This learning path explores the core concepts of machine learning, the models available, and how to train them. We’ll take a deeper look at what it means to train a machine learning model, as well as the data and methods required to do so. We’ll also provide an overview of the most common models you’re likely to encounter, and take a practical approach to understand when and how to use them to solve business problems. We then do a structured walkthrough on a series of case studies that will show you how to apply the concepts covered in this course to real-life examples.

We then try out the concepts covered in the course with practical labs. 

Learning Objectives

• Understand the key concepts and models related to machine learning
• Learn how to use training data sets with machine learning models
• Learn how to choose the best machine learning model to suit your requirements
• Understand how machine learning concepts can be applied to real-world scenarios in property prices, health, animal classification, and marketing activities

Intended Audience

This learning path is intended for anyone who is:

• Interested in understanding machine learning models on a deeper level
• Looking to enrich their understanding of machine learning and how to use it to solve complex problems
• Looking to build a foundation for continued learning in the machine learning space and data science in general

Prerequisites

To get the most out of this learning path, you should have a general understanding of data concepts as well as some familiarity with cloud providers and their managed services, especially Amazon or Google. Some experience in data or development is preferable but not essential.

Feedback

If you have any feedback relating to this course, feel free to contact us at support@cloudacademy.com.