Details

The Artificial Intelligence and Machine Learning Suite will prepare you with a practical knowledge foundation of key definitions, applications, processes, techniques, and more, enabling you to sharpen your knowledge and skills in the fields of AI and machine learning.

Introduction to Artificial Intelligence

This course will introduce you to various forms of artificial intelligence (AI) and how we interact with AI as consumers in applications like chatbots and recommendation engines. You will see how AI provides analytics in business and consider industries that may be transformed or even disrupted by AI implementations. Next, you will go under the hood to see how computers can "learn" using artificial neural networks and various forms of machine learning. You will review AI applications such as natural language processing, forecasting, and robotics. You will also learn about the AI development process and how AI will affect the workforce. And lastly, you will consider some of the ethical factors in AI deployment.

Introduction to Machine Learning

Machine learning can be used to solve specific kinds of problems when key considerations in selecting data for a machine learning project are implemented properly. You will learn about specific techniques used in supervised, unsupervised, and semi-supervised learning, which applications each type of machine learning is best suited for, and the type of training data each requires.

You will also be able to differentiate offline and online training and predictions, automated machine learning, and how the cloud environment affects machine learning functions. Finally, you will explore some of the most significant areas in the very active area of machine learning research.

Suite bundles are not eligible for partial drops or refunds. Transfers to other open sessions of the same course are available. Please refer to your school for additional details regarding drops, transfers, and refunds on Suite bundles. Courses should be taken two months apart to avoid overlapping.

Syllabus