224 Online Short courses in Machine Learning

The Machine Learning course offered by Concordia University Montréal will cover topics like mining of frequent item sets, clustering, stream analysis, similarity search, machine learning and recommendation systems.

Students will receive an introduction to common machine learning (ML) algorithms and how each supports different learning types in AI fields in this Machine Learning Algorithms and Frameworks course at the University of Manitoba.

In this Introduction to TensorFlow in Python course offered by Data Camp you will learn he fundamentals of neural networks and how to build deep learning models using TensorFlow.

In this Supervised Learning in R - Classification course offered by Data Camp you will learn the basics of machine learning for classification.

In this Machine Learning for Marketing in Python course offered by Data Camp you will learn and implement Machine Learning use cases for Marketing in Python, from customer lifetime value, predicting churn to segmentation.

In this Feature Engineering for NLP in Python course offered by Data Camp you will learn techniques to extract useful information from text and process them into a format suitable for machine learning.

In this Feature Engineering for Machine Learning in Python course offered by Data Camp you will create new features to improve the performance of your Machine Learning models.

This Machine Learning Specialization offered by Coursera in partnership with Stanford is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. This beginner-friendly program will teach you the fundamentals of machine learning and how to use these techniques to build real-world AI applications. 

This Predicting CTR with Machine Learning in Python course at Data Camp will teach you how to implement basic models in Python so that you can see how to better optimize ads with machine learning.

EdX is an online learning platform trusted by over 12 million users offering the Quantum 301 - Quantum Computing with Semiconductor Technology Certificate in collaboration with Delft University of Technology (TU Delft) - DelftX.

In this Supervised Learning in R - Regression course offered by Data Camp you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.

In this Building Recommendation Engines with PySpark course offered by Data Camp you will learn tools and techniques to leverage your own big data to facilitate positive experiences for your users.

In this Machine Learning Scientist in Python course offered by Data Camp you will discover machine learning with Python and work towards becoming a machine learning scientist.

In this Bayesian Modeling with RJAGS course offered by Data Camp you will learn how to implement more advanced Bayesian models using RJAGS.

This Intro to Machine Learning course from Udacity will teach you the end-to-end process of investigating data through a machine learning lens, and you'll apply what you've learned to a real-world data set.

This Machine Learning course at the University of Waterloo is developed in partnership with the School of Continuing Studies at the University of Toronto.

Learn how Artificial Intelligence and Machine Learning can solve the most important challenges in your business or organization and fuel your career with this Artificial Intelligence - Machine Learning Solutions program at the University of Manitoba.

Participants in this Introduction to Artificial Intelligence and Machine Learning course at the University of Manitoba will learn the differences between these applications and how advances in these areas can be employed to solve a range of real-world business and organizational problems.

Build production-ready machine learning models with TensorFlow on Google Cloud Platform. This Advanced Machine Learning on Google Cloud course is offered by Coursera in partnership with Google Cloud. 

Throughout Intro to TensorFlow for Deep Learning course from Udacity you'll gain an intuitive understanding of neural networks without the dense jargon.