Tech Resources for Academic Communities

Overview

Tech Resources for Academic Communities

The content and the code in this repo are intended for computer science instruction as a collaboration with Microsoft developer advocates and Faculty / Students under the MIT license. Please check back regularly for updated versions.

Source: https://github.com/microsoft/AcademicContent

This repo provides technical resources to help students and faculty learn about Azure and teach others. The content covers cross-platform scenarios in AI and machine learning, data science, web development, mobile app dev, internet of things, and DevOps. It also includes interesting tech talks and engaging, fun tech challenges that Microsoft leads at student hackathons and Imagine Cup.

Important: We are migrating to Microsoft Learn | If you can't find what you're looking for in this repo, check out the labs on Microsoft Learn too. Many of these labs have their own built-in Azure sandbox making it easier for faculty and students to learn without requiring an Azure Subscription.

Students can get free Azure credits to explore these resources here:

  • Azure for Students | $100 in Azure for 12 months with free tier of services - no credit card required with academic verification
  • Azure for Students Starter | use select Azure products like App Services for free - no credit card required with academic verification
  • Azure Free Account | $200 in Azure for one month with free tier of services - requires a credit card and probably the best fit for faculty evaluating Azure for course instruction unless your organization has a grant or enterprise agreement.

Your feedback is appreciated - please fork this repo and contribute!

To report any issues, please log a GitHub issue. Include the content section, module number, and title, along with any error messages and screenshots.

Learn by doing with our hands-on labs

Check out our hands-on labs that can be used on your own or in the classroom. They also make for fun, easy-to-run workshops!

Lab Categories Description
AI and Machine Learning Build bots and apps backed by AI and ML using Azure and Azure Cognitive Services.
Azure Services Deploy serverless code with Azure Functions, run Docker containers, use Azure to build Blockchain networks and more.
Big Data and Analytics Spin up Apache Spark Clusters, Use Hadoop to extract information from big datasets or use Power BI to explore and visualize data.
Deep Learning These labs build on each other to introduce tools and libraries for AI. They're labeled 200-400 level to indicate level of technical detail.
Internet-of-Things Use Azure to collect and stream IoT data securely and in real time.
Web Development Quickly create scalable web apps using Node, PHP, MySQL on easy-to-use tools like Visual Studio Code and GitHub.
Web Development for Beginners, 24 lessons A curriculum with 24 lessons, assignments and five projects to build. Covers HTML, CSS and JavaScript. Also includes Pre- and Post- Quizzes. Made with teachers in mind, or as self paced learning
Machine Learning for Beginners, 25 lessons A curriculum with 25 lessons with assignments covering classic Machine Learning primarily using Scikit-learn. Covers Regression, Classification, Clustering, NLP, Time Series Forecasting, and Reinforcement Learning, with two Applied ML lessons. Also includes 50 Pre- and Post- Quizzes. Made with teachers in mind, or as self paced learning
IoT for Beginners, 24 lessons A curriculum with 24 lessons with assignments all about the Internet of Things. The projects cover the journey of food from farm to table. This includes farming, logistics, manufacturing, retail and consumer - all popular industry areas for IoT devices. Also includes Pre- and Post- Quizzes. Made with teachers in mind, or as self paced learning

Host great events and hacks

Want to host an event at your school? We can help with the resources below!

Resource
Events and Hacks These are keynotes and hack workshops that Microsoft has produced for student events. Feel free to use. Most slides also contain suggested demos and talk tracks. There's also pre-packaged coding challenge to help students explore machine learning.
Tech Talks One-off presentations on emerging or innovative tech topics with speakers notes and demos.

Other available academic resources

We also have other great educator content to help you use Azure in the classroom.

Resource
Scripts Scripts and templates built in PowerShell or BASH to help set up your classroom environment.
Azure Guides Discover what Azure technologies apply to different teaching areas.
Course Content Learning modules to complement existing course instruction. Includes presentations, speaker notes, and hands-on labs.

Attend our Reactor Workshops

We focus on developing high-quality content for all Cloud, Data Science, Machine Learning, and AI learners. Through workshops, tech talks, and hackathons hosted around the world, come learn and apply new skills to what you're interested in!

Resource
Reactor Workshops Content for our First Party Reactor Workshops can be found here.
Reactor Locations Find out schedules, learn more about each space, and see where we are opening a Reactor near you!

Content from other sources

Resource
Azure Architecture Center Cloud architecture guides, reference architectures, and example workloads for how to put the pieces of the cloud together
Microsoft AI School Content for students, developers and data scientists to get started and dive deep into the Microsoft AI platform and deep learning.
Microsoft Learn Hundreds of free online training by world-class experts to help you build your technical skills on the latest Microsoft technologies.
Technical Community Content Workshops from the community team.
Research case studies Case studies of faculty using Azure for Research collected by Microsoft Research. Submit your own Azure research stories here too!
Microsoft Research Data Sets Data sets shared by Microsoft Research for academic use.
Machine Learning Data Sets Data sets shared by Azure Machine Learning team to help explore machine learning.
MS MARCO Microsoft MAchine Reading COmprehension Dataset generated from real Bing user queries and search results.
IoT School Resources for learning about Azure IoT solutions, platform services and industry-leading edge technologies.
Azure IoT curriculum resources Hands on labs and content for students and educators to learn and teach the Internet of Things at schools, universities, coding clubs, community colleges and bootcamps
AI Labs Experience, learn and code the latest breakthrough AI innovations by Microsoft.
Channel9 Videos for developers from people building Microsoft products and services.

Structure of the docs part of this repository

This repository is designed to build a VuePress site that is hosted using GitHub Pages.

The content of this site lives in the docs folder. The main page is constructed from the README.md in that folder, and the side bar is made of the contents of the content folder.

Building the docs

To build these docs, you will need npm installed. Once you have this installed, install VuePress:

npm install vuepress

To build the docs, use the deploy.sh script. This script will build the docs, then push them to the gh-pages branch of a given fork of this project. You pass the GitHub user/org name to the script. This way you can test the build offline, then push to the parent as part of an automated script.

deploy.sh <org>

Contributing

We 💖 love 💖 contributions. In fact, we want students, faculty, researchers and life-long learners to contribute to this repo, either by adding links to existing content, or building content. Please read the contributing guide to learn more.

Owner
Microsoft
Open source projects and samples from Microsoft
Microsoft
State of the art Semantic Sentence Embeddings

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Code release of paper "Deep Multi-View Stereo gone wild"

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USC ISI VISTA Computer Vision 6 Feb 06, 2022
Open-source python package for the extraction of Radiomics features from 2D and 3D images and binary masks.

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This is a library for training and applying sparse fine-tunings with torch and transformers.

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Cambridge Language Technology Lab 37 Dec 30, 2022
Offical code for the paper: "Growing 3D Artefacts and Functional Machines with Neural Cellular Automata" https://arxiv.org/abs/2103.08737

Growing 3D Artefacts and Functional Machines with Neural Cellular Automata Video of more results: https://www.youtube.com/watch?v=-EzztzKoPeo Requirem

Robotics Evolution and Art Lab 51 Jan 01, 2023
Pytorch implementation of the paper "Topic Modeling Revisited: A Document Graph-based Neural Network Perspective"

Graph Neural Topic Model (GNTM) This is the pytorch implementation of the paper "Topic Modeling Revisited: A Document Graph-based Neural Network Persp

Dazhong Shen 8 Sep 14, 2022
A transformer model to predict pathogenic mutations

MutFormer MutFormer is an application of the BERT (Bidirectional Encoder Representations from Transformers) NLP (Natural Language Processing) model wi

Wang Genomics Lab 2 Nov 29, 2022
Using LSTM to detect spoofing attacks in an Air-Ground network

Using LSTM to detect spoofing attacks in an Air-Ground network Specifications IDE: Spider Packages: Tensorflow 2.1.0 Keras NumPy Scikit-learn Matplotl

Tiep M. H. 1 Nov 20, 2021
Official PyTorch implementation of "Edge Rewiring Goes Neural: Boosting Network Resilience via Policy Gradient".

Edge Rewiring Goes Neural: Boosting Network Resilience via Policy Gradient This repository is the official PyTorch implementation of "Edge Rewiring Go

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A Pytorch loader for MVTecAD dataset.

MVTecAD A Pytorch loader for MVTecAD dataset. It strictly follows the code style of common Pytorch datasets, such as torchvision.datasets.CIFAR10. The

Jiyuan 1 Dec 27, 2021
Implementation for the paper: Invertible Denoising Network: A Light Solution for Real Noise Removal (CVPR2021).

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A minimal implementation of face-detection models using flask, gunicorn, nginx, docker, and docker-compose

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Collection of generative models in Tensorflow

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Code and data for the paper "Hearing What You Cannot See"

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