Unsupervised Learning Courses and Certifications

Machine Learning Fundamentals in R

Learn the basics of prediction using machine learning.

• DataCamp
• 1 day
• Self-Paced
• Free Trial Available

Advanced Dimensionality Reduction in R

Learn how to apply advanced dimensionality techniques such as t-SNE and GLRM.

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

Dimensionality Reduction in R

Learn dimensionality reduction techniques in R and master feature selection and extraction for your own data and models.

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

Alfredo Canziani

Unsupervised Learning - Autoencoding the Targets

Explore unsupervised learning through autoencoders, latent-space modeling, and generative applications such as inpainting and super-resolution.

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

Google Cloud Tech

How to Create ML Models That Teach Themselves - Unsupervised Learning in Self-Driving Cars

Explore self-driving car technology and unsupervised ML models with Helm.ai. Learn about deep teaching, real-world applications, and future enhancements in autonomous vehicle development.

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

Career Certificate

Implementing AI Algorithms from Scratch

346 ratings at CodeSignal

Implement classic machine-learning algorithms from scratch—including regression, classification, ensembles, clustering, and neural-network basics—without machine-learning libraries.

• CodeSignal
• 21 hours
• Self-Paced
• Free Certificate
• 6 courses

Modelos predictivos con Machine Learning

36 ratings

En este curso conocerás los fundamentos del aprendizaje automático y como crear modelos de predicción, regresión y clasificación con ayuda de Python. Explorarás problemas de clasificación, regresión,

• edX
• 4 weeks, 6-8 hours a week
• Self-Paced
• Free Online Course (Audit)

Mathematics for Machine Learning: PCA

3190 ratings at Coursera

Derive PCA from geometry: summarize datasets with means and variances, use inner products and orthogonal projections, then implement PCA in Python notebooks.

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

EDGE AI FOUNDATION

Unsupervised Federated Learning for Edge Computing Applications

Explore federated learning techniques for edge devices, focusing on utilizing unannotated data to build global models while maintaining data privacy and security in IoT applications.

• YouTube
• 1 hour 5 minutes
• Self-Paced
• Free Video

VinAI

Annotation-Efficient Object Detection: Unsupervised Discovery to Active Learning

Explore annotation-efficient object detection techniques, from unsupervised discovery to active learning strategies, enhancing intelligent systems with less manual input.

• YouTube
• 1 hour 12 minutes
• Self-Paced
• Free Video

PioPetro

Unsupervised Learning and Advanced Topics - Lecture 4

Explore unsupervised learning techniques, model deployment, and ethical considerations in petroleum engineering and energy transition contexts.

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

Career Certificate

Implementing AI Algorithms from Scratch

67 ratings at CodeSignal

Implement classic machine learning algorithms from scratch—including regression, classification, clustering, ensemble methods, optimization, and neural networks—without high-level libraries.

• CodeSignal
• Self-Paced
• Free Certificate
• 6 courses

K-means Clustering Decoded

Implement K-means clustering in Python: initialize centroids, choose the number of clusters, visualize Iris clusters with Matplotlib, and evaluate results with the Rand Index.

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

Hierarchical Clustering Deep Dive

Build hierarchical clustering in Python: run agglomerative clustering on Iris data, compute Euclidean and alternative distance metrics, compare linkage criteria, and plot dendrograms.

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

Density-Based Clustering Simplified

Learn density-based clustering with DBSCAN in Python: implement connectivity and expansion logic from scratch, tune epsilon and distance metrics, and visualize clusters with scikit-learn.

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