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
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: 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
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
Fractal Analytics
Skills you'll gain: Model Evaluation, Model Deployment, Applied Machine Learning, Machine Learning, Machine Learning Methods, Supervised Learning, Regression Analysis, Decision Tree Learning, Machine Learning Algorithms, Model Training, Feature Engineering, Data Preprocessing, Unsupervised Learning, Predictive Modeling, Model Optimization, Logistic Regression, Anomaly Detection, Classification Algorithms
Skills you'll gain: Matplotlib, Data Visualization, NumPy, Pandas (Python Package), Model Evaluation, Plot (Graphics), Data Preprocessing, Regression Analysis, Scikit Learn (Machine Learning Library), Data Manipulation, Model Training, Machine Learning Methods, Machine Learning, Feature Engineering, Predictive Modeling, Data Wrangling, Applied Machine Learning, Supervised Learning, Data Processing, Data Pipelines
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: Apache Spark, Machine Learning, Generative AI, Model Evaluation, Supervised Learning, Apache Hadoop, Data Pipelines, Unsupervised Learning, Data Processing, Extract, Transform, Load, Predictive Modeling, Model Deployment, Classification Algorithms, Data Transformation, Regression Analysis
The University of Chicago
Skills you'll gain: Keras (Neural Network Library), Machine Learning Methods, Unsupervised Learning, Machine Learning Algorithms, Deep Learning, Machine Learning, Statistical Machine Learning, Machine Learning Software, Decision Tree Learning, Applied Machine Learning, Scikit Learn (Machine Learning Library), Classification Algorithms, Supervised Learning, Regression Analysis, Artificial Intelligence and Machine Learning (AI/ML), Random Forest Algorithm, Model Training, Dimensionality Reduction, Model Evaluation, Data Preprocessing
Skills you'll gain: Matplotlib, Data Preprocessing, Regression Analysis, Scikit Learn (Machine Learning Library), Machine Learning Methods, Data Visualization, Plot (Graphics), Python Programming, Applied Machine Learning, Model Optimization, Model Training, Data Processing, Pandas (Python Package), Data Wrangling, Model Evaluation, NumPy, Predictive Modeling, Machine Learning Algorithms, Statistical Machine Learning, Data Manipulation
Skills you'll gain: Exploratory Data Analysis, Logistic Regression, Correlation Analysis, Applied Machine Learning, Model Evaluation, Data Modeling
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
Skills you'll gain: Data Preprocessing, Unsupervised Learning, Model Evaluation, Time Series Analysis and Forecasting, Supervised Learning, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Algorithms, Model Training, Feature Engineering, Artificial Intelligence, Deep Learning, Classification Algorithms, Generative AI, Model Optimization, Regression Analysis
In summary, here are 10 of our most popular math for machine learning courses
- Matrix Methods: University of Minnesota
- Octave for Machine Learning: Data Analysis Mastery: EDUCBA
- Machine Learning Essentials for Business and Technical Decision Makers: Amazon Web Services
- Foundations of Machine Learning : Fractal Analytics
- Learn & Build Machine Learning Models with Python: EDUCBA
- Building a Machine Learning Solution: Coursera
- Machine Learning with Apache Spark: IBM
- Machine Learning: Concepts and Applications: The University of Chicago
- Machine Learning with Python: Build & Optimize: EDUCBA
- Statistics You Need to Know for Machine Learning: SAS
