
Google Cloud
Skills you'll gain: Model Deployment, Convolutional Neural Networks, Google Cloud Platform, Natural Language Processing, Tensorflow, MLOps (Machine Learning Operations), Reinforcement Learning, Transfer Learning, Computer Vision, Systems Design, Applied Machine Learning, Image Analysis, Cloud Deployment, Hybrid Cloud Computing, Recurrent Neural Networks (RNNs), Systems Architecture, Performance Tuning, Embeddings, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning
Advanced · Specialization · 3 - 6 Months

Multiple educators
Skills you'll gain: Unsupervised Learning, Supervised Learning, Transfer Learning, Machine Learning, Jupyter, Applied Machine Learning, Data Ethics, Decision Tree Learning, Model Evaluation, Tensorflow, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Classification Algorithms, Reinforcement Learning, Random Forest Algorithm, Feature Engineering, Data Preprocessing
Beginner · Specialization · 1 - 3 Months

Coursera
Skills you'll gain: Transfer Learning, Data Preprocessing, Hugging Face, Model Evaluation
Intermediate · Course · 1 - 3 Months

University of Washington
Skills you'll gain: Model Evaluation, Classification Algorithms, Regression Analysis, Applied Machine Learning, Feature Engineering, Machine Learning, Image Analysis, Unsupervised Learning, Predictive Modeling, Supervised Learning, Bayesian Statistics, Logistic Regression, Statistical Modeling, Artificial Intelligence, Data Preprocessing, Deep Learning, Data Mining, Decision Tree Learning, Computer Vision, Statistical Machine Learning
Intermediate · Specialization · 3 - 6 Months

Skills you'll gain: Feature Engineering, Model Evaluation, Applied Machine Learning, Advanced Analytics, Analytics, Statistical Machine Learning, Machine Learning, Scikit Learn (Machine Learning Library), Unsupervised Learning, Machine Learning Algorithms, Workflow Management, Data Ethics, Supervised Learning, Data Preprocessing, Random Forest Algorithm, Decision Tree Learning, Verification And Validation, Python Programming, Classification Algorithms, Performance Tuning
Advanced · Course · 1 - 3 Months

DeepLearning.AI
Skills you'll gain: Transfer Learning, Machine Learning, Applied Machine Learning, Data Ethics, Decision Tree Learning, Model Evaluation, Tensorflow, Artificial Intelligence, Supervised Learning, Deep Learning, Classification Algorithms, Random Forest Algorithm, Artificial Neural Networks, Logistic Regression, Performance Tuning
Beginner · Course · 1 - 4 Weeks

DeepLearning.AI
Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Linear Algebra, Statistical Inference, A/B Testing, Statistical Analysis, Applied Mathematics, NumPy, Probability, Calculus, Dimensionality Reduction, Numerical Analysis, Machine Learning Algorithms, Data Preprocessing, Machine Learning, Machine Learning Methods
Intermediate · Specialization · 1 - 3 Months

DeepLearning.AI
Skills you'll gain: Convolutional Neural Networks, Recurrent Neural Networks (RNNs), Computer Vision, Transfer Learning, Deep Learning, Image Analysis, Hugging Face, Natural Language Processing, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Tensorflow, Applied Machine Learning, Embeddings, Supervised Learning, Keras (Neural Network Library), Machine Learning, Debugging, Performance Tuning, PyTorch (Machine Learning Library), Data Preprocessing
Build toward a degree
Intermediate · Specialization · 3 - 6 Months

University of Pennsylvania
Skills you'll gain: Statistical Machine Learning, Data Preprocessing, Model Evaluation, PyTorch (Machine Learning Library), Statistical Methods, Probability, Probability & Statistics, Sampling (Statistics), Logistic Regression, Deep Learning, Probability Distribution, Supervised Learning, Statistics, Machine Learning Methods, Machine Learning, Agentic systems, Artificial Intelligence, Artificial Neural Networks, Algorithms, Python Programming
Intermediate · Specialization · 3 - 6 Months
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, Decision Tree Learning, Unsupervised Learning, Python Programming, Random Forest Algorithm, Regression Analysis, Classification Algorithms, Artificial Neural Networks
Intermediate · Course · 1 - 4 Weeks

Alberta Machine Intelligence Institute
Skills you'll gain: Supervised Learning, Data Preprocessing, Feature Engineering, Responsible AI, Machine Learning Algorithms, Data Ethics, Applied Machine Learning, Model Evaluation, Data Quality, Classification Algorithms, MLOps (Machine Learning Operations), Model Deployment, Jupyter, Data Validation, Machine Learning, Decision Tree Learning, Business Operations, Data Cleansing, Product Lifecycle Management, Project Management
Intermediate · Specialization · 3 - 6 Months

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, Reinforcement Learning, Feature Engineering, Machine Learning Algorithms, Convolutional Neural Networks, Regression Analysis, Data Processing, Machine Learning, Data Mining, Data Cleansing, Deep Learning, Artificial Neural Networks
Intermediate · Specialization · 3 - 6 Months
It depends on your learning style and whether you want to focus more on theory or hands-on skills using Python:
Try Andrew Ng's Machine Learning Specialization for learners who want to use practical tools right away. ‎
A course teaches one focused topic—offering concise, standalone learning experiences.
A Specialization is a curated series of courses—designed to build expertise through a structured progression.
A Professional Certificate is a career-ready program—often including hands-on projects and aligned with industry roles.
You'll want to make sure you have a strong foundation of machine learning fundamentals before moving onto advanced concepts and classes. It's helpful to know the fundamentals of scalable data science and mathematics, including linear algebra and multivariate calculus. Programming, especially in Python, is also recommended, as is basic knowledge of SQL. ‎