- Coursera GCP courses Courses provided by both Google and other institutions that use GCP. Eligible faculty and students can get free access to 13 of the Google courses though the Training Credits Program.
- The Machine Learning Crash Course Originally, an on-line public version of the training for Google engineers, this has expanded to numerous classes including problem framing, data prep, and testing and debugging. Students get hands-on experience using Colab. Along with the basic course, there are 5 specialized courses, practica, guides, and a glossary.
- Mining of Massive Datasets by Jure Leskovec, Anand Rajaraman, Jeff Ullman. A book to go with Stanford's 246 class.
- Cloud Computing for Science and Engineering It's getting old (over 2 years), but has some useful background. See the Chapters tab.
- Data Science on Google Cloud Platform by Valliappa (Lak) Lakshmanan. This book was distributed to attendees of SIGCSE 2019 and has been useful in a number of classes since then.
Codelabs and Qwiklabs are self-paced, hands-on tutorials. Codelabs require students to have their own GCP account whereas Qwiklabs provide a new account for the student for each lab. Eligible faculty and students can get free access to Qwiklabs though the Training Credits Program.
- GCP codelabs
- Other Google codelabs
- Qwiklabs Along with individual labs, Qwiklabs provides Quests, groupings of individual labs that make sense together.
Jupyter notebooks are becoming extremely popular in many different classes, especially data science and machine learning.
- Google Colab A hosting platform for notebooks that provides access to GPUs and TPUs, with numerous instructional notebooks on how to use Colab.
- Kaggle Kaggle provides hosting of Juptyer notebooks and so much more. There are numerous public data sets, notebooks that provide microcourses in numerous topics (such as Python, Machine Learning, and SQL) to help students, competitions, and the ability for faculty to run their own competitions.
- AI Platform Notebooks An enterprise notebook solution that interfaces quickly and easily with GCP tools such as BigQuery, Cloud Dataproc, and Cloud Dataflow.
- Cloud Datalab Another GCP tool to provide a notebook server.
- Seedbank A collection of interactive Machine Learning examples, designed to be used in Colab.
- Kaggle A WWW site with public data sets, data science contests, learning materials for numerous topics (Python, Data science, ML, SQL, etc.), numerous tutorials (including Titanic and MNIST), and sample solutions. Also allows faculty to run their own contests in class.
- GCP hackathon toolkit (https://github.com/GoogleCloudPlatform/hackathon-toolkit) Variety of GCP resources for hackathons.
- GCP Essentials A series of 4 to 9 minute videos focusing on introductory level GCP, including topics such as compute options, serverless computing, machine learning, and data storage. There are currently 8 videos, but they seems to add 1 per month.
GCP has a number of different grant programs, listed below.
Here's a quick comparison of those programs.
There are many faculty who share much of their course material online. These include the following:
- The Database Whisperer Materials to go with Harvey Hyman's ISM 4212 course at USF.
- ART350 video experimentation toolkit Materials from the Department of Art at the University of Buffalo.
- Repo of Cloud Computing curriculum resources A repo of a variety of cloud computing teaching resources.
(coming soon)
This repo is focused on GCP, but below are resources to consider when working with other public clouds.
- Know AWS? Compare to GCP — This section in the GCP documentation is for you if you're familiar with using AWS and want to discover the equivalent tools on GCP. There are also specific drilldowns found at the bottom should you want to get more product-level comparisons.