Mathematics for Machine Learning Courses
Mathematics for machine learning courses can help you learn linear algebra, calculus, probability, and statistics. You can build skills in optimization techniques, data analysis, and algorithm development. Many courses introduce tools like Python libraries such as NumPy and SciPy, that support implementing mathematical concepts in AI applications. You'll also explore key topics like regression analysis, dimensionality reduction, and neural networks, all of which are crucial for developing effective machine learning models.
Popular Mathematics for Machine Learning Courses and Certifications
EDHEC Business School
Skills you'll gain: Investment Management, Portfolio Management, Asset Management, Investments, Portfolio Risk, Machine Learning, Statistical Machine Learning, Applied Machine Learning, Financial Modeling, Supervised Learning, Predictive Analytics, Market Data, Feature Engineering, Unsupervised Learning, Regression Analysis, Statistical Methods, Analysis, Estimation, Risk Analysis, Computer Science
Skills you'll gain: Scikit Learn (Machine Learning Library), Classification Algorithms, Applied Machine Learning, Model Training, Machine Learning Algorithms, Predictive Modeling, Supervised Learning, Random Forest Algorithm, Machine Learning, Unsupervised Learning, Data Analysis
Skills you'll gain: PyTorch (Machine Learning Library), Model Optimization, Transfer Learning, Convolutional Neural Networks, Artificial Neural Networks, Deep Learning, Model Training, Logistic Regression, Image Analysis, Applied Machine Learning, Model Evaluation, Computer Vision, Classification Algorithms, Supervised Learning, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Statistical Methods
Google Cloud
Skills you'll gain: Model Optimization, MLOps (Machine Learning Operations), Model Deployment, Model Training, Systems Design, Tensorflow, Hybrid Cloud Computing, Google Cloud Platform, Machine Learning Methods, Performance Tuning, Applied Machine Learning, Machine Learning, Distributed Computing, Dependency Analysis, Data Pipelines
University of Washington
Skills you'll gain: Unsupervised Learning, Bayesian Statistics, Applied Machine Learning, Data Mining, Statistical Machine Learning, Statistical Inference, Text Mining, Machine Learning Methods, Statistical Modeling, Machine Learning Algorithms, Unstructured Data, Machine Learning, Sampling (Statistics), Scalability, Distributed Computing, Probability Distribution, Algorithms
Skills you'll gain: Marketing Analytics, Time Series Analysis and Forecasting, Retrieval-Augmented Generation, AI Personalization, Feature Engineering, Personalized Service, Customer Insights, Generative AI, Data-Driven Marketing, Customer Analysis, Key Performance Indicators (KPIs), Data Transformation, Generative Model Architectures, Customer Engagement, Marketing Strategies, Generative Adversarial Networks (GANs), Predictive Modeling, Responsible AI, Predictive Analytics, Trend Analysis
Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Data Preprocessing, Classification And Regression Tree (CART), Exploratory Data Analysis, Logistic Regression, Statistical Machine Learning, Model Evaluation, Model Training, Supervised Learning, Decision Tree Learning, Probability & Statistics, Data Processing, Statistical Software, Machine Learning Methods, Machine Learning Software, Workflow Management, Machine Learning, Correlation Analysis, Applied Machine Learning
University of Colorado Boulder
Skills you'll gain: Machine Learning Methods, Feature Engineering, Supervised Learning, Model Evaluation
DeepLearning.AI
Skills you'll gain: Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Convolutional Neural Networks, Applied Machine Learning, Supervised Learning, Artificial Intelligence, Machine Learning Methods, Python Programming, Model Training, Model Optimization
Columbia University
Skills you'll gain: Reinforcement Learning, Machine Learning Methods, Machine Learning Algorithms, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Algorithms, Decision Intelligence, Markov Model, Deep Learning, Statistical Methods, Analysis
Politecnico di Milano
Skills you'll gain: Machine Learning Methods, Unsupervised Learning, Supervised Learning, Machine Learning Algorithms, Machine Learning, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Reinforcement Learning, Dimensionality Reduction, Model Evaluation, Classification Algorithms, Algorithms
Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Microsoft Azure, Artificial Intelligence and Machine Learning (AI/ML), Model Training, Cloud Deployment, Data Pipelines, AI Workflows, AI Security, CI/CD, Continuous Monitoring, Identity and Access Management, Version Control, Data Storage
In summary, here are 10 of our most popular mathematics for machine learning courses
- Python and Machine Learning for Asset Management: EDHEC Business School
- Scikit-Learn For Machine Learning Classification Problems: Coursera
- Deep Learning with PyTorch: IBM
- Production Machine Learning Systems: Google Cloud
- Machine Learning: Clustering & Retrieval: University of Washington
- Machine Learning and Generative AI for Marketing: Packt
- SAS Machine Learning Engineer: SAS
- Introduction to Machine Learning: Unsupervised Learning: University of Colorado Boulder
- Neural Networks and Deep Learning: DeepLearning.AI
- Decision Making and Reinforcement Learning: Columbia University
