Differences between Kanban and Scrum.
Outcome: Knowledge about Agile Methodologies

Learn about Cloud SQL, a fully-managed MySQL/PostgreSQL/SQL Server offering. Learn how to set it up in a few steps

Learn about Cloud Datastore, a NoSQL offering which serves both as a document store and as a Key Value store.

Google Compute Engine lets you create and run virtual machines on Google infrastructure. Compute Engine offers scale, performance, and value that allows you to easily launch large compute clusters on Google's infrastructure. There are no upfront investments and you can run thousands of virtual CPUs on a system that has been designed to be fast, and to offer strong consistency of performance: see this content for more details.

GCP introduction and documentation

Learn about GCP main topics, such as Storage, Compute and Security

Building great solutions requires having the right tools for the job. With Google Cloud Platform (GCP), you have many different tools at your disposal. In this session, you'll get an overview of GCP offerings, including storage options, ways to make use of and protect your data, and getting started with machine learning. You'll get answers to questions like: How do I get a Virtual Machine? What NoSQL solutions are available? Where do I open a firewall port?

A beginner's guide to Spark in Python based on 9 popular questions, such as how to install PySpark in Jupyter Notebook and best practices

Understand Spark basics: Spark Core and RDDs

You’ll learn how to use Spark to work with big data and build machine learning models at scale, including how to wrangle and model massive datasets with PySpark. Learn about big data and how Spark fits into the big data ecosystem. Practice processing and cleaning datasets to get comfortable with Spark’s SQL and dataframe APIs. Debug and optimize your Spark code when running on a cluster. Use Spark’s Machine Learning Library to train machine learning models at scale.