Machine Learning
This course focuses on using machine learning, which is concerned with algorithms that transform information into actionable intelligence.
What you can learn.
- Learn how to collect data and explore and prepare the data for the machine learning algorithm
- Learn how to select the appropriate machine learning algorithm for the data and proposed task
- Learn how to train a model, and evaluate and improve the model performance
About this course:
This course focuses on machine learning, which is concerned with algorithms that transform information into actionable intelligence. This field is made possible due to the rapid and simultaneous evolution of available data, statistical methods, and computing power. Students learn the origins and practical applications of machine learning, how knowledge is defined and represented by computers, and the basic concepts that differentiate machine learning approaches. Machine learning algorithms can be divided into two main groups: supervised learners that are used to construct predictive models and unsupervised learners that are used to build descriptive models. Students learn the classification, numeric predictor, pattern detection, and clustering algorithms. Students learn to train a model, evaluate its performance, and improve its performance. Algorithm uses are illustrated with real-world cases, such as breast cancer diagnosis, spam filtering, identifying bank loan risk, predicting medical expenses, estimating wine quality, identifying groceries frequently purchased together, and finding teen market segments.Spring 2021 Schedule
Available Format(s):
These courses are fully online and have no regular meeting times.
Enrollment limited. Enrollment deadline: April 4, 2021. Internet access required. Materials required.
These courses have regular meeting times and are fully online, via remote instruction. Click “See Details” below for more information.
Enrollment limited. Enrollment deadline: April 7, 2021. Internet access required. Materials required.
Available Format(s):
These courses are fully online and have no regular meeting times.
Enrollment limited. Enrollment deadline: June 27, 2021. Internet access required. Materials required.
These courses have regular meeting times and are fully online, via remote instruction. Click “See Details” below for more information.
Enrollment limited. Enrollment deadline: June 30, 2021. Internet access required. Materials required.
This course applies towards the following certificates & specializations…
Corporate Education
Learn how we can help your organization meet its professional development goals and corporate training needs.
Donate to UCLA Extension
Support our many efforts to reach communities in need.