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: Predictive Modeling, Matplotlib, Machine Learning Methods, Applied Machine Learning, Seaborn, Statistical Modeling, Data Visualization, Plot (Graphics), Regression Analysis, Machine Learning Algorithms, Pandas (Python Package), Statistical Analysis, Machine Learning, Supervised Learning, Data Science, Statistical Methods, Probability & Statistics, Python Programming, Model Training, Statistical Programming
Alberta Machine Intelligence Institute
Skills you'll gain: Responsible AI, Data Ethics, MLOps (Machine Learning Operations), Model Deployment, Model Optimization, Business Operations, Machine Learning, Ethical Standards And Conduct, Operational Performance Management, Applied Machine Learning, Business Strategy, Risk Mitigation, Systems Integration, Stakeholder Communications
Northeastern University
Skills you'll gain: Transfer Learning, Small Data, Fine-tuning, Deep Learning, Applied Machine Learning, Machine Learning Methods, Model Training, Unsupervised Learning, Machine Learning, Data Synthesis, Supervised Learning
Simplilearn
Skills you'll gain: Mathematical Modeling, Linear Algebra, Dimensionality Reduction, Applied Mathematics, Data Analysis, Analytical Skills, Feature Engineering, Applied Machine Learning, Data Science
Skills you'll gain: Unsupervised Learning, Exploratory Data Analysis, Autoencoders, Feature Engineering, Dimensionality Reduction, Supervised Learning, Generative AI, Classification Algorithms, Regression Analysis, Time Series Analysis and Forecasting, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Reinforcement Learning, Generative Adversarial Networks (GANs), Generative Model Architectures, Scikit Learn (Machine Learning Library), Deep Learning, Data Science, Machine Learning, Python Programming
University of Washington
Skills you'll gain: Model Evaluation, Classification Algorithms, Regression Analysis, Applied Machine Learning, Feature Engineering, Machine Learning Methods, Machine Learning, Image Analysis, Machine Learning Algorithms, AI Personalization, Unsupervised Learning, Predictive Modeling, Classification And Regression Tree (CART), Supervised Learning, Bayesian Statistics, Statistical Machine Learning, Model Training, Logistic Regression, Statistical Modeling, Data Mining
Microsoft
Skills you'll gain: Unsupervised Learning, Microsoft Azure, Applied Machine Learning, Machine Learning Software, Model Training, Regression Analysis, Predictive Modeling, Machine Learning, No-Code Development, Machine Learning Algorithms, Artificial Intelligence and Machine Learning (AI/ML), Model Deployment, Artificial Intelligence, Classification Algorithms, Supervised Learning
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
Skills you'll gain: Tensorflow, Google Cloud Platform, Scripting, Data-Driven Decision-Making, Model Training, Applied Machine Learning, Machine Learning Methods, Artificial Neural Networks, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Cloud Computing, Development Environment
Multiple educators
Skills you'll gain: Tensorflow, Keras (Neural Network Library), Machine Learning Methods, Model Evaluation, Machine Learning, Google Cloud Platform, Model Training, Machine Learning Algorithms, Financial Trading, Reinforcement Learning, Recurrent Neural Networks (RNNs), Supervised Learning, Data Pipelines, Machine Learning Software, Time Series Analysis and Forecasting, Applied Machine Learning, Statistical Machine Learning, Model Optimization, Deep Learning, Portfolio Management
University of Michigan
Skills you'll gain: Feature Engineering, Model Evaluation, Applied Machine Learning, Supervised Learning, Scikit Learn (Machine Learning Library), Predictive Modeling, Machine Learning Methods, Machine Learning, Model Training, Model Optimization, Machine Learning Algorithms, Unsupervised Learning, Python Programming, Classification Algorithms, Artificial Neural Networks
DeepLearning.AI
Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Application Deployment, Model Training, Continuous Deployment, Model Evaluation, Data Preprocessing, Model Optimization, Machine Learning, Applied Machine Learning, Data Validation, Data Integrity, Data Maintenance, Data Quality, Data Synthesis, Data Collection, System Monitoring, Continuous Monitoring, Unstructured Data
In summary, here are 10 of our most popular math for machine learning courses
- Foundations of Data Science and Machine Learning with Python: Packt
- Optimizing Machine Learning Performance: Alberta Machine Intelligence Institute
- Machine Learning with Small Data Part 1: Northeastern University
- Linear Algebra for ML and Analytics Training: Simplilearn
- IBM Machine Learning: IBM
- Machine Learning: University of Washington
- Microsoft Azure Machine Learning: Microsoft
- IBM Introduction to Machine Learning: IBM
- Learning TensorFlow: the Hello World of Machine Learning: Google Cloud
- Machine Learning for Trading: New York Institute of Finance
