Machine Learning and its Applications

$49
ENROLL NOWCourse Overview
One of the most important applications of AI in engineering is classification and regression using machine learning. After taking this course, students will have a clear understanding of essential concepts in machine learning, and be able to fluently use popular machine learning techniques in science and engineering problems via MATLAB. Among the many machine learning methods, only those with the best performance and are widely used in science and engineering are carefully selected and taught. To avoid students getting lost in details, in contrast to teaching machine learning methods one by one, the first two lectures display the global picture of machine learning, making students clearly understand essential concepts and the working principle of machine learning. Data preparation is then introduced, followed by two popular machine learning methods, support vector machines and artificial neural networks. Practical cases in science and engineering are provided, making sure students have the ability to apply what they have learned in real practice. In addition, MATLAB classification and regression apps, which allow easy access to many machine learning methods, are introduced. In partnership with MathWorks, enrolled students have access to MATLAB for the duration of the course.
Course FAQs
What are the prerequisites for 'Machine Learning and its Applications'?
Prerequisites for this continuing education class are set by University of Glasgow. Most professional development online classes benefit from some prior knowledge. Please check the provider's page for specific requirements.
Will I receive a certificate for this CE class?
Yes, upon successful completion, University of Glasgow typically offers a shareable certificate to showcase your new skills and fulfill your continuing education requirements.
How long does this online course take to complete?
Completion times for online continuing education courses vary. The provider's website will have the most accurate estimate of the time commitment needed.





