- Course Introduction
- Introduction to Unsupervised Learning - Part 1
- Introduction to Unsupervised Learning - Part 2
- Introduction to Clustering
- K-Means - Part 1
- K-Means - Part 2
- K-Means - Part 3
- K-Means - Part 4
- K Means Notebook - Part 1
- K Means Notebook - Part 2
- K Means Notebook - 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 Unsupervised Learning and K Means
Videos
Readings
- K Means Demo (Activity)
- Summary
Practice Exercises
- Introduction to Unsupervised Learning
- K Means Clustering
- End of Module
Week 2: Selecting a clustering algorithm
Videos
- Distance Metrics - Part 1
- Distance Metrics - Part 2
- Curse of Dimensionality Notebook - Part 1
- Curse of Dimensionality Notebook - Part 2
- Curse of Dimensionality Notebook - Part 3
- Curse of Dimensionality Notebook - Part 4
- Hierarchical Agglomerative Clustering - Part 1
- Hierarchical Agglomerative Clustering - Part 2
- DBSCAN - Part 1
- DBSCAN - Part 2
- Mean Shift
- Comparing Algorithms
- Clustering Notebook - Part 1
- Clustering Notebook - Part 2
- Clustering Notebook - Part 3
- Clustering Notebook - Part 4
Readings
- Curse of Dimensionality Demo (Activity)
- Clustering Demo (Activity)
- Summary
Practice Exercises
- Distance Metrics
- Clustering Algorithms
- Comparing Clustering Algorithms
- End of Module
Week 3: Dimensionality Reduction
Videos
- Dimensionality Reduction - Part 1
- Dimensionality Reduction - Part 2
- PCA Notebook - Part 1
- PCA Notebook - Part 2
- PCA Notebook - Part 3
- Non-Negative Matrix Factorization
- Non Negative Matrix Factorization Notebook - Part 1
- Non Negative Matrix Factorization Notebook - Part 2
- Dimensionality Reduction Imaging Example
Readings
- Principal Component Analysis (Activity)
- Non Negative Matrix Factorization (Activity)
- Summary
Practice Exercises
- Dimensionality Reduction
- Non Negative Matrix Factorization
- End of Module
Instructors
Mr Mark J Grover
Digital Content Delivery Lead
IBM
Mr Miguel Maldonado
Machine Learning Curriculum Developer
IBM
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