Harvard University
High-Dimensional Data Analysis
4.316 ratingsA focus on several techniques that are widely used in the analysis of high-dimensional data.
- edX
- 4 weeks, 2 - 4 hours per week
- Self-paced
- Free to audit
- Paid certificate
- Advanced
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Dimensionality Reduction courses 24
Learn Dimensionality Reduction online: university courses, full YouTube courses, and courses with free certificates, from the IITs, MIT, Harvard, Google, Microsoft and more.
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IBM
AI Workflow: Feature Engineering and Bias Detection
4.486 ratingsThis is the third course in the IBM AI Enterprise Workflow Certification specialization. You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones. Course 3 introduces you to t…
Partner
- Coursera
- This course requires 7.5 to 9 hours of study.
- Self-paced
- Paid · free trial
- Paid certificate
- Cognitive Class
- 6 hours
- Self-paced
- Free course
- Free badge
- Beginner
Stanford University
Mining Massive Datasets
The course is based on the text Mining of Massive Datasets by Jure Leskovec, Anand Rajaraman, and Jeff Ullman, who by coincidence are also the instructors for the course.
- edX
- Self-paced
- Free to audit
- Paid certificate
- Advanced
Imperial College London
Mathematics for Machine Learning: PCA
4.03,190 ratingsThis intermediate-level course introduces the mathematical foundations to derive Principal Component Analysis (PCA), a fundamental dimensionality reduction technique. We'll cover some basic statistics of data sets, such as mean values and variances, we'll compute distances and angles between vector…
Partner
- Coursera
- 4 weeks of study, 4-6 hours/week
- Self-paced
- Paid · free trial
- Paid certificate
IBM
Deep Learning with Python and PyTorch.
3.816 ratingsThis course is the second part of a two-part course on how to develop Deep Learning models using Pytorch.
- edX
- 6 weeks, 2 - 4 hours per week
- Self-paced
- Free to audit
- Paid certificate
- Intermediate
Delft University of Technology
AI skills: Introduction to Unsupervised, Deep and Reinforcement Learning
Learn the fundamentals and principal AI concepts about clustering, dimensionality reduction, reinforcement learning and deep learning to solve real-life problems.
- edX
- 6 weeks, 5 - 7 hours per week
- Self-paced
- Free to audit
- Paid certificate
- Intermediate
University of Colorado Boulder
Predicting Extreme Climate Behavior with Machine Learning
Throughout Predicting Extreme Climate Behavior with Machine Learning, you'll explore both theoretical concepts and practical applications or machine learning and data analysis. You'll begin by analyzing unsupervised learning algorithms, mastering techniques like clustering and dimensionality reduct…
Partner
- Coursera
- 5 weeks, 4-6 hours/week
- Self-paced
- Paid · free trial
- Paid certificate
IBM
Machine Learning: Unsupervised Models
This course introduces key unsupervised machine learning techniques and explains how to choose the best algorithm for your data. Learn clustering and dimensionality reduction to find insights in unlabeled data sets.
- edX
- 1 weeks, 23 - 27 hours per week
- Self-paced
- Free to audit
- Paid certificate
- Intermediate
Adelaide University
Computational Thinking and Big Data
Learn the core concepts of computational thinking and how to collect, clean and consolidate large-scale datasets.
- edX
- 10 weeks, 7 - 9 hours per week
- Self-paced
- Free to audit
- Paid certificate
- Beginner
Udacity
Data Scientist Nanodegree Program
4.8814 ratingsThis advanced Nanodegree prepares you to tackle data science at scale. Work with AI best practices, build production-ready projects, and gain the confidence to lead data-driven solutions.
PartnerLearning path or series
- Udacity
- 5 minutes
- Self-paced
- Paid course
- Advanced
University of California, Davis
Linear Algebra for Machine Learning
Learn the linear algebra concepts behind machine learning.
- edX
- Self-paced
- Free to audit
- Paid certificate
- Intermediate
RWTH Aachen University
Mathematical Foundations of AI
"Mathematical Foundatiouns of AI" offers a rigorous introduction to the fundamental concepts of linear algebra, calculus, and optimization theory that form the mathematical basis of machine learning, data science, deep learning, and artificial intelligence. It explores key topics including a compre…
- edX
- Fixed dates
- Free to audit
- Paid certificate
- Intermediate
Coursera
Advanced Machine Learning Techniques
Welcome to Advanced Machine Learning Techniques, where you'll dive deep into sophisticated approaches that power modern AI applications. We'll explore five key areas of advanced ML: ensemble methods for combining models, dimensionality reduction techniques for handling complex data, natural languag…
Partner
- Coursera
- 5 weeks / 6-7 hours per week
- Self-paced
- Paid · free trial
- Paid certificate
University of Maryland Baltimore County
Data Preprocessing for Data Science
4.25 ratingsLearn how to prepare and transform data for analysis and machine learning. The course includes techniques for data cleaning, normalization, domain reduction, and the application of various dimensionality reduction methods such as PCA and t-SNE to enhance data usability and visualization.
- edX
- 4 weeks, 5 - 7 hours per week
- Self-paced
- Free to audit
- Paid certificate
- Beginner
Universidad del Rosario
Introducción a Machine Learning
4.05 ratingsConoce los conceptos básicos del aprendizaje automático de máquinas, usando un acercamiento algebraico. Aborda problemas de regresión, clasificación y agrupamiento, desde modelos lineales hasta modelos no-lineales utilizando redes neuronales artificiales.
- edX
- Self-paced
- Free to audit
- Paid certificate
- Beginner
Udacity
Unsupervised Learning Course
Learn to apply unsupervised learning methods like K-means and Gaussian mixtures to extract value from raw data. Develop skills in feature extraction and cluster validation to enhance data analysis.
Partner
- Udacity
- P3W
- Self-paced
- Paid course
- Intermediate
CodeSignal
Journey into Data Science with Python
Build practical data science skills in Python through hands-on work with NumPy, Pandas, visualization, preprocessing, and machine learning. Analyze real datasets while learning how to prepare data, model outcomes, and interpret patterns.
- edX
- Self-paced
- Free to audit
- Paid certificate
- Intermediate
CodeSignal
Text Classification with Natural Language Processing
Build advanced text classification skills for natural language processing, from collecting and preparing text data to training and optimizing models. Work with feature engineering, classical machine learning, ensemble methods, and deep learning approaches.
- edX
- Self-paced
- Free to audit
- Paid certificate
- Advanced
Udacity
Unsupervised Machine Learning and Recommendation Systems Course
This course covers advanced data science topics related to unsupervised machine learning. You will apply techniques including clustering and dimensionality reduction, then learn about the different strategies for generating personalized recommendations. The final lesson of the course covers practic…
Partner
- Udacity
- P4W
- Self-paced
- Paid course
- Advanced