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
Simple Linear 2nd ODE Solver GUI - A 2nd constant coefficient linear ODE solver with simple GUI using euler's method

Simple_Linear_2nd_ODE_Solver_GUI Description It is a 2nd constant coefficient li

:) 4 Feb 05, 2022
Official pytorch implementation of "DSPoint: Dual-scale Point Cloud Recognition with High-frequency Fusion"

DSPoint Official pytorch implementation of "DSPoint: Dual-scale Point Cloud Recognition with High-frequency Fusion" Coming soon, as soon as I finish a

Ziyao Zeng 14 Feb 26, 2022
Exploration-Exploitation Dilemma Solving Methods

Exploration-Exploitation Dilemma Solving Methods Medium article for this repo - HERE In ths repo I implemented two techniques for tackling mentioned t

Aman Mishra 6 Jan 25, 2022
FEDn is an open-source, modular and ML-framework agnostic framework for Federated Machine Learning

FEDn is an open-source, modular and ML-framework agnostic framework for Federated Machine Learning (FedML) developed and maintained by Scaleout Systems. FEDn enables highly scalable cross-silo and cr

Scaleout 75 Nov 09, 2022
Robustness between the worst and average case

Robustness between the worst and average case A repository that implements intermediate robustness training and evaluation from the NeurIPS 2021 paper

CMU Locus Lab 16 Dec 02, 2022
Official code for 'Robust Siamese Object Tracking for Unmanned Aerial Manipulator' and offical introduction to UAMT100 benchmark

SiamSA: Robust Siamese Object Tracking for Unmanned Aerial Manipulator Demo video 📹 Our video on Youtube and bilibili demonstrates the evaluation of

Intelligent Vision for Robotics in Complex Environment 12 Dec 18, 2022
Fit Fast, Explain Fast

FastExplain Fit Fast, Explain Fast Installing pip install fast-explain About FastExplain FastExplain provides an out-of-the-box tool for analysts to

8 Dec 15, 2022
Official repository for HOTR: End-to-End Human-Object Interaction Detection with Transformers (CVPR'21, Oral Presentation)

Official PyTorch Implementation for HOTR: End-to-End Human-Object Interaction Detection with Transformers (CVPR'2021, Oral Presentation) HOTR: End-to-

Kakao Brain 114 Nov 28, 2022
Simplified interface for TensorFlow (mimicking Scikit Learn) for Deep Learning

SkFlow has been moved to Tensorflow. SkFlow has been moved to http://github.com/tensorflow/tensorflow into contrib folder specifically located here. T

3.2k Dec 29, 2022
Adversarial examples to the new ConvNeXt architecture

Adversarial examples to the new ConvNeXt architecture To get adversarial examples to the ConvNeXt architecture, run the Colab: https://github.com/stan

Stanislav Fort 19 Sep 18, 2022
StyleSwin: Transformer-based GAN for High-resolution Image Generation

StyleSwin This repo is the official implementation of "StyleSwin: Transformer-based GAN for High-resolution Image Generation". By Bowen Zhang, Shuyang

Microsoft 349 Dec 28, 2022
Modeling CNN layers activity with Gaussian mixture model

GMM-CNN This code package implements the modeling of CNN layers activity with Gaussian mixture model and Inference Graphs visualization technique from

3 Aug 05, 2022
PyTorch code for training MM-DistillNet for multimodal knowledge distillation

There is More than Meets the Eye: Self-Supervised Multi-Object Detection and Tracking with Sound by Distilling Multimodal Knowledge MM-DistillNet is a

51 Dec 20, 2022
[CVPR 2022] Deep Equilibrium Optical Flow Estimation

Deep Equilibrium Optical Flow Estimation This is the official repo for the paper Deep Equilibrium Optical Flow Estimation (CVPR 2022), by Shaojie Bai*

CMU Locus Lab 136 Dec 18, 2022
On Evaluation Metrics for Graph Generative Models

On Evaluation Metrics for Graph Generative Models Authors: Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham Taylor This is the offic

13 Jan 07, 2023
Six - a Python 2 and 3 compatibility library

Six is a Python 2 and 3 compatibility library. It provides utility functions for smoothing over the differences between the Python versions with the g

Benjamin Peterson 919 Dec 28, 2022
HTSeq is a Python library to facilitate processing and analysis of data from high-throughput sequencing (HTS) experiments.

HTSeq DEVS: https://github.com/htseq/htseq DOCS: https://htseq.readthedocs.io A Python library to facilitate programmatic analysis of data from high-t

HTSeq 57 Dec 20, 2022
A Simple Framwork for CV Pre-training Model (SOCO, VirTex, BEiT)

A Simple Framwork for CV Pre-training Model (SOCO, VirTex, BEiT)

Sense-GVT 14 Jul 07, 2022
OpenAi's gym environment wrapper to vectorize them with Ray

Ray Vector Environment Wrapper You would like to use Ray to vectorize your environment but you don't want to use RLLib ? You came to the right place !

Pierre TASSEL 15 Nov 10, 2022
SSD: A Unified Framework for Self-Supervised Outlier Detection [ICLR 2021]

SSD: A Unified Framework for Self-Supervised Outlier Detection [ICLR 2021] Pdf: https://openreview.net/forum?id=v5gjXpmR8J Code for our ICLR 2021 pape

Princeton INSPIRE Research Group 113 Nov 27, 2022