Clustering Courses and Certifications

Unsupervised Learning and Clustering

Implement k-Means, mini-batch k-Means, PCA, and DBSCAN from scratch while visualizing clusters and evaluating clustering quality.

• CodeSignal
• 3 hours
• Self-Paced
• Free Certificate

Hierarchical Clustering Deep Dive

Learn hierarchical clustering in R by computing distance metrics, comparing linkage methods, and constructing and interpreting dendrograms.

• CodeSignal
• 2 hours
• Self-Paced
• Free Certificate

Density-Based Clustering Simplified

Learn how DBSCAN uses connectivity, density, and custom distance metrics to reveal nontraditional cluster shapes, with implementation and visualization in R.

• CodeSignal
• 2 hours
• Self-Paced
• Free Certificate

Clustering and Dimensionality Reduction

Implement k-means, PCA, UMAP, DBSCAN/HDBSCAN and Louvain clustering from scratch and with scikit-learn, then apply them to single-cell RNA, geospatial and mixed-type data.

• Train in Data
• Self-Paced
• Paid Course

Statistical Techniques in Tableau

682 ratings at DataCamp

Use Built-in Statistical Functions Take your reporting skills to the next level with Tableau’s built-in statistical functions.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

LiquidBrain Bioinformatics

Clustering and Markers Identification for ScRNA-Seq - Seurat Package Tutorial

Analyze single-cell RNA-seq data in Seurat: perform QC, normalization, PCA/UMAP clustering, and identify marker genes for cell types.

• YouTube
• 23 minutes
• Self-Paced
• Free Video

Goldsmiths University of London;  University of London

Foundations of Data Science: K-Means Clustering in Python

735 ratings at Coursera

Learn the maths, statistics and Python basics behind data science: compute means and deviations, move to two-dimensional data, use pandas, and cluster a dataset with K-means.

• Coursera
• 5 weeks, 6 hours a week
• Self-Paced
• Paid Course

Algorithmic Thinking (Part 2)

9 ratings

Implement divide-and-conquer and dynamic programming algorithms in Python — closest pairs, point clustering, sequence alignment — and apply them to large genomic and text data sets.

• Coursera
• 4 weeks, 3 hours a week
• Self-Paced
• Paid Course

Unsupervised Learning in R

107 ratings at DataCamp

Many times in machine learning, the goal is to find patterns in data without trying to make predictions.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Brown University;  Georgia Tech

Machine Learning: Unsupervised Learning

3 ratings

Ever wonder how Netflix can predict what movies you'll like? Or how Amazon knows what you want to buy before you do? The answer can be found in Unsupervised Learning!

• Udacity
• 5 hours
• Self-Paced
• Free Online Course

NPTEL-NOC IITM

K-means and Spectral Clustering Tutorial

Explore the application of k-means and spectral clustering techniques on custom datasets, including silhouette score calculation for performance evaluation.

• YouTube
• 11 minutes
• Self-Paced
• Free Video

UofU Data Science

Data Mining: Assignment-Based Clustering and k-Means Algorithms - Lecture 12

Dive into clustering algorithms like k-means, k-center, and k-median, exploring implementation techniques through Gonzalez, Lloyd's, and k-means++ algorithms for effective data grouping.

• YouTube
• 1 hour 22 minutes
• Self-Paced
• Free Video

Security BSides London

Malware Campaign Tracking Using Big Data Analytics and Machine Learning Clustering

Discover how to automate malware detection and tracking using big data analytics and machine learning clustering techniques for enhanced cybersecurity threat hunting and campaign analysis.

• YouTube
• 43 minutes
• Self-Paced
• Free Video

AI Engineer

How to Look at Your Data - Clustering Techniques and Data Analysis for AI Applications

Discover clustering techniques and data analysis methods to extract valuable insights from AI application conversation histories and create generative evaluations.

• YouTube
• 19 minutes
• Self-Paced
• Free Video

UofU Data Science

K-Means and Friends - Assignment-Based Clustering Algorithms - L9

Explore k-means clustering algorithms including k-median, k-mediod, and k-center formulations with Gonzalez and Lloyd's algorithms plus k-means++ initialization techniques.

• YouTube
• 1 hour 21 minutes
• Self-Paced
• Free Video