Course summary

1. Course summary

This brings us to the end of the Innovating with Google Cloud Artificial Intelligence course, let's do a quick recap. In the first section of the course titled AI and ML fundamentals, you explored the difference between artificial intelligence and machine learning. How machine learning differs from data analytics and business intelligence, different types of problems that AI solutions are suited to solve. The importance of using high quality data for machine learning, and the importance of responsible and explainable AI. And in the second section of the course titled Google Cloud's AI and ML solutions. You learnt about BigQuery ML, Pre-trained APIs, AutoML and custom models, which are both part of Vertex AI. Tensorflow, existing AI solutions and what you should consider when choosing a Google Cloud AI or ML solution. Now that you've had a comprehensive introduction to artificial intelligence and machine learning on Google Cloud. You can move on to the next course in the series, Modernize Infrastructure and Applications with Google Cloud. Where you'll learn about, why modernization and migration to the cloud is an important step in an organization transformation journey. Options for and advantages of running compute workloads in the cloud. Using containers and serverless computing in application modernization, the business value of application programming interfaces, APIs. And the business reasons for choosing hybrid or multi-cloud strategies, we'll see you next time.

2. Let's practice!

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