Machine Learning (Caltech)

Machine Learning (Caltech)

A real Caltech course, not a watered-down version. This is an introductory course in machine learning (ML) that covers the basic theory, algorithms, and applications.

This is an introductory course in machine learning (ML) that covers the basic theory, algorithms, and applications. ML is a key technology in Big Data, and in many financial, medical, commercial, and scientific applications. It enables computational systems to adaptively improve their performance with experience accumulated from the observed data. ML has become one of the hottest fields of study today, taken up by graduate and undergraduate students from 15 different majors at Caltech. This course balances theory and practice, and covers the mathematical as well as the heuristic aspects.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

LangChain: Chat with Your Data (DeepLearning.AI) Other Providers
DeepLearning.AI

LangChain: Chat with Your Data (DeepLearning.AI)

Create a chatbot to interface with your private data and documents using LangChain. Join our new short course, LangChain: Chat With Your Data! The course delves into two main topics: (1) Retrieval Augmented Generation (RAG), a common LLM application that retrieves contextual documents from an external dataset, and (2) a guide to building a chatbot that responds to queries based on the content of your documents, rather than the information it has learned in training.

Self Paced
Self-Paced
Machine Learning: Concepts and Applications (Coursera) Coursera
University of Chicago

Machine Learning: Concepts and Applications (Coursera)

This course gives you a comprehensive introduction to both the theory and practice of machine learning. You will learn to use Python along with industry-standard libraries and tools, including Pandas, Scikit-learn, and Tensorflow, to ingest, explore, and prepare data for modeling and then train and evaluate models using a wide variety of techniques. Those techniques include linear regression with ordinary least squares, logistic regression, support vector machines, decision trees and ensembles, clustering, principal component analysis, hidden Markov models, and deep learning.

Oct 19th 2026
5-12 Weeks
Introduction to Digital Transformation (Coursera) Coursera
Siemens

Introduction to Digital Transformation (Coursera)

This course is primarily for professionals, college students, and advanced high school students who are interested in driving the digital transformation by integrating automation, software, and cutting-edge technologies. This course represents a foundational introduction to Digital Transformation, appropriate for learners with a basic familiarity with common business terms and concepts and an interest in digital technology.

Oct 19th 2026
5-12 Weeks
Data Processing with Azure (Coursera) Coursera
LearnQuest

Data Processing with Azure (Coursera)

This Azure training course is designed to equip students with the knowledge need to process, store and analyze data for making informed business decisions. Through this Azure course, the student will understand what big data is along with the importance of big data analytics, which will improve the students mathematical and programming skills. Students will learn the most effective method of using essential analytical tools such as Python, R, and Apache Spark.

Oct 19th 2026
3 Weeks
Machine Learning for All (Coursera) Coursera
University of London

Machine Learning for All (Coursera)

Machine Learning, often called Artificial Intelligence or AI, is one of the most exciting areas of technology at the moment. We see daily news stories that herald new breakthroughs in facial recognition technology, self driving cars or computers that can have a conversation just like a real person. Machine Learning technology is set to revolutionise almost any area of human life and work, and so will affect all our lives, and so you are likely to want to find out more about it.

Oct 19th 2026
4 Weeks
Big Data Science with the BD2K-LINCS Data Coordination and Integration Center (Coursera) Coursera
Icahn School of Medicine at Mount Sinai

Big Data Science with the BD2K-LINCS Data Coordination and Integration Center (Coursera)

In this course we briefly introduce the DCIC and the various Centers that collect data for LINCS. We then cover metadata and how metadata is linked to ontologies. We then present data processing and normalization methods to clean and harmonize LINCS data. This follow discussions about how data is served as RESTful APIs. Most importantly, the course covers computational methods including: data clustering, gene-set enrichment analysis, interactive data visualization, and supervised learning. Finally, we introduce crowdsourcing/citizen-science projects where students can work together in teams to extract expression signatures from public databases and then query such collections of signatures against LINCS data for predicting small molecules as potential therapeutics.

Oct 19th 2026
5-12 Weeks
Building Systems with the ChatGPT API (DeepLearning.AI) Other Providers
DeepLearning.AI

Building Systems with the ChatGPT API (DeepLearning.AI)

Level up your use of LLMs. Learn to break down complex tasks, automate workflows, chain LLM calls, and get better outputs. In Building Systems With The ChatGPT API, you will learn how to automate complex workflows using chain calls to a large language model. Unlock new development capabilities and improve your efficiency in this brand new short course.

Self Paced
Self-Paced