About this Course

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Intermediate Level
Approx. 9 hours to complete
English
Subtitles: English

Skills you will gain

Dimensionality ReductionUnsupervised LearningCluster AnalysisK Means ClusteringPrincipal Component Analysis (PCA)
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. 9 hours to complete
English
Subtitles: 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 Unsupervised Learning and K Means

2 hours to complete
11 videos (Total 61 min), 2 readings, 3 quizzes
11 videos
Introduction to Unsupervised Learning - Part 18m
Introduction to Unsupervised Learning - Part 24m
Introduction to Clustering1m
K-Means - Part 13m
K-Means - Part 23m
K-Means - Part 34m
K-Means - Part 44m
K Means Notebook - Part 19m
K Means Notebook - Part 26m
K Means Notebook - Part 313m
2 readings
K Means Demo (Activity)10m
Summary10m
3 practice exercises
Introduction to Unsupervised Learning10m
K Means Clustering10m
End of Module20m
Week
2

Week 2

4 hours to complete

Selecting a clustering algorithm

4 hours to complete
16 videos (Total 143 min), 3 readings, 4 quizzes
16 videos
Distance Metrics - Part 26m
Curse of Dimensionality Notebook - Part 111m
Curse of Dimensionality Notebook - Part 212m
Curse of Dimensionality Notebook - Part 312m
Curse of Dimensionality Notebook - Part 410m
Hierarchical Agglomerative Clustering - Part 13m
Hierarchical Agglomerative Clustering - Part 29m
DBSCAN - Part 15m
DBSCAN - Part 28m
Mean Shift9m
Comparing Algorithms11m
Clustering Notebook - Part 114m
Clustering Notebook - Part 26m
Clustering Notebook - Part 37m
Clustering Notebook - Part 411m
3 readings
Curse of Dimensionality Demo (Activity)10m
Clustering Demo (Activity)10m
Summary10m
4 practice exercises
Distance Metrics10m
Clustering Algorithms10m
Comparing Clustering Algorithms10m
End of Module10m
Week
3

Week 3

4 hours to complete

Dimensionality Reduction

4 hours to complete
9 videos (Total 88 min), 2 readings, 4 quizzes
9 videos
Dimensionality Reduction - Part 26m
PCA Notebook - Part 111m
PCA Notebook - Part 212m
PCA Notebook - Part 311m
Non Negative Matrix Factorization9m
Non Negative Matrix Factorization Notebook - Part 18m
Non Negative Matrix Factorization Notebook - Part 26m
Dimensionality Reduction Imaging Example7m
2 readings
Non Negative Matrix Factorization (Activity)2m
Summary10m
3 practice exercises
Dimensionality Reduction5m
Non Negative Matrix Factorization10m
End of Module10m

About the IBM Introduction to Machine Learning Specialization

This specialization will help you realize the potential of machine learning in a business setting. There will be a focus on helping you gain the skills that will help you succeed in a career in machine learning and data science. You will be able to realize the potential of machine learning and artificial intelligence in different business scenarios. You will also be able to identify when to use machine learning to explain certain behaviors and when to use it to predict future outcomes. You will also learn how to evaluate your machine learning models and to incorporate best practices....
IBM Introduction to Machine Learning

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