Math For Machine Learning Courses
Courses in Math for Machine Learning can help you learn linear algebra, calculus, probability, and statistics. You can build skills in data analysis, model evaluation, and algorithm optimization. Many courses introduce tools like Python libraries such as NumPy and SciPy, that support implementing mathematical concepts in AI and artificial intelligence projects. You'll also explore techniques like gradient descent and matrix factorization, which are crucial for developing effective machine learning 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, Supervised Learning, Data Validation, Data Cleansing, Data Ethics, Applied Machine Learning, Machine Learning, Unsupervised Learning, Machine Learning 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), Probability Distribution, Linear Algebra, Statistical Inference, A/B Testing, Statistical Analysis, Applied Mathematics, NumPy, Probability, Calculus, Dimensionality Reduction, Numerical Analysis, Mathematical Modeling, Data Preprocessing, Machine Learning, Machine Learning Methods
Imperial College London
Skills you'll gain: Linear Algebra, Dimensionality Reduction, NumPy, Regression Analysis, Calculus, Applied Mathematics, Data Preprocessing, Unsupervised Learning, Feature Engineering, Machine Learning Algorithms, Jupyter, Advanced Mathematics, Statistics, Artificial Neural Networks, Algorithms, Mathematical Modeling, Python Programming, Derivatives
DeepLearning.AI
Skills you'll gain: Linear Algebra, NumPy, Dimensionality Reduction, Data Preprocessing, Machine Learning Methods, Advanced Mathematics, Data Manipulation, Applied Mathematics, Mathematical Modeling, Machine Learning, Python Programming, Algebra
DeepLearning.AI
Skills you'll gain: Applied Mathematics, Calculus, Numerical Analysis, Mathematical Modeling, Machine Learning, Python Programming, Artificial Neural Networks, Deep Learning, Visualization (Computer Graphics), Derivatives
DeepLearning.AI
Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Probability, Statistical Inference, A/B Testing, Statistical Analysis, Statistical Machine Learning, Data Science, Statistical Modeling, Exploratory Data Analysis, Statistical Visualization
What brings you to Coursera today?
University of Pittsburgh
Skills you'll gain: Statistical Analysis, NumPy, Probability Distribution, Matplotlib, Statistics, Pandas (Python Package), 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, Supervised Learning, Statistics, Machine Learning Methods, Machine Learning, Agentic systems, Artificial Intelligence, Artificial Neural Networks, Algorithms, Python Programming
Skills you'll gain: Feature Engineering, Decision Tree Learning, Applied Machine Learning, Supervised Learning, Advanced Analytics, Machine Learning, Machine Learning Algorithms, Unsupervised Learning, Analytics, Random Forest Algorithm, Data Analysis, Predictive Modeling, Model Evaluation, Bayesian Network, Python Programming, Statistical Modeling, Classification Algorithms
Coursera
Skills you'll gain: Model Evaluation, Supervised Learning, Unsupervised Learning, Data Preprocessing, Time Series Analysis and Forecasting, Applied Machine Learning, Machine Learning Algorithms, Feature Engineering, Dimensionality Reduction, Machine Learning, Predictive Modeling, Predictive Analytics, Scikit Learn (Machine Learning Library), Classification Algorithms, Forecasting, Decision Tree Learning, Anomaly Detection, Data Manipulation, Regression Analysis, Statistical Modeling
Imperial College London
Skills you'll gain: Linear Algebra, NumPy, Applied Mathematics, Machine Learning Algorithms, Jupyter, Algorithms, Python Programming
Imperial College London
Skills you'll gain: Regression Analysis, Calculus, Advanced Mathematics, Machine Learning Algorithms, Linear Algebra, Artificial Neural Networks, Mathematical Modeling, Python Programming, Derivatives
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
- Linear Algebra for Machine Learning and Data Science: DeepLearning.AI
- Calculus for Machine Learning and Data Science: DeepLearning.AI
- 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
- The Nuts and Bolts of Machine Learning: Google
- Foundations of Machine Learning: Coursera
