Machine Learning and Deep Learning
Machine learning (ML) is an umbrella term for different AI systems that can learn from past data to process new data and make predictions, classifications, and decisions.
Deep learning (DL) is a subset of ML that specifically deals with neural networks which are inspired by the structure of the human brain.
On this page, you will find access to free courses to explain Machine Learning, Deep Learning, and neural networks, understand the principles of fairness and bias when using these technologies, identify the key steps involved in building, training, and deploying ML models, and define core concepts such as decision forests, clustering techniques, and recommendation systems.
Press on the course titles to access the learning material.
Beginner
Amazon SageMaker JumpStart Foundations
Beginner’s Guide to Machine Learning and Data Science
Introduction to AI and Machine Learning on Google Cloud
Introduction to Amazon SageMaker
Introduction to machine learning concepts
Introduction to Machine Learning Problem Framing
Machine Learning & Deep Learning
Machine Learning Learning Plan
Machine Learning Terminology and Process
Intermediate
AWS Certified Machine Learning Engineer – Associate
Building Language Models on AWS
End-to-end machine learning operations (MLOps) with Azure Machine Learning
Introduction to machine learning operations (MLOps)
Practical Guide to Machine Learning: Defining Problem Scope and Assessing Model Requirements
Advanced
Fundamentals of Neural Networks and Deep Neural Networks
Fundamentals of Reinforcement Learning
Fundamentals of Uncertainty Quantification (UQ): Modelling Real Problems with UQ