Singular Value Decomposition Courses and Certifications

Foundations of Statistical Learning & Algorithms

Master fundamental mathematical concepts for machine learning through linear algebra, probability theory, and optimization techniques, focusing on practical applications and model evaluation methods.

• Coursera
• 21 hours 22 minutes
• Self-Paced
• Paid Course

Applied Mathematics in Bioengineering

Explore applied mathematics in bioengineering, covering linear algebra, statistics, signal processing, and Fourier analysis to solve real biomedical problems with practical tools like SVD, PCA, and hypothesis testing.

• Coursera
• 4 weeks, 8 hours a week
• Self-Paced
• Paid Course

Numerical Methods Applied to Chemical Engineering

Explore advanced numerical methods for solving complex chemical engineering problems, including heat transfer, fluid mechanics, and molecular simulation. Gain practical skills in computational techniques.

• MIT OpenCourseWare
• Self-Paced
• Free Online Course

Linear Algebra

Master matrix theory and linear algebra, exploring systems of equations, vector spaces, determinants, eigenvalues, and applications in various disciplines. Gain practical skills for solving complex mathematical problems.

• MIT OpenCourseWare
• Self-Paced
• Free Online Course

StatQuest with Josh Starmer

Principal Component Analysis - PCA, Step-by-Step

Step-by-step guide to Principal Component Analysis (PCA), explaining its importance in data analysis and machine learning. Covers 2D and 3D data examples, PC calculation, and interpretation of results.

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

Linear Algebra for AI - Generative AI - Agentic AI

433 ratings at Udemy

Master Linear Algebra: Essential Math for AI , Data Science, Machine Learning, Deep Learning Applications , Agentic AI

• Udemy
• 1 day 4 hours 5 minutes
• Self-Paced
• Paid Course

MathWorks

Introduction to Linear Algebra with MATLAB

1 rating

Use matrix methods to solve systems of linear equations and perform eigenvalue decomposition.

• MATLAB Academy
• 2 hours
• Self-Paced
• Paid Course

Mastering Linear Algebra: An Introduction with Applications

58 ratings at The Great Courses Plus

Take your math skills to a new level with linear algebra, which is used in everything from computer graphics to quantum mechanics.

• The Great Courses Plus
• 12 hours 2 minutes
• Self-Paced
• Free Trial Available

Matrix Theory and Applications

Master linear algebra and matrix decompositions, covering least squares, optimization, and machine learning applications—tailored for EE, CSE, and AI/Data Science undergraduates with no prior ML experience required.

• Swayam
• Self-Paced
• Free Online Course

Data Science Dojo

Introduction to Text Analytics with R - Overview

Explore text analytics with R: tokenization, feature engineering, classification models. Learn data cleaning, analysis, and visualization using a spam dataset. Practical introduction for aspiring data scientists.

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

NPTEL;  IIT Madras

Applied Linear Algebra

Explore vector spaces, linear maps, eigenvalues, and applications in systems, algorithms, and optimization. Gain practical skills in linear algebra for various fields.

• YouTube
• 1 day
• Self-Paced
• Free Video

NPTEL;  IIT Madras

Linear System Theory

We will cover time invariant, time varying, continuous and discrete time systems. This course will cover concepts of stability, controllability, observability, and design and serve as a necessary foundation for further study in the area of systems and co…

• YouTube
• 1 day 2 hours
• Self-Paced
• Free Video

Aleksa Gordić - The AI Epiphany

Neural Search with Jina AI - Open-Source ML Tool Explained

Explore Jina AI, an open-source neural search engine. Learn core concepts, set up an MNIST fashion example, and understand indexing, encoding, and evaluation processes for efficient machine learning workflows.

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

Weights & Biases

Linear Algebra - Math for Machine Learning

Explore core linear algebra concepts essential for machine learning, including arrays, linear functions, and SVD, with practical applications and programming analogies.

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

Steve Brunton

Sparse Nonlinear Dynamics Models with SINDy - The Library of Candidate Nonlinearities

Explores advanced techniques for SINDy algorithm, including control variables, bifurcation parameters, rational functions, dimensionality reduction, and symmetry constraints in nonlinear dynamics modeling.

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