Instructors
Mr Mark J Grover
Digital Content Delivery Lead
IBM
Mr Miguel Maldonado
Machine Learning Curriculum Developer
IBM
Articles
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