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
Amazon Web Services
Skills you'll gain: Artificial Intelligence and Machine Learning (AI/ML), Generative AI, Deep Learning, Artificial Intelligence, Amazon Web Services, Applied Machine Learning, AI literacy, Machine Learning, Digital Transformation
Korea Advanced Institute of Science and Technology(KAIST)
Skills you'll gain: Linear Algebra, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Applied Mathematics, Deep Learning, Machine 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: Model Evaluation, Classification Algorithms, R Programming, Apache Spark, Deep Learning, Applied Machine Learning, Data Wrangling, Keras (Neural Network Library), Unsupervised Learning, Model Training, Statistical Machine Learning, Data Manipulation, Machine Learning Methods, Machine Learning Algorithms, Data Science, Machine Learning, Tidyverse (R Package), Data Analysis, Bayesian Network, Logistic Regression
Multiple educators
Skills you'll gain: Unsupervised Learning, Supervised Learning, Machine Learning Methods, Model Training, Applied Machine Learning, Machine Learning Algorithms, Transfer Learning, Machine Learning, Jupyter, Decision Tree Learning, Model Evaluation, Responsible AI, Tensorflow, Data Ethics, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Classification Algorithms
Skills you'll gain: Model Evaluation, Predictive Modeling, Model Training, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Supervised Learning, Applied Machine Learning, Machine Learning Algorithms, Artificial Intelligence, Deep Learning, Classification Algorithms, Unsupervised Learning, Regression Analysis, Reinforcement Learning
Coursera
Skills you'll gain: Model Evaluation, Supervised Learning, Unsupervised Learning, Data Preprocessing, Time Series Analysis and Forecasting, Applied Machine Learning, Model Training, Machine Learning Methods, Machine Learning Algorithms, Statistical Machine Learning, Feature Engineering, Machine Learning Software, Dimensionality Reduction, Machine Learning, Predictive Modeling, Data Wrangling, Predictive Analytics, Scikit Learn (Machine Learning Library), Classification Algorithms, Forecasting
Skills you'll gain: Sampling (Statistics), Matplotlib, Data Analysis, Machine Learning Algorithms, Data Mining, Statistical Analysis, Statistical Hypothesis Testing, Plot (Graphics), Probability & Statistics, NumPy, Pandas (Python Package), Probability Distribution, Dimensionality Reduction, Model Evaluation, R Programming, Python Programming, Data Preprocessing, Applied Machine Learning, Regression Analysis, Artificial Intelligence and Machine Learning (AI/ML)
Skills you'll gain: Unsupervised Learning, Supervised Learning, Model Evaluation, Regression Analysis, Scikit Learn (Machine Learning Library), Machine Learning Methods, Applied Machine Learning, Model Training, Statistical Machine Learning, Predictive Modeling, Machine Learning Algorithms, Machine Learning, Dimensionality Reduction, Decision Tree Learning, Python Programming, Logistic Regression, Model Optimization, Predictive Analytics, Classification Algorithms
Johns Hopkins University
Skills you'll gain: Computer Vision, Model Evaluation, PyTorch (Machine Learning Library), Supervised Learning, Unsupervised Learning, Image Analysis, Applied Machine Learning, Data Preprocessing, Dimensionality Reduction, Machine Learning Methods, Reinforcement Learning, Feature Engineering, Machine Learning Algorithms, Convolutional Neural Networks, Regression Analysis, Data Processing, Model Training, Machine Learning, Deep Learning, Model Optimization
Skills you'll gain: Data Science, Unsupervised Learning, Exploratory Data Analysis, Probability & Statistics, Machine Learning Algorithms, Applied Machine Learning, Classification And Regression Tree (CART), Data Analysis, Python Programming, Random Forest Algorithm, Dimensionality Reduction, Predictive Modeling, NumPy, Regression Analysis, Statistical Analysis, Data Processing, Deep Learning, Pandas (Python Package), Data Visualization, Data Manipulation
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 and Artificial Intelligence: Amazon Web Services
- Math for AI beginner part 1 Linear Algebra: Korea Advanced Institute of Science and Technology(KAIST)
- Linear Algebra for ML and Analytics Training: Simplilearn
- Machine Learning with R: Packt
- Machine Learning: DeepLearning.AI
- Machine Learning Introduction for Everyone: IBM
- Foundations of Machine Learning: Coursera
- AI Machine Learning with R & Python Projects: EDUCBA
- Machine Learning with Python: IBM
- Applied Machine Learning: Johns Hopkins University
