Linear Algebra for Machine Learning Courses
Linear Algebra for Machine Learning courses can help you learn matrix operations, vector spaces, eigenvalues, and linear transformations. You can build skills in solving systems of equations, dimensionality reduction, and understanding data representations. Many courses introduce tools like NumPy and MATLAB, that support implementing algorithms and performing computations efficiently in AI and machine learning projects.
Popular Linear Algebra for Machine Learning Courses and Certifications
Birla Institute of Technology & Science, Pilani
Skills you'll gain: Linear Algebra, Numerical Analysis, Artificial Intelligence and Machine Learning (AI/ML), Applied Mathematics, Data Analysis, Machine Learning, Dimensionality Reduction, Model Optimization, Artificial Neural Networks
Imperial College London
Skills you'll gain: Linear Algebra, Applied Mathematics, Jupyter, Data Science, Data Manipulation, Dimensionality Reduction, Data Transformation, Machine Learning, Computational Thinking
DeepLearning.AI
Skills you'll gain: Linear Algebra, Dimensionality Reduction, Mathematical Software, Machine Learning Methods, Data Transformation, Data Manipulation, Applied Mathematics, Machine Learning, Python Programming, Algebra, Image Analysis
Skills you'll gain: Model Deployment, Databricks, MLOps (Machine Learning Operations), Cloud Deployment, Feature Engineering, Apache Spark, Model Training, AI Workflows, Machine Learning Software, Data Lakes, CI/CD, Model Evaluation, Applied Machine Learning, Data Store, Machine Learning, Development Environment, Statistical Machine Learning, Data Science, Machine Learning Algorithms, Python Programming
Imperial College London
Skills you'll gain: Dimensionality Reduction, Linear Algebra, Regression Analysis, NumPy, Calculus, Unsupervised Learning, Applied Mathematics, Statistical Methods, Descriptive Statistics, Model Optimization, Mathematical Software, Machine Learning Methods, Applied Machine Learning, Jupyter, Statistics, Numerical Analysis, Machine Learning Algorithms, Geometry, Artificial Neural Networks, Data Science
What brings you to Coursera today?
DeepLearning.AI
Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Statistical Methods, Probability Distribution, Linear Algebra, Statistical Inference, Model Optimization, Machine Learning Methods, Statistics, Applied Mathematics, Probability, Calculus, Dimensionality Reduction, Applied Machine Learning, Mathematical Software, Data Transformation, Machine Learning
Simplilearn
Skills you'll gain: Mathematical Modeling, Linear Algebra, Dimensionality Reduction, Data Analysis, Analytical Skills, Feature Engineering, Applied Machine Learning, Data Science, Data Transformation, Algebra
Imperial College London
Skills you'll gain: Dimensionality Reduction, NumPy, Unsupervised Learning, Statistical Methods, Descriptive Statistics, Jupyter, Statistics, Geometry, Linear Algebra, Data Transformation, Python Programming, Advanced Mathematics, Applied Mathematics, Calculus
University of Glasgow
Skills you'll gain: Generative AI, Data Preprocessing, Model Evaluation, Generative Model Architectures, Dimensionality Reduction, Applied Machine Learning, Feature Engineering, Image Analysis, Tensorflow, Generative Adversarial Networks (GANs), Computer Vision, LLM Application, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Convolutional Neural Networks, Keras (Neural Network Library), Recurrent Neural Networks (RNNs), Large Language Modeling, Data Cleansing, Autoencoders
John Wiley & Sons
Skills you'll gain: Data Literacy, Responsible AI, Machine Learning Methods, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Unstructured Data, Generative AI, Machine Learning Algorithms, Model Training, NumPy, Python Programming, Data Science, Scalability, Artificial Intelligence, Supervised Learning, Data Preprocessing, Unsupervised Learning, Feature Engineering, Algorithms
Birla Institute of Technology & Science, Pilani
Skills you'll gain: Supervised Learning, Applied Machine Learning, Feature Engineering, Machine Learning Methods, Machine Learning Algorithms, Statistical Machine Learning, Predictive Modeling, Model Training, Model Evaluation, Scikit Learn (Machine Learning Library), Machine Learning, Regression Analysis, Bayesian Statistics, Artificial Intelligence and Machine Learning (AI/ML), Logistic Regression, Classification Algorithms, Decision Tree Learning, Model Optimization, Data Preprocessing, Probability & Statistics
Skills you'll gain: Unsupervised Learning, Exploratory Data Analysis, Feature Engineering, Dimensionality Reduction, Supervised Learning, Classification Algorithms, Regression Analysis, Scikit Learn (Machine Learning Library), Machine Learning Algorithms, Statistical Methods, Data Preprocessing, Applied Machine Learning, Model Evaluation, Statistical Inference, Predictive Modeling, Machine Learning Methods, Statistical Hypothesis Testing, Model Training, Data Processing, Machine Learning
What brings you to Coursera today?
In summary, here are 10 of our most popular linear algebra for machine learning courses
- Linear Algebra for Machine Learning & AI: Birla Institute of Technology & Science, Pilani
- Mathematics for Machine Learning: Linear Algebra: Imperial College London
- Linear Algebra for Machine Learning and Data Science: DeepLearning.AI
- Practical Machine Learning on Databricks: Packt
- Mathematics for Machine Learning: Imperial College London
- Mathematics for Machine Learning and Data Science: DeepLearning.AI
- Linear Algebra for ML and Analytics Training: Simplilearn
- Mathematics for Machine Learning: PCA: Imperial College London
- Advanced Machine Learning and its Applications: University of Glasgow
- Foundations of Machine Learning: Concepts, Tools, and Math: John Wiley & Sons
