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
Birla Institute of Technology & Science, Pilani
Skills you'll gain: Supervised Learning, Applied Machine Learning, Feature Engineering, Machine Learning Methods, Machine Learning Algorithms, Statistical Machine Learning, Predictive Modeling, Model Training, Model Evaluation, Scikit Learn (Machine Learning Library), Machine Learning, Regression Analysis, Bayesian Statistics, Logistic Regression, Classification Algorithms, Decision Tree Learning, Model Optimization, Data Preprocessing, Probability & Statistics
Skills you'll gain: Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Methods, Artificial Intelligence, Agentic systems, Machine Learning Algorithms, Applied Machine Learning, Computational Logic, Machine Learning, Logical Reasoning, Unsupervised Learning, Artificial Neural Networks, Reinforcement Learning, Markov Model, Algorithms, Problem Solving, Systems Design
Skills you'll gain: Model Optimization, Machine Learning Methods, Model Training, Hugging Face, Classification Algorithms
O.P. Jindal Global University
Wesleyan University
Skills you'll gain: Decision Tree Learning, Predictive Modeling, Model Evaluation, Random Forest Algorithm, Applied Machine Learning, Predictive Analytics, Machine Learning Methods, Unsupervised Learning, Machine Learning Algorithms, Machine Learning, Data Analysis, Exploratory Data Analysis, Regression Analysis, Python Programming
New York Institute of Finance
Skills you'll gain: Tensorflow, Keras (Neural Network Library), Financial Trading, Data Pipelines, Machine Learning Methods, Applied Machine Learning, Machine Learning, Securities Trading, Model Training, Python Programming, Model Evaluation
Stanford Online
Skills you'll gain: Machine Learning Methods, Healthcare Ethics, Data Ethics, Applied Machine Learning, Machine Learning Algorithms, Machine Learning, Artificial Neural Networks, Model Evaluation, Artificial Intelligence and Machine Learning (AI/ML), Reinforcement Learning, Deep Learning, Health Policy, Artificial Intelligence
Fractal Analytics
Skills you'll gain: Feature Engineering, Machine Learning Algorithms, Model Optimization, Machine Learning Methods, Random Forest Algorithm, Algorithms, Predictive Modeling
Skills you'll gain: Reinforcement Learning, Dimensionality Reduction, PyTorch (Machine Learning Library), Machine Learning Algorithms, Data Preprocessing, Model Training, Model Evaluation, Generative Adversarial Networks (GANs), Machine Learning Methods, Deep Learning, Applied Machine Learning, Pandas (Python Package), Scikit Learn (Machine Learning Library), Python Programming, Model Optimization, Machine Learning, Artificial Neural Networks, Natural Language Processing, Convolutional Neural Networks
Imperial College London
Skills you'll gain: Dimensionality Reduction, NumPy, Descriptive Statistics, Statistics, Geometry, Linear Algebra, Data Transformation, Python Programming, Calculus
DeepLearning.AI
Skills you'll gain: Supervised Learning, Applied Machine Learning, Scikit Learn (Machine Learning Library), Machine Learning, Model Training, NumPy, Predictive Modeling, Classification Algorithms, Feature Engineering, Artificial Intelligence, Model Evaluation, Python Programming, Logistic Regression, Model Optimization, Regression Analysis
Skills you'll gain: Machine Learning Methods, Health Informatics, Machine Learning, Deep Learning, Convolutional Neural Networks, Data Preprocessing, Predictive Modeling, Electronic Medical Record System, Machine Learning Algorithms, Recurrent Neural Networks (RNNs), Model Evaluation, Data Analysis
