About this Course

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Flexible deadlines
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Intermediate Level
Approx. 11 hours to complete
English

Skills you will gain

Regression AnalysisSupervised LearningLinear RegressionRidge RegressionMachine Learning (ML) Algorithms
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 11 hours to complete
English

Offered by

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IBM

Syllabus - What you will learn from this course

Week
1

Week 1

2 hours to complete

Introduction to Supervised Machine Learning and Linear Regression

2 hours to complete
9 videos (Total 77 min), 3 readings, 3 quizzes
9 videos
Introduction to Supervised Machine Learning: What is Machine Learning?4m
Introduction to Supervised Machine Learning: Types of Machine Learning10m
Supervised Machine Learning for Interpretation and Prediction12m
Regression and Classification Examples7m
Introduction to Linear Regression12m
Linear Regression Demo - Part110m
Linear Regression Demo - Part211m
Linear Regression Demo - Part34m
3 readings
Course Prerequisites4m
Linear Regression Demo (Activity)10m
Summary/Review4m
3 practice exercises
Check for Understanding15m
Check for Understanding15m
End of Module Quiz20m
Week
2

Week 2

4 hours to complete

Data Splits and Cross Validation

4 hours to complete
12 videos (Total 116 min), 3 readings, 4 quizzes
12 videos
Training and Test Splits Lab - Part 17m
Training and Test Splits Lab - Part 216m
Training and Test Splits Lab - Part 310m
Training and Test Splits Lab - Part 45m
Cross Validation11m
Cross Validation Demo - Part 110m
Cross Validation Demo - Part 28m
Cross Validation Demo - Part 311m
Cross Validation Demo - Part 410m
Cross Validation Demo - Part 56m
Polynomial Regression7m
3 readings
Training and Test Splits Demo10m
Cross Validation Demo10m
Summary/Review4m
4 practice exercises
Check for Understanding15m
Check for Understanding15m
Check for Understanding30m
End of Module Quiz15m
Week
3

Week 3

5 hours to complete

Regression with Regularization Techniques: Ridge, LASSO, and Elastic Net

5 hours to complete
11 videos (Total 126 min), 3 readings, 3 quizzes
11 videos
Regularization and Model Selection7m
Ridge Regression8m
LASSO Regression12m
Polynomial Features and Regularization Demo - Part 120m
Polynomial Features and Regularization Demo - Part 211m
Polynomial Features and Regularization Demo - Part 310m
Further details of regularization14m
Details of Regularization - Part 18m
Details of Regularization - Part 29m
Details of Regularization - Part 39m
3 readings
Polynomial Features and Regularization Demo10m
Details of Regularization Demo10m
Summary/Review10m
2 practice exercises
Check for Understanding15m
End of Module Quiz15m

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