Machine learning can be used to solve various kinds of problems when key considerations in data selection are correctly implemented. This informative course will enable you to learn about different techniques, algorithms, programming languages, and types of machine learning.
The Introduction to Machine Learning course will allow you to learn about specific techniques used in supervised, unsupervised, and semi-supervised learning, including which applications each type of machine learning is best suited for and the type of training data each requires.
You will discover how to differentiate offline and online training and predictions, automated machine learning, and how the cloud environment affects machine learning functions. Additionally, you will explore some of the most significant areas in the field of machine learning research.
Prerequisites:
The Intro to Machine Learning course will look to build on concepts learned within the Intro to AI course. However, students should still be able to take the ML course without the AI.
Requirements:
Hardware Requirements:
Software Requirements:
Other:
Instructional Material Requirements:
The instructional materials required for this course are included in enrollment and will be available online.