Math For Machine Learning Courses
Courses in Math for Machine Learning often teach linear algebra, calculus, probability, and statistics, providing a solid foundation for understanding algorithms. You can build skills in optimization techniques, data analysis, and model evaluation, which are crucial for effective machine learning applications. Many courses introduce tools like Python libraries such as NumPy and TensorFlow, which help you implement mathematical concepts in AI projects and enhance your ability to work with data-driven models.
Popular Math For Machine Learning Courses and Certifications
Alberta Machine Intelligence Institute
Skills you'll gain: Feature Engineering, Data Preprocessing, Model Evaluation, Data Quality, Model Training, Data Validation, Data Cleansing, Data Transformation, Verification And Validation, Applied Machine Learning, Machine Learning, Responsible AI, Machine Learning Algorithms, Algorithms, Python Programming, Computer Programming, Linear Algebra, Statistical Analysis
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
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, Jupyter, Statistics, Numerical Analysis, Applied Machine Learning, Geometry, Artificial Neural Networks, Data Science, Data Manipulation, Data Transformation
Skills you'll gain: Feature Engineering, Model Evaluation, Model Deployment, Fine-tuning, Data Preprocessing, Model Training, Deep Learning, Machine Learning Methods, Model Optimization, Scikit Learn (Machine Learning Library), PyTorch (Machine Learning Library), Scalability, Hugging Face, Docker (Software), Supervised Learning, Machine Learning Algorithms, Applied Machine Learning, Application Deployment, Software Development, Machine Learning
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
Imperial College London
Skills you'll gain: Linear Algebra, Applied Mathematics, Jupyter, Data Science, Data Manipulation, Data Transformation, Machine Learning
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, Probability, Statistical Inference, Statistics, A/B Testing, Statistical Analysis, Statistical Machine Learning, Data Science, Exploratory Data Analysis, Correlation Analysis, Histogram, Statistical Visualization, Box Plots
University of Pittsburgh
Skills you'll gain: Statistical Analysis, NumPy, Probability Distribution, Matplotlib, Plot (Graphics), Statistics, Data Science, Probability & Statistics, Probability, Statistical Modeling, Predictive Modeling, Data Analysis, Linear Algebra, Predictive Analytics, Statistical Methods, Mathematics and Mathematical Modeling, Applied Mathematics, Python Programming, Machine Learning, Logical Reasoning
University of Pennsylvania
Skills you'll gain: Statistical Machine Learning, Data Preprocessing, Model Evaluation, PyTorch (Machine Learning Library), Statistical Methods, Probability, Probability & Statistics, Sampling (Statistics), Logistic Regression, Deep Learning, Probability Distribution, Statistical Modeling, Python Programming, Supervised Learning, Machine Learning, Data Processing, Agentic systems, Artificial Intelligence, Algorithms, AI literacy
Johns Hopkins University
Skills you'll gain: Descriptive Statistics, Linear Algebra, Exploratory Data Analysis, Data-Driven Decision-Making, Data Analysis, Bayesian Statistics, Artificial Intelligence, Probability, Regression Analysis, Calculus, Mathematical Software, Advanced Mathematics, Applied Mathematics, Probability Distribution, Mathematical Modeling, Model Optimization, Integral Calculus, Algebra, Machine Learning Algorithms, Dimensionality Reduction
DeepLearning.AI
Skills you'll gain: Model Optimization, Machine Learning Methods, Applied Mathematics, Calculus, Applied Machine Learning, Numerical Analysis, Mathematical Modeling, Machine Learning, Data Visualization, Python Programming, Artificial Neural Networks, Deep Learning, Computer Programming, Derivatives
Skills you'll gain: Feature Engineering, Decision Tree Learning, Applied Machine Learning, Supervised Learning, Advanced Analytics, Statistical Machine Learning, Machine Learning, Machine Learning Algorithms, Unsupervised Learning, Analytics, Model Training, Random Forest Algorithm, Model Optimization, Predictive Modeling, Model Evaluation, Python Programming, Performance Tuning, Classification Algorithms
In summary, here are 10 of our most popular math for machine learning courses
- Data for Machine Learning: Alberta Machine Intelligence Institute
- Mathematics for Machine Learning and Data Science: DeepLearning.AI
- Mathematics for Machine Learning: Imperial College London
- Machine Learning and Deep Learning for Software Engineers: Board Infinity
- Linear Algebra for Machine Learning and Data Science: DeepLearning.AI
- Mathematics for Machine Learning: Linear Algebra: Imperial College London
- Probability & Statistics for Machine Learning & Data Science: DeepLearning.AI
- Mathematical Foundations for Data Science and Analytics: University of Pittsburgh
- AI and Machine Learning Essentials with Python: University of Pennsylvania
- Foundational Mathematics for AI: Johns Hopkins University
