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https://github.com/GoogleCloudPlatform/edu-resources

Curated List of GCP educational resources http://goo.gle/google-cloud-edu
https://github.com/GoogleCloudPlatform/edu-resources

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Curated List of GCP educational resources http://goo.gle/google-cloud-edu

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# Curated List of GCP educational resources



## Online Courses



- [Coursera GCP courses](https://www.coursera.org/courses?query=gcp) Courses provided by both Google and other institutions that use GCP. [Eligible faculty and students](https://edu.google.com/programs/credits/faqs) can get free access to 13 of the Google courses though the [Training Credits Program](https://edu.google.com/programs/credits/training).

- The [Machine Learning Crash Course](https://developers.google.com/machine-learning/crash-course/) series: An online public version of the internal training for Googlers which has expanded to a series of courses including problem framing, data prep, and testing & debugging, along with the original ML intro "crash course." Students get hands-on experience using Colab.



## Books



### Available on-line

- [Mining of Massive Datasets](http://mmds.org/) by Jure Leskovec, Anand Rajaraman, Jeff Ullman. A book to go with Stanford's CS 246 class.

- [Cloud Computing for Science and Engineering](https://cloud4scieng.org/) It's getting old (over 2 years) but has some useful background. See the [Chapters tab](https://cloud4scieng.org/chapters/).



### Not available on-line

- [Data Science on Google Cloud Platform](http://amzn.com/B0787L7RK3) by Valliappa (Lak) Lakshmanan. This book was distributed to SIGCSE 2019 attendees and has been used in various courses.



## Hands-on labs/tutorials



Codelabs are self-paced, hands-on tutorials. **Google codelabs** require a Google account but are always free whereas **Qwiklabs codelabs** do not require a Google account but generally have fees. [Eligible faculty and students](https://edu.google.com/programs/credits/faqs) can get free access to Qwiklabs though the [Training Credits Program](https://edu.google.com/programs/credits/training).



- [Google Cloud Platform codelabs](http://gcplab.me)

- [Other Google codelabs](http://g.co/codelabs)

- [Qwiklabs](http://google.qwiklabs.com) Along with individual codelabs, Qwiklabs also features _quests_, a logical grouping of labs organized as a "learning path."



## Notebooks

Jupyter notebooks are becoming extremely popular in many different classes, especially data science and machine learning.



- [Google Colab](http://colab.research.google.com) A hosting platform for notebooks that provides access to GPUs and TPUs, with numerous instructional notebooks on how to use Colab.

- [Kaggle](https://www.kaggle.com/docs/kernels#notebooks) Kaggle provides hosting of Juptyer notebooks and so much more. There are numerous public data sets, notebooks that provide [microcourses](https://www.kaggle.com/learn/overview) in numerous topics (such as Python, Machine Learning, and SQL) to help students, competitions, and the ability for faculty to run [their own competitions](https://www.kaggle.com/about/inclass/overview).

- [AI Platform Notebooks](https://cloud.google.com/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](https://cloud.google.com/datalab/docs/how-to/working-with-notebooks) Another GCP tool to provide a notebook server.

- [Seedbank](https://research.google.com/seedbank/) A collection of interactive Machine Learning examples, designed to be used in Colab.



## General Resources



- [Kaggle](https://www.kaggle.com/) A machine learning and contest management site with [public data sets](https://www.kaggle.com/datasets), data science contests, [learning materials for numerous topics](https://www.kaggle.com/learn/overview) (Python, Data science, ML, SQL, etc.), numerous tutorials (including [Titanic](https://www.kaggle.com/eraaz1/a-comprehensive-guide-to-titanic-machine-learning) and MNIST), and sample solutions. Also allows faculty to run [their own contests in class](https://www.kaggle.com/about/inclass/overview).

- [GCP student hackathon toolkit](http://goo.gle/hackathon-toolkit) Variety of GCP resources for hackathons.



## Videos



- [Google Cloud @ Hackathons](http://youtu.be/VP6e9HL9eUY) ~2.5-minute intro to Google Cloud for students

- [Google Cloud for Student Developers](http://goo.gle/GCPStudent) video series

- [GCP Essentials](https://www.youtube.com/playlist?list=PLIivdWyY5sqKh1gDR0WpP9iIOY00IE0xL) A series of 4-9 minute videos focusing on introductory level GCP, including topics such as compute options, serverless computing, machine learning, and data storage.

- [GCP YouTube channel](https://youtube.com/GoogleCloudPlatform) All other GCP videos & series



## Grants and other programs

The GCP higher education team offers various programs:



- [GCP teaching grants](https://edu.google.com/programs/credits/teaching/) GCP credits for your courses where grants are provided to faculty, teaching assistants, and students for the course duration.

- [GCP research grants](https://edu.google.com/programs/credits/research/) GCP credits as seed funding for a research project using GCP resources.

- [Qwiklabs credits & Coursera courses](https://edu.google.com/programs/credits/training/) Qwiklabs credits for individuals or courses as well as access to a number of Coursera courses.

- [Career readiness track/certification](http://g.co/edu/cloudready) We offer several certifications for students. Faculty are expected to complete the certification (100% of the costs are covered by Google) with the expectation they then mentor students through the program afterwards (50% of the exam costs are covered by Google).

- [Google AI/TensorFlow cash grants](http://bit.ly/tensorflow-rfp) If you're developing an AI/ML course featuring TensorFlow 2.0 & Keras, these **cash grants** are meant to help you fund development of those teaching materials. Special consideration given to proposals targeting underrepresented groups in Computer Science. _Apply by_ ___2020 Oct 30___



Here's a quick comparison chart for many of those programs:



![comparison of above edu programs](https://user-images.githubusercontent.com/1102504/59053652-c377b000-8846-11e9-90c2-70875c1c7f21.png)



## Solutions and Course Materials



There are many faculty who share much of their course material online. These include the following:

- [The Database Whisperer](https://github.com/hymanphd-database-whisperer) Materials to go with Harvey Hyman's ISM 4212 course at USF.

- [ART350 video experimentation toolkit](https://github.com/realtechsupport/ActionCameraCode) Materials from the Department of Art at the University of Buffalo.

- [Repo of Cloud Computing curriculum resources](https://github.com/cloudcomputingcurricula/Cloud-Computing-Curricula) A repo of a variety of cloud computing teaching resources.



## Slide Decks



- [Google Cloud @ Hackathons](http://bit.ly/2KqGfzh) slide deck for quick student video intro to Google Cloud (see above)

- _(more coming soon)_



## Other public clouds

This repo is focused on GCP, but below are resources to consider when working with other public clouds.



- [Know AWS? Compare to GCP](https://cloud.google.com/docs/compare/aws/) — 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.