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
Skills you'll gain: LLM Application, Machine Learning Methods, Applied Machine Learning, Machine Learning Algorithms, Fine-tuning, Model Training
Skills you'll gain: Reinforcement Learning, Dimensionality Reduction, PyTorch (Machine Learning Library), Machine Learning Algorithms, Data Preprocessing, Model Training, Model Evaluation, Artificial Intelligence and Machine Learning (AI/ML), Generative Adversarial Networks (GANs), Deep Learning, Generative AI, Applied Machine Learning, Pandas (Python Package), Scikit Learn (Machine Learning Library), Python Programming, Model Optimization, Machine Learning, Artificial Neural Networks, Natural Language Processing, Feature Engineering
Skills you'll gain: Exploratory Data Analysis, Logistic Regression, Correlation Analysis, Applied Machine Learning, Model Evaluation, Data Modeling
Amazon Web Services
Skills you'll gain: Machine Learning Methods, Decision Intelligence, Applied Machine Learning, Machine Learning, Technology Roadmaps, Data-Driven Decision-Making, Artificial Intelligence and Machine Learning (AI/ML), Business Solutions, Organizational Strategy, AI Product Strategy, Organizational Change, Feasibility Studies
University of Minnesota
Skills you'll gain: Dimensionality Reduction, Linear Algebra, Unsupervised Learning, Machine Learning Methods, Numerical Analysis, Mathematical Modeling, Applied Mathematics, Applied Machine Learning, Data Manipulation, Algorithms, Python Programming
Skills you'll gain: Exploratory Data Analysis, Model Evaluation, Data Collection, Model Deployment, Data Ethics, Machine Learning Software, Model Training, Feature Engineering, Data Cleansing, Responsible AI, Machine Learning Methods, Applied Machine Learning, Data Analysis, Statistical Analysis, Machine Learning, Statistical Methods, Application Deployment, Generative AI, Data Preprocessing, Continuous Monitoring
Skills you'll gain: Sampling (Statistics), Data Mining, Statistical Hypothesis Testing, Probability, Statistical Machine Learning, Probability & Statistics, Linear Algebra, Statistical Methods, Statistical Analysis, Statistical Inference, Data Analysis, Probability Distribution, Data Science, Statistics, Machine Learning Methods, Applied Machine Learning, Unsupervised Learning, Machine Learning Algorithms, Machine Learning, Supervised Learning
DeepLearning.AI
Skills you'll gain: Supervised Learning, Applied Machine Learning, Jupyter, Scikit Learn (Machine Learning Library), Machine Learning, Model Training, NumPy, Machine Learning Algorithms, Predictive Modeling, Classification Algorithms, Feature Engineering, Artificial Intelligence, Model Evaluation, Data Preprocessing, Python Programming, Logistic Regression, Model Optimization, Regression Analysis, Algorithms
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 Pennsylvania
Skills you'll gain: Statistical Machine Learning, Model Evaluation, Statistical Methods, Logistic Regression, Python Programming, Statistical Modeling, Supervised Learning, Machine Learning Methods, Machine Learning, Classification Algorithms, Regression Analysis, Statistical Analysis, Applied Machine Learning, Predictive Modeling, Probability & Statistics, Bayesian Statistics, Dimensionality Reduction, Statistical Hypothesis Testing, Model Optimization, Feature Engineering
Skills you'll gain: Supervised Learning, Model Optimization, Feature Engineering, Applied Machine Learning, Unsupervised Learning, Model Evaluation, Machine Learning Methods, Statistical Machine Learning, Machine Learning Algorithms, Predictive Modeling, Model Training, Data Preprocessing, Classification Algorithms, Artificial Intelligence and Machine Learning (AI/ML), Dimensionality Reduction, Data Transformation, Fine-tuning
Skills you'll gain: Plot (Graphics), Scripting, Scientific Visualization, Graphing, Scripting Languages, Data Visualization Software, Scalability, Code Reusability, Text Mining, Statistical Analysis, Time Series Analysis and Forecasting, Matlab, Mathematical Software, File I/O, Software Installation, Numerical Analysis, Mathematical Modeling, Predictive Modeling, Python Programming, Data Analysis
In summary, here are 10 of our most popular math for machine learning courses
- Fundamentals of Machine Learning: Packt
- Machine Learning with PyTorch and Scikit-Learn: Packt
- Statistics You Need to Know for Machine Learning: SAS
- Machine Learning Essentials for Business and Technical Decision Makers: Amazon Web Services
- Matrix Methods: University of Minnesota
- Building a Machine Learning Solution: Coursera
- Machine Learning with Python & Statistics: EDUCBA
- Supervised Machine Learning: Regression and Classification : DeepLearning.AI
- Mathematics for Machine Learning: PCA: Imperial College London
- Machine Learning Essentials: University of Pennsylvania
