├── .vscode └── settings.json ├── AI & Advanced Analytics ├── img │ └── fitting.png ├── Non-Tech Stream │ ├── img │ │ ├── img01.png │ │ ├── img02.png │ │ └── img03.png │ ├── MSA-Bootcamp-13-April-Slides.pdf │ ├── Setting up Azure Machine Learning Studio │ │ ├── img │ │ │ ├── .DS_Store │ │ │ ├── img01.png │ │ │ ├── img02.png │ │ │ ├── img03.png │ │ │ ├── img04.png │ │ │ ├── img05.png │ │ │ ├── img06.png │ │ │ ├── img07.png │ │ │ ├── img08.png │ │ │ └── img09.png │ │ └── README.md │ ├── MNIST demo using Machine Learning Studio designer tool │ │ ├── img │ │ │ ├── img01.png │ │ │ ├── img02.png │ │ │ ├── img03.png │ │ │ ├── img04.png │ │ │ ├── img05.png │ │ │ ├── img06.png │ │ │ ├── img07.png │ │ │ ├── img08.png │ │ │ ├── img09.png │ │ │ ├── img10.png │ │ │ ├── img11.png │ │ │ ├── img12.png │ │ │ ├── img13.png │ │ │ ├── img14.png │ │ │ ├── img15.png │ │ │ ├── img16.png │ │ │ ├── img17.png │ │ │ ├── img18.png │ │ │ ├── img19.png │ │ │ ├── img20.png │ │ │ ├── img21.png │ │ │ ├── img22.png │ │ │ ├── img23.png │ │ │ ├── img24.png │ │ │ └── img25.png │ │ └── README.md │ └── Adding User to Workspace.md ├── Tech Stream │ ├── MSA-Bootcamp-14-April-Slides.pdf │ ├── Setting up Azure Notebook │ │ ├── img │ │ │ ├── .DS_Store │ │ │ ├── img01.png │ │ │ ├── img02.png │ │ │ ├── img03.png │ │ │ ├── img04.png │ │ │ ├── img05.png │ │ │ ├── img06.png │ │ │ ├── img07.png │ │ │ ├── img08.png │ │ │ ├── img09.png │ │ │ ├── img10.png │ │ │ ├── img11.png │ │ │ ├── img12.png │ │ │ ├── img13.png │ │ │ └── img06b.png │ │ └── README.md │ ├── MNIST demo using Azure Notebook │ │ └── README.md │ └── setting-up-local-environment.md └── README.md ├── Azure For Students ├── img │ ├── email-sign-in.png │ ├── your-credit.png │ ├── azure-homepage.png │ ├── email-verification.png │ ├── enter-and-verify.png │ ├── portal-home-page.png │ ├── phone-authentication.png │ ├── verification-options.png │ ├── azure-sponsorships-page.png │ ├── verify-student-status.png │ └── terms-and-conditions-agreement.png └── README.md ├── Workshops └── Git & GitHub │ ├── img │ ├── forking.png │ ├── pr-requests.png │ ├── commit-screen.png │ ├── making-new-pr.png │ ├── creating-a-repo.png │ ├── github-register.png │ ├── creating-new-repo.png │ ├── quick-setup-screen.png │ ├── cloning-existing-repo.png │ ├── creating-pull-requests.png │ └── pull-request-description.png │ ├── README.md │ ├── Git-handbook.md │ └── GitHub-Handbook.md ├── Azure & Cloud Fundamentals ├── Tech Stream │ └── Project Walkthrough │ │ └── azure-iot-samples-python-master.zip ├── An Introduction to Cloud Computing.md └── README.md ├── README.md └── Web App & APIs └── README.md /.vscode/settings.json: -------------------------------------------------------------------------------- 1 | { 2 | "git.ignoreLimitWarning": true 3 | } -------------------------------------------------------------------------------- /AI & Advanced Analytics/img/fitting.png: -------------------------------------------------------------------------------- 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Analytics/Non-Tech Stream/Adding User to Workspace.md: -------------------------------------------------------------------------------- 1 | # Adding User to Workspace 2 | 3 | In this tutorial we will teach you how to add user to workspace. 4 | 5 | 1. Go to settings tab on your workspace 6 | 7 | ![img01.png](img/img01.png) 8 | 9 | 10 | 2. Click on invite more users button at the bottom 11 | 12 | ![img02.png](img/img02.png) 13 | 14 | 15 | 3. Type in mail ID of user and click ok at the right bottom – Azure will send the mail to user to sign up 16 | 17 | ![img03.png](img/img02.png) -------------------------------------------------------------------------------- /AI & Advanced Analytics/Tech Stream/MNIST demo using Azure Notebook/README.md: -------------------------------------------------------------------------------- 1 | # MNIST demo using Azure Notebook 2 | In this tutorial we will be using Azure Notebook for the MNIST training demonstration. 3 | 4 | ## SSH Setup 5 | When we are creating our compute on AzureML, we want to enable SSH access, just incase we need it. [Here](https://github.com/beauwilliams/MSA-AUS-2020-AzureML/blob/master/Notes/SSHSetup.md) is the tutorial for setting up SSH access to your compute (Mac/Linux users only, Windows users please refer to this [tutorial](https://docs.microsoft.com/en-gb/azure/virtual-machines/linux/ssh-from-windows)). 6 | 7 | ## ZSH Users 8 | When running a command such as 9 | 10 | `pip install --upgrade azureml-sdk[notebooks,contrib] scikit-image tensorflow tensorboardX --user` 11 | 12 | You will get the error 13 | 14 | `zsh: no matches found: azureml-sdk[notebooks,contrib]` 15 | 16 | This is due to ZSH globbing function. In order to fix it, please refer to this [tutorial](https://github.com/beauwilliams/MSA-AUS-2020-AzureML/blob/master/Notes/Links.md). 17 | 18 | ### Click [here](https://github.com/Azure/MachineLearningNotebooks/tree/master/tutorials/image-classification-mnist-data) for the ipynb file. 19 | 20 | ### Click [here](https://github.com/beauwilliams/MSA-AUS-2020-AzureML) for more resources. 21 | -------------------------------------------------------------------------------- /AI & Advanced Analytics/Tech Stream/setting-up-local-environment.md: -------------------------------------------------------------------------------- 1 | ## Machine Learning Set-up Guide 2 | 3 | For your machine learning projects, you first have to set-up your environment. These environment is essentially the necessary libraries and packages you are going to use during your machine learning projects. In order to do that you can either use Virtual Environments or use a package manager such as Miniconda. we highly recommend the latter approach. 4 | 5 | Here are is an article what Miniconda is and how to setup your Machine Learning Environment using it. We advise you to read the articles properly to understand what's happening as we **would not** be individually helping everyone to set up their environment. 6 | 7 | 1. [Windows users](https://realpython.com/python-windows-machine-learning-setup/) 8 | 2. [MacOS/Linux users](https://towardsdatascience.com/get-your-computer-ready-for-machine-learning-how-what-and-why-you-should-use-anaconda-miniconda-d213444f36d6) - (Open in Incognito/Private Window if necessary) 9 | 10 | We emphasize again, that this is only one way of doing it and there are many other resources available online and encourage it to troubleshoot if you're having any problems. 11 | 12 | Once you have set-up the local environment, you would probably need a IDE or text editor for your coding and we recommend checking out [Visual Studio Code](https://code.visualstudio.com/) which is an free source-code editor with lots of useful built-in tools. -------------------------------------------------------------------------------- /AI & Advanced Analytics/Non-Tech Stream/Setting up Azure Machine Learning Studio/README.md: -------------------------------------------------------------------------------- 1 | # Setting up Azure Machine Learning Studio 2 | ## Create a workspace 3 | An Azure Machine Learning workspace is a foundational resource in the cloud that you use to experiment, train, and deploy machine learning models. It ties your Azure subscription and resource group to an easily consumed object in the service. 4 | 5 | You create a workspace via the Azure portal, a web-based console for managing your Azure resources. 6 | 7 | 1. Sign in to [Azure portal](https://portal.azure.com/#home) by using the credentials for your Azure subscription. 8 | ![img01](img/img01.png) 9 | 10 | 2. In the upper-left corner of Azure portal, select + Create a resource. 11 | ![img02](img/img02.png) 12 | 13 | 3. Use the search bar to find Machine Learning and select **Machine Learning Studio (classic) Workspace**. 14 | ![img03](img/img03.png) 15 | 16 | 4. In the Machine Learning Studio (classic) Workshpace pane, select Create to begin. 17 | ![img04](img/img04.png) 18 | 19 | 5. Provide the following information to configure your new workspace. After you are finished configuring the workspace, select **Create**. **Please note that it can take several minutes to create your workspace in the cloud.** 20 | ![img05](img/img05.png) 21 | 22 | 6. Please wait for several minutes to create your workspace in the cloud. 23 | ![img06](img/img06.png) 24 | 25 | 7. To view the new workspace, select **Go to resource**. 26 | ![img07](img/img07.png) 27 | 28 | 8. To launch Machine Learning Studio, please select **Launch Machine Learning Studio (classic)** 29 | ![img08](img/img08.png) 30 | 31 | 9. Congratulations! You can now access your own Machine Learning Studio. 32 | ![img09](img/img09.png) -------------------------------------------------------------------------------- /Azure For Students/README.md: -------------------------------------------------------------------------------- 1 | # Azure For Students 2 | ## Introduction 3 | 4 | Get a $100 credit when you create your Azure free account 5 | 6 | ## Getting started 7 | 8 | Visit Azure For Students Home Page: 9 | 10 | https://azure.microsoft.com/en-us/free/students/ 11 | 12 | Click 'Activate Now' 13 | 14 | ![azure-home-page](img/azure-homepage.png) 15 | 16 | Sign in with your existing microsoft account 17 | 18 | ![email-sign-in](img/email-sign-in.png) 19 | 20 | Choose 'School email address' on the verification method drop down list. 21 | 22 | ![verify-student-status](img/verification-options.png) 23 | 24 | Enter your School email address and choose 'Verify and claim your offer' 25 | 26 | ![enter-and-verify](img/enter-and-verify.png) 27 | 28 | You should receive an email like the one below, navigate to the link. 29 | ![email-verification](img/email-verification.png) 30 | 31 | Enter your phone number, you will recieve a verification code. Enter it in the respective text field. 32 | ![phone-verification](img/phone-authentication.png) 33 | 34 | Once your code has been successfully verified, Read and accept the terms and conditions to proceed. 35 | ![terms-and-conditions-agreement](img/terms-and-conditions-agreement.png) 36 | 37 | After clicking 'Sign up' you will be able navigated to the azure portal home page. Go through the tutorial if you are new to azure to familiarise yourself with azure's capability. 38 | ![portal-home-page](img/portal-home-page.png) 39 | 40 | Visit [Azure Sponsorships Page](http://www.microsoftazuresponsorships.com) and click 'Check your Balance' to view your azure credit balance. 41 | 42 | ![azure-sponsorships-page](img/azure-sponsorships-page.png) 43 | ![your-credit](img/your-credit.png) 44 | 45 | # Congratulations 46 | 47 | You have now successfully activated azure for students. 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | 56 | 57 | 58 | 59 | 60 | 61 | 62 | 63 | 64 | 65 | 66 | -------------------------------------------------------------------------------- /AI & Advanced Analytics/Tech Stream/Setting up Azure Notebook/README.md: -------------------------------------------------------------------------------- 1 | # Setting Up Azure Notebook 2 | 3 | In this tutorial, you complete the end-to-end steps to get started with the Azure Machine Learning Python SDK running in Jupyter notebooks. This tutorial will cover Python environment setup and configuration, as well as creating a workspace to manage your experiments and machine learning models. 4 | 5 | In this tutorial, you: 6 | 1. Create an Azure Machine Learning Workspace to use in the project. 7 | 2. Create a cloud-based compute instance with Azure Machine Learning Python SDK installed and pre-configured. 8 | 9 | ## Create a workspace 10 | An Azure Machine Learning workspace is a foundational resource in the cloud that you use to experiment, train, and deploy machine learning models. It ties your Azure subscription and resource group to an easily consumed object in the service. 11 | 12 | You create a workspace via the Azure portal, a web-based console for managing your Azure resources. 13 | 14 | 1. Sign in to [Azure portal](https://portal.azure.com/#home) by using the credentials for your Azure subscription. 15 | ![img01](img/img01.png) 16 | 17 | 2. In the upper-left corner of Azure portal, select + Create a resource. 18 | ![img02](img/img02.png) 19 | 20 | 3. Use the search bar to find Machine Learning and select "Machine Learning". 21 | ![img03](img/img03.png) 22 | 23 | 4. In the Machine Learning pane, select Create to begin. 24 | ![img04](img/img04.png) 25 | 26 | 5. Provide the following information to configure your new workspace. After you are finished configuring the workspace, select **Review** + **Create**. **Please note that it can take several minutes to create your workspace in the cloud.** 27 | ![img05](img/img05.png) 28 | 29 | 6. To view the new workspace, select **Go to resource**. 30 | ![img06](img/img06.png) 31 | 32 | 33 | ## Run notebook in your workspace 34 | 35 | 1. Sign in to [Azure Machine Learning studio](https://ml.azure.com/). 36 | 37 | 2. Select your subscription and the workspace you created. 38 | ![img06b](img/img06b.png) 39 | 40 | 3. Select Notebooks on the left and click on the "create new file". 41 | ![img07](img/img07.png) 42 | 43 | 4. Provide the following information to configure your new file. 44 | ![img08](img/img08.png) 45 | 46 | 5. Click on the "Create new compute". 47 | ![img09](img/img09.png) 48 | 49 | 6. Follow the configuration shown in the picture below. 50 | ![img10](img/img10.png) 51 | 52 | 7. Wait for several minutes to get the new compute ready. 53 | ![img11](img/img11.png) 54 | 55 | 8. Once the compute is ready , click on the "Edit" and "Edit in Jupyter". 56 | ![img12](img/img12.png) 57 | 58 | 9. Then you are ready to use Jupyter notebook in your workspace. 59 | ![img13](img/img13.png) 60 | -------------------------------------------------------------------------------- /Workshops/Git & GitHub/README.md: -------------------------------------------------------------------------------- 1 | # Git & GitHub 2 | 3 | ## Introduction 4 | 5 | Git is officially defined as a "distributed version control system" (VCS). 6 | 7 | In other words, it's a system that tracks changes to our project files over time. It enables us to record project changes and go back to a specific version of the tracked files, at any given point in time. This system can be used by many people to efficiently work together and collaborate on team projects, where each developer can have their own version of the project, distributed on their computer. 8 | 9 | GitHub is a hosting platform for Git repositories. You can use Git on its own without Github (and other similar platforms), but it's difficult to collaborate or share your code with. others. 10 | 11 | ## Benefits of GitHub (especially as a student) 12 | 1. Industry recognised platform to showcase your projects. 13 | 2. Very easy to contribute to open source projects. 14 | 3. Most companies use Git & GitHub to manage projects. 15 | 4. Often actively asked for in job descriptions & interviews. 16 | 5. Can be a free online backup for personal projects & work so mitigates the risk of losing them. 17 | 18 | 19 | >> If you're already familiar with Git, GitHub and want to get started with open source contributions straight away then feel free to skip to that section. 20 | 21 | 22 | ## Getting Started with Git 23 | 24 | We have put together a in-depth guidelines for setting up Git and using the main functionalities. Please click the below link to visit it. 25 | 26 | - [Git Handbook](Git-handbook.md) 27 | 28 | 29 | ## Getting Started with GitHub 30 | GitHub is like Robin to your Batman or Bonnie to your Clyde. Follow the guidelines below and supercharge your Git powers. 31 | - [GitHub Handbook](GitHub-Handbook.md) 32 | 33 | 34 | ## How to make open source contributions 35 | 36 | You don't always have to code to contribute to open source projects. Checkout the article below for more details. The general method of contributing to open source contributions is to [fork the project](https://github.com/AUMSA/2020-MSA-content/blob/master/Workshops/Git%20&%20GitHub/GitHub-Handbook.md#forking-projects-on-github), [commit your changes](https://github.com/AUMSA/2020-MSA-content/blob/master/Workshops/Git%20%26%20GitHub/Git-handbook.md#staging--commiting) into your forked repo and then [open a pull-request](https://github.com/AUMSA/2020-MSA-content/blob/master/Workshops/Git%20&%20GitHub/GitHub-Handbook.md#creating-a-pull-req) of the developers to review. If you're familiar with any of the steps then click of the hyperlinks. 37 | 38 | Checkout the following article, it not only describes it further but also lists different ways to contribute to open source: https://opensource.guide/how-to-contribute/ 39 | 40 | 41 | ## Activity 42 | Done reading the guides and want to get your hands dirty. Here's a GitHub "Hello World" to start the magical world of GitHub 43 | 44 | - [GitHub Hello World](https://guides.github.com/activities/hello-world/) 45 | 46 | 47 | ## Git & Beyond 48 | 49 | - **Host your website** - **GitHub Pages** is a popular service for hosting web pages via GitHub. You can learn more about it here: https://guides.github.com/features/pages/ 50 | 51 | - **Share code & notes** GitHub also allows you to easily share your code, notes or other snippets through GitHub Gist: https://gist.github.com/ 52 | 53 | ## Offical Docs 54 | - You can find the offical GitHub Documentation here: https://help.github.com/en 55 | - They also have official video guides which you can find on this link: https://www.youtube.com/githubguides 56 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Microsoft Student Accelerator Program Australia 2020 2 | *Welcome to **MSA Australia** official GitHub repository. Please note that all the instructions about MSA will be uploaded to this GitHub repository. However, don't forget to like our [Facebook page](https://www.facebook.com/msaaussie/) and join our [Facebook group](https://www.facebook.com/groups/235821840767124/) to stay up to date.* 3 | 4 | *MSA 2020 Handbook can be found [here](https://aka.ms/aumsaHandbook)* 5 | 6 | MSA Australia 2020 will cover 3 main topics: 7 | 1) [AI & Advanced Analytics](https://github.com/AUMSA/2020-MSA-content/tree/master/AI%20%26%20Advanced%20Analytics) 8 | 2) [Cloud Computing with Azure](https://github.com/AUMSA/2020-MSA-content/tree/master/Azure%20%26%20Cloud%20Fundamentals) 9 | 3) [Web App & APIs](https://github.com/AUMSA/2020-MSA-content/tree/master/Web%20App%20%26%20APIs) 10 | 11 | There would be one project for each topic. The detail of each project would be announced shortly in the respective GitHub Documentation. 12 | 13 | ## Microsoft Azure for Students 14 | An Azure account is required to start the program. If you do not have one, please [sign up](https://github.com/AUMSA/2020-Phase-1/tree/master/Azure%20For%20Students) for a free account (no credit card needed), and you will get $100 credit as well as 12 months of free Azure services. Find out more information [here](https://azure.microsoft.com/en-us/free/students/). 15 | 16 | ## Bootcamps & Supporting Workshops 17 | ### Bootcamps 18 | There are several bootcamps that will be run on Microsoft Teams. 19 | 1) [AI & Advanced Analytics](https://www.facebook.com/events/220234762372121/) 20 | - 13 April 2020 (Low/No code Approach 21 | - 14 April 2020 (Coding Approach 22 | 2) Cloud Computing with Azure 23 | - 20th May 2020 24 | 3) Web App & APIs 25 | - End of July 2020 26 | 27 | ### Supporting Workshops 28 | The MSA 2020 program will also host a series of complimenting workshops: 29 | 1) [Git & GitHub](https://github.com/AUMSA/2020-MSA-content/tree/master/Workshops/Git%20%26%20GitHub) 30 | 2) DevOps and Project Workflow 31 | 3) Presentation and Soft Skills 32 | 33 | > *To ensure all the bootcamps & workshops to be run smoothly, please **mute** your microphone as we will have a Q&A session at the end of the bootcamps.* 34 | 35 | ## MSA Assessments 36 | Each bootcamp will have one assessment to complete. Please read through the criteria on the respective GitHub documentation to get more information about respective assessment. 37 | 38 | ### Microsoft Learn 39 | Completing the modules on the [Microsoft learn platform](https://docs.microsoft.com/en-us/learn/) would significantly help you get better understanding of the topics covered in this program. 40 | The MSP's will outline which modules you have to do in the respective GitHub Documentaion. 41 | 42 | ### MSA Certificate 43 | In order to get MSA certificate, you **must**: 44 | 1. Pass at least two projects in this program; **and** 45 | 2. Complete the related Microsoft Learn modules (The MSP's will outline which modules you have to do in the respective GitHub Documentaion). 46 | 47 | ### Top MSA Students 48 | The top students with the most amount of points will be mentored by Microsoft professionals to participate in the [Microsoft Imagine Cup 2020](https://imaginecup.microsoft.com/en-us). 49 | 50 | We also have exclusive prizes up for grab for the top students. Based on the points accumulated, while top students can earn exclusive Microsoft swags and goodies, there are special prizes for the top 3 participants: 51 | 52 | 1. 1st place: Surface Book 2 53 | 2. 2nd place: Xbox One X 54 | 3. 3rd place: Surface Headphone 55 | 56 | -------------------------------------------------------------------------------- /Web App & APIs/README.md: -------------------------------------------------------------------------------- 1 | # MSA 2020 - Web App & APIs 2 | ## Table of Contents 3 | 4 | 1. [Introduction](#1-Introduction) 5 | 2. [Resources](#2-Resources) 6 | 3. [Assessment](#3-Assessment) 7 | 4. [Submission](#4-Submission) 8 | 5. [Deadline](#5-Deadline) 9 | 10 | ## 1. Introduction 11 | Welcome to the third and final bootcamp of the 2020 MSA program. We would like to wrap bootcamps up by giving you a taste building an interactive application which solves a particular problem or fulfills a need. In our tech career, it is a quite a handy skill to know how to materialize an idea into a real application. 12 | 13 | - [Non-Technical Stream](https://stdntpartners-my.sharepoint.com/:p:/g/personal/kaif_ahsan_studentambassadors_com/EfzLlfibDz1Bk09zd7eBzJ0B6aGbgVxXt9ylzD39gRErJw?e=1RTKha) 14 | - [Technical Stream](https://stdntpartners-my.sharepoint.com/:p:/g/personal/kaif_ahsan_studentambassadors_com/EW6tAm8CKEdKkWjgW7lJ4E4BJxpcX4tPS3kioWmMkMkT6g?e=WGDw0h) 15 | 16 | #### Low/No code Approach 17 | In the non-technical stream, we will be getting introduced to the Power Platform to create our professional apps without writing a single line of code. The Power Platform feature rich, versatile and easy to get started with. 18 | 19 | A crucial part of this project is not just create an app, but also understand for whom and why are we creating the application for. To achieve this we will be exploring a concept called 'Building a Persona'. This is a very important skill and a useful step to plan and design our software in the real life. 20 | 21 | #### Coding Approach 22 | In the technical stream, we will be learning not only how to create our interactive web apps, but also how to implement third party services through APIs as well as how to share our awesome work with the world through hosting it. To achieve this, we will be using HTML, Bootstrap & Flask to create our web application. 23 | 24 | Further, we will also see, how we can deploy our web service with a web hosting provider such as Azure for testing and sharing with the public through a URL. Participants are free to choose from Either HTML, Bootstrap and Flask or HTML, CSS and JavaScript to develop their application. However, we will focus using the former and the resources & demos will be targeted towards that. 25 | 26 | ## 2. Resources 27 | 28 | ### Low/No code Approach 29 | - [Creating A Canvas Power App](https://docs.microsoft.com/en-us/learn/paths/create-powerapps/) 30 | - [Microsoft PowerApps Documentation](https://docs.microsoft.com/en-us/powerapps/) 31 | - [Examples of Power Apps](https://powerusers.microsoft.com/t5/Community-App-Samples/bd-p/AppFeedbackGallery?sortby=kudos) 32 | 33 | External Resources: 34 | - https://www.avepoint.com/blog/office-365/microsoft-powerapps/ 35 | 36 | 37 | ### Coding Approach 38 | - [Creating a To-do App using Flask](https://github.com/JerryyZhu/todo_markdown) (Bootcamp Demo) 39 | - [AI web app by using Python and Flask](https://docs.microsoft.com/en-us/learn/modules/python-flask-build-ai-web-app/) 40 | - [Flask Mega Tutorial](https://blog.miguelgrinberg.com/post/the-flask-mega-tutorial-part-i-hello-world) 41 | - [Deploying a Flask app to Azure](https://www.youtube.com/watch?v=K_RTlbOOCts) 42 | 43 | Additional Resources: 44 | - [Setting up Flask for VS Code](https://code.visualstudio.com/docs/python/tutorial-flask) 45 | - [Official Flask documentation](https://flask.palletsprojects.com/en/1.1.x/tutorial/#tutorial) 46 | 47 | 48 | ## 3. Assessment 49 | To complete *Web App & APIs* bootcamp, you are required to compete these tasks. Please refer to stream specific guidelines below. 50 | 51 | ### Low/No code Approach 52 | **Microsoft Learn** - 25 53 | - [Creating a canvas app](https://docs.microsoft.com/en-us/learn/paths/create-powerapps/) 54 | - [Use UI and Controls in canvas app](https://docs.microsoft.com/en-us/learn/paths/ui-controls-canvas-app-powerapps/) 55 | 56 | **Project** - 75 57 | - [Project specification & marking rubric](https://stdntpartners-my.sharepoint.com/:w:/g/personal/kaif_ahsan_studentambassadors_com/EUbzKw4SBwNMqsT8eufOKJ8BjiR5tU6oCQ9tDUR_oK8sRQ?e=I7Xdo4) 58 | - [Project Submission Guide](https://stdntpartners-my.sharepoint.com/:w:/g/personal/kaif_ahsan_studentambassadors_com/EcVSzqJRTp1Nt15pLSD_UiEB3_OK2F1DSHiN7o8GALFMNw?e=i9Y4eg) 59 | 60 | ### Coding Approach 61 | **Microsoft Learn** - 10 Marks 62 | - [AI Web App using Python & Flask](https://docs.microsoft.com/en-us/learn/modules/python-flask-build-ai-web-app/) 63 | 64 | **Project** - 90 Marks 65 | - [Project specification & marking rubric](https://stdntpartners-my.sharepoint.com/:w:/g/personal/kaif_ahsan_studentambassadors_com/EXdnOeJnSoFIvVRL-JSgj2gB93NKBUcCrTBTbZ0gfzgCHA?e=PZb1fJ) 66 | - [Project Submission Guide](https://stdntpartners-my.sharepoint.com/:w:/g/personal/kaif_ahsan_studentambassadors_com/EfyYlZDMwJVCpQ8sAx3q8CcBc0U7W2p7k078oFh6DGmdgA?e=UsUqti) 67 | 68 | ## 4. Submission 69 | 70 | ### Low/No code Approach 71 | Review the submission guidelines again here: 72 | - [Submission Guidelines](https://stdntpartners-my.sharepoint.com/:w:/g/personal/kaif_ahsan_studentambassadors_com/EcVSzqJRTp1Nt15pLSD_UiEB3_OK2F1DSHiN7o8GALFMNw?e=i9Y4eg) 73 | 74 | > **Project Submission Link: ** https://aka.ms/MSAAusProjectSubmission 75 | 76 | ### Coding Approach 77 | Review the submission guidelines again here: 78 | - [Submission guidelines](https://stdntpartners-my.sharepoint.com/:w:/g/personal/kaif_ahsan_studentambassadors_com/EfyYlZDMwJVCpQ8sAx3q8CcBc0U7W2p7k078oFh6DGmdgA?e=UsUqti) 79 | 80 | > **Project Submission Link: ** https://aka.ms/MSAAusProjectSubmission 81 | 82 | Please read through the submission guidelines and ensured all criteria are met. 83 | 84 | ## 5. Deadline 85 | The deadline for this bootcamp is **11:59pm AEDT, 14th September, 2020.** 86 | 87 | #### Late Submissions 88 | For this bootcamp late submissions up to **11:59pm AEDT, 16th September, 2020. 11:59pm** is allowed. However there will be a **20%** penalty on the total grade. 89 | -------------------------------------------------------------------------------- /Azure & Cloud Fundamentals/An Introduction to Cloud Computing.md: -------------------------------------------------------------------------------- 1 | # An Introduction to Cloud Computing 2 | 3 | ## What actually is cloud computing? 4 | Simply put, it is the delivery of computing services throughout the Internet. These services include servers, storage, databases, networking, software, analytics and intelligence. Here are a few examples of what’s possible today with cloud services from a cloud provider: 5 | 1. Email 6 | 2. Storage, backup, and data retrieval 7 | 3. Creating and testing apps 8 | 4. Analysing data 9 | 5. Audio and video streaming 10 | 6. Delivering software on demand 11 | 12 | ## Why cloud computing? 13 | Many organisations are turning to cloud computing services because cloud computing is a big shift from the traditional way businesses think about IT resources. Here are 7 reasons: 14 | 1. **Cost**: Cloud computing eliminates the capital expense of buying hardware and software and setting up and running on-site data centres 15 | 2. **Speed**: Most cloud computing services are provided as self service and on demand, so even vast amounts of computing resources can be provisioned in minutes, typically with just a few mouse clicks. 16 | 3. **Global Scale**: Cloud computing has the ability to scale elastically. In cloud speak, that means delivering the right amount of IT resources (e.g. more or less computing power, storage, bandwidth – right when they’re needed, and from the right geographic location). 17 | 4. **Productivity**: Cloud computing removes the need for “racking and stacking” (hardware setup, software patching and other time-consuming IT management chores), so IT teams can spend time on achieving more important business goals. 18 | 5. **Performance**: The biggest cloud computing services run on a worldwide network of secure data centres, which are regularly upgraded to the latest generation of fast and efficient computing hardware. This offers several benefits over a single corporate data centre, including reduced network latency for applications and greater economies of scale. 19 | 6. **Reliability**: Cloud computing makes data backup, disaster recovery and business continuity easier and less expensive because data can be mirrored at multiple redundant sites on the cloud provider’s network. 20 | 7. **Security**: Many cloud providers offer a broad set of policies, technologies and controls that strengthen your security posture overall, helping to protect your data, apps and infrastructure from potential. 21 | 22 | ## Types of cloud computing 23 | Not all clouds are the same and not one type of cloud computing is right for everyone. Several different models, types and services have evolved to help offer the right solution for your needs. 24 | 25 | First, you need to determine the type of cloud deployment, or cloud computing architecture, that your cloud services will be implemented on. There are three different ways to deploy cloud services: on a public cloud, private cloud or hybrid cloud. 26 | 27 | 1. **Public cloud** - Public clouds are owned and operated by third-party cloud service providers, who deliver their computing resources such as servers and storage over the Internet. Microsoft Azure is an example of a public cloud. With a public cloud, all hardware, software and other supporting infrastructure are owned and managed by the cloud provider. You access these services and manage your account using a web browser. 28 | 2. **Private cloud** - A private cloud refers to cloud computing resources used exclusively by a single business or organisation. A private cloud can be physically located on the company’s on-site data centre. Some companies also pay third-party service providers to host their private cloud. A private cloud is one in which the services and infrastructure are maintained on a private network. 29 | 3. **Hybrid cloud** - Hybrid clouds combine public and private clouds, bound together by technology that allows data and applications to be shared between them. By allowing data and applications to move between private and public clouds, a hybrid cloud gives your business greater flexibility, more deployment options and helps optimise your existing infrastructure, security and compliance. 30 | 31 | 32 | ## Types of cloud services 33 | Most cloud computing services fall into four broad categories: 34 | 1. **Infrastructure as a service (*IaaS*)** - The most basic category of cloud computing services. With IaaS, you rent IT infrastructure – servers and virtual machines (VMs), storage, networks, operating systems – from a cloud provider on a pay-as-you-go basis. 35 | 36 | 2. **Platform as a service (*PaaS*)** - Platform as a service refers to cloud computing services that supply an on-demand environment for developing, testing, delivering and managing software applications. PaaS is designed to make it easier for developers to quickly create web or mobile apps, without worrying about setting up or managing the underlying infrastructure of servers, storage, network and databases needed for development. 37 | 38 | 3. **Serverless computing** - Overlapping with PaaS, serverless computing focuses on building app functionality without spending time continually managing the servers and infrastructure required to do so. The cloud provider handles the setup, capacity planning, and server management for you. Serverless architectures are highly scalable and event-driven, only using resources when a specific function or trigger occurs. 39 | 40 | 4. **Software as a service (*SaaS*)** - Software as a service is a method for delivering software applications over the Internet, on demand and typically on a subscription basis. With SaaS, cloud providers host and manage the software application and underlying infrastructure, and handle any maintenance, such as software upgrades and security patching. Users connect to the application over the Internet, usually with a web browser on their phone, tablet or PC. 41 | 42 | 43 | ### Reference link: 44 | https://azure.microsoft.com/en-au/overview/what-is-cloud-computing/ -------------------------------------------------------------------------------- /Azure & Cloud Fundamentals/README.md: -------------------------------------------------------------------------------- 1 | # MSA 2020 - Cloud Computing with Azure 2 | ## Table of Contents 3 | 4 | 1. [Introduction](#1-Introduction) 5 | 2. [Resources](#2-Resources) 6 | 3. [Assessment](#3-Assessment) 7 | 4. [Submission](#4-Submission) 8 | 5. [Deadline](#5-Deadline) 9 | 10 | ## 1. Introduction 11 | 12 | - [Lecture Slides](https://stdntpartners-my.sharepoint.com/:p:/g/personal/kaif_ahsan_studentpartner_com/Ec67a5-kyd5AnUjKqHAYvYsBA-_7oSQP4WA6sVyz2SxSmA?e=JbmDFl) 13 | 14 | Welcome to the Microsoft Student Accelerator Australia 2020 bootcamp on Cloud Computing with Azure. Cloud computing is one of the most common buzzwords out there and as student we often don't get the chance harness the true potential of cloud. So, through this bootcamp we aim to give some hands-on experience with cloud comptuing using azure to not only understand what it is but also how you can push your career forward using it. If you never heard of Cloud Computing, click [here](https://docs.microsoft.com/en-us/learn/modules/principles-cloud-computing/) for a brief introduction to Cloud Computing. 15 | 16 | 17 | #### Low/No code Approach 18 | If you have always thought about having your resume or blog website, then we have some exciting news for you. In this bootcamp we will learn to create, configure and deploy your very own resume/blog website using Azure. We will also explore we can customize and optimise our website to stand out from the crowd. And, yes all this without having to write a single line of code. 19 | 20 | #### Coding Approach 21 | We have for the technical approach. We wouldn't just be exploring cloud computing, we would also going to learning about another amazing technology (and a buzzword) IoT. In this bootcamp by creating our IoT solution, we would be learning how cloud computing and IoT can be utilised together to create solutions to some of the most challenging problems of our current world. 22 | 23 | ## 2. Resources 24 | 25 | #### Low/No code Approach 26 | 27 | **Main resource** 28 | - [MS Learning Path: Azure Fundamentals](https://docs.microsoft.com/en-us/learn/paths/azure-fundamentals/) 29 | 30 | **Additional resources** 31 | - Microsoft Azure [YouTube channel](https://www.youtube.com/channel/UC0m-80FnNY2Qb7obvTL_2fA) has some great videos. 32 | - You can also learn how to add your own custom domain name (i.e.- www.youraddress.com) to your website in the [Host your domain on Azure DNS](https://docs.microsoft.com/en-us/learn/modules/host-domain-azure-dns/) module. However for the bootcamp we recommend using the default azure domain. 33 | 34 | You are welcome to the web and explore any other resources you find interesting. 35 | 36 | #### Coding Approach 37 | **Main resource** 38 | - [Azure IoT Learning Path](https://docs.microsoft.com/en-us/learn/paths/introduction-to-azure-iot/) 39 | - [Power BI learning Path](https://docs.microsoft.com/en-us/learn/paths/create-use-analytics-reports-power-bi/) 40 | 41 | **Additional resources** 42 | Microsoft Azure [YouTube channel](https://www.youtube.com/channel/UC0m-80FnNY2Qb7obvTL_2fA) has some great videos. Specially checkout the IoT and 'How To' playlist. 43 | You are welcome to the web and explore any other resources you find interesting. 44 | 45 | 46 | ## 3. Assessment 47 | To complete *Cloud Computing with Azure* bootcamp, you are required to compete these tasks. Please refer to stream specific guidelines below. 48 | 49 | #### Low/No code Approach 50 | **Microsoft Learn** 51 | - [MS Learning Path: Azure Fundamentals](https://docs.microsoft.com/en-us/learn/paths/azure-fundamentals/) - 10 Points 52 | 53 | **Project** 54 | - Build your own resume/blog website - 90 Points 55 | - [Project Specifications](https://1drv.ms/w/s!ArEj5-yGzsb8iqUAyZY8gS4ROr-uJw?e=PWqtcu) 56 | - [Marking Rubric](https://1drv.ms/w/s!ArEj5-yGzsb8iqRJ77I7nyXxn6a0EQ?e=XzHlsd) 57 | 58 | Check out this this [step-by-step guide](https://1drv.ms/w/s!ArEj5-yGzsb8iqUCi4eKI4MnIwLNfg?e=xA9VWz) to get started with with the project. This would guide you through setting up Azure and creating the web app. 59 | 60 | #### Coding Approach 61 | **Microsoft Learn** 62 | 63 | - [Azure IoT Learning Path](https://docs.microsoft.com/en-us/learn/paths/introduction-to-azure-iot/)** - 15 Points 64 | - [Power BI learning Path](https://docs.microsoft.com/en-us/learn/paths/create-use-analytics-reports-power-bi/) - 10 Points 65 | 66 | 67 | ** If you have already done [MS Learning Path: Azure Fundamentals](https://docs.microsoft.com/en-us/learn/paths/azure-fundamentals/) then you would still get 15 points as there was a mistake in the document. We wouldn't penalize you for not doing the Azure Iot Learning Path. However we recommend doing it. 68 | 69 | **Project** 70 | - Create your own solution using IoT hub and visualise data using Power BI - 75 Points 71 | - [Marking Rubric](https://1drv.ms/w/s!AvIx2ypSd5N7rg0Juxpnv7vCHvrC?e=qj08vh) 72 | 73 | Here are some useful documents that can help you get stared with your project: 74 | - [Sending Telemetry Data to Azure IoT using Python](https://docs.microsoft.com/en-us/azure/iot-hub/quickstart-send-telemetry-python) 75 | - [Visualizing sensor data using PowerBI](https://docs.microsoft.com/en-us/azure/iot-hub/iot-hub-live-data-visualization-in-power-bi) 76 | - [Raspberry Pi Azure IoT Simulator](https://azure-samples.github.io/raspberry-pi-web-simulator/) 77 | 78 | The left navigation bar of each of these links have a plethora of useful documents which you can use educate yourself. 79 | 80 | ## 4. Submission 81 | 82 | #### Low/No code Approach 83 | Review the submission guidelines again here: 84 | - [Submission Guidelines](https://1drv.ms/w/s!ArEj5-yGzsb8iqR-Kz5hEHfzXuTBbA?e=rvwXjJ) 85 | 86 | > **Project Submission Link: ** https://aka.ms/MSAAusProjectSubmission 87 | 88 | #### Coding Approach 89 | > [Project submission guidelines](https://stdntpartners-my.sharepoint.com/:w:/g/personal/kaif_ahsan_studentpartner_com/EWGncVP9q3BLsOfWjdRsKKgBfAWFU2fQaVHUEswPwfJDEA?e=Z5QcOM) 90 | 91 | To submit your work please fill in the submission form below. This will require you to submit GitHub links and screenshots of your completed tasks: 92 | 93 | > **Project Submission Link: ** https://aka.ms/MSAAusProjectSubmission 94 | 95 | 96 | Please read through the criteria on the respective GitHub documentation prior to submitting to ensure you have covered off everything. 97 | 98 | ## 5. Deadline 99 | The deadline for this bootcamp is on **26th July, 2020, 11:59pm AEDT** 100 | 101 | #### Late Submissions 102 | For this bootcamp late submissions upto **28th July 2020, 11:59pm AEDT** is allowed. However there will be a **20%** penalty on the total grade. -------------------------------------------------------------------------------- /AI & Advanced Analytics/Non-Tech Stream/MNIST demo using Machine Learning Studio designer tool/README.md: -------------------------------------------------------------------------------- 1 | # MNIST Demo with Machine Learning Studio Designer tool 2 | 3 | 4 | ## Create a new experiment 5 | 1. Login [Azure Machine Learning Studio (classic)](https://studio.azureml.net) 6 | 7 | 2. The List on the left side of the window can be used to navigate between experiments, projects and other features in ML Studio. Click on **Experiment** tab and choose **+NEW** on the bottom left corner of the window. A pop-up window appears with various options to choose from. Please select **Blank Experiment** from the available options. 8 | ![img01](img/img01.png) 9 | 10 | 3. The left most panel contains various functions and models to choose from. The centre panel is to build the model and the right most panel shows the description of model or selected function. The name of the experiment can be changed by clicking on default name on the top “Experiment created on 7/4/2020” and type the required name in place of it. 11 | ![img02](img/img02.png) 12 | 13 | ## Demo Experiment 14 | 1. In this tutorial we will be running a demo experiment of predicting the handwritten numbers using Machine Learning Model. In this experiment we will use the pre-defined data set available under sample datasets. 15 | ![img03](img/img03.png) 16 | 17 | 2. From the drop-down list of **Samples** choose **MNIST Train 60K 28x28 dense**, click on the dataset and drag it on to the workspace in the centre, similarly choose **MNIST Test 10K 28x28 dense** and drag it on to the workspace. 18 | ![img04](img/img04.png) 19 | 20 | 3. Azure Machine Learning studio has several in-built functions that are used to perform pre-processing actions on the dataset itself which is discussed in the later section of the document. Now from left panel Choose from the in-built Machine Learning algorithms available under **Machine Learning** tab select Multiclass Neural Network and drag it on to workspace. In the same left panel search for **Train model** and drag into on to workspace. Similarly drag in **Score Model** and **Evaluate Model**. 21 | ![img05](img/img05.png) 22 | ![img06](img/img06.png) 23 | ![img07](img/img07.png) 24 | ![img08](img/img08.png) 25 | 26 | 4. Once the required functions are dragged and dropped on workspace, the tree diagram is connected as shown in the figure below. 27 | ![img09](img/img09.png) 28 | 29 | 5. Once the model is connected as above run click on the **Train module** function and from the right panel **Launch the column selector**. This step is to specify the response class for the Machine Learning algorithm to be applied on. 30 | ![img10](img/img10.png) 31 | 32 | 6. After the column selector window is open choose column **Label** and move it to adjacent list using the arrow keys as shown below. 33 | ![img11](img/img11.png) 34 | 35 | 7. Once the column is moved to Selected columns list click on the **Tick** mark on bottom right corner of the window to exit column selector. Now hit the **RUN** command on bottom centre of the page to execute the Machine Learning Model. Once the model is successfully executed a green tick marks appears in each of the function blocks showing the successful execution of each function. 36 | ![img12](img/img12.png) 37 | 38 | 8. The results of this experiment can be visualised by right clicking on the bottom white dot of **Evaluate model** tab. 39 | ![img13](img/img13.png) 40 | 41 | 9. Upon clicking Visualize the results of the model are displayed below: 42 | ![img14](img/img14.png) 43 | 44 | ### Pre-processing Functions 45 | Azure Machine learning studio also supports user to perform several of pre-processing on the raw data before applying Machine learning algorithm. These pre-processing is done to improve the accuracy of the results and to make the model more compact and robust. Here in this tutorial we will be looking at splitting the data, cleaning the data and summarizing the data. 46 | 47 | #### Importing data 48 | 1. Import data function is used to import data into ML studio. This function can be found in the left panel under Data input and output list, you can also navigate to it from search bar. 49 | ![img15](img/img15.png) 50 | 51 | 2. This function is dragged and dropped into workspace and Import wizard is opened from right panel. 52 | ![img16](img/img16.png) 53 | 54 | 3. This action will pop up a window on the screen to perform import action as shown below: 55 | ![img17](img/img17.png) 56 | 57 | 4. The source of the dataset can be selected from available options and the application will prompt the user proceeding steps to import the data. In this case we will be importing data from a .csv file in the local drive as shown in below (**+NEW > Dataset > Local drive**): 58 | ![img18](img/img18.png) 59 | 60 | #### Splitting the data 61 | 1. Most of the times in production, user is not supplied with separate sets of data to train and test the model. Hence a split function is used to split the raw data into two parts one of which is used to train the model while the other is used to score the model while testing. Here to facilitate the split operation, default MNIST data has been downloaded to local drive and altered to add some irregularities in the data. Using the above described procedure, the altered dataset has been imported into ML Studio to perform splitting action. 62 | ![img19](img/img19.png) 63 | 64 | 2. Click on the Split Data function and navigate to the right panel to perform splitting action. The splitting mode, Fraction of splitting are specified as shown below. 65 | ![img20](img/img20.png) 66 | > [**NOTE**: Here the splitting mode is based on rows due to the nature of dataset. The fraction of split is 0.7 which means 70% of data is split into first node (first white dot from left at bottom of split function) and rest of it is split into second node. It is an ideal practice to split data into 70% for train set and 30% for test set in general. More information about split function can be found in Microsoft help documentation] 67 | 68 | 3. As mentioned above the split data is now 70% into first node which will be used to train the model and 30% into second node which is used for testing. As a rule of thumb nodes in ML studio are always numbered from left. 69 | ![img21](img/img21.png) 70 | 71 | #### Cleaning the missing data 72 | 1. In real time the data we deal with Machine learning always comes with blank or missing data points which if supplied as it is to ML algorithm can result in errors. Hence it is important to clean the missing data before processing it into ML algorithm. This action can be performed using in-built Clean missing data function in ML studio. 73 | ![img22](img/img22.png) 74 | 75 | 2. Once this function is dragged and dropped in the workspace the input node is connected to raw data that has missing values in it. Now the cleaning action can be performed from right panel as shown: 76 | ![img23](img/img23.png) 77 | > [**Note**: In this case cleaning mode is chosen to be Remove entire row due to nature of data, but there are various other options available for cleaning modes which has their own performance benefits for different datasets. These can be referred in Microsoft documentation for cleaning data function] 78 | 79 | #### Publishing the experiment 80 | 1. Once the ML model is executed successfully, the model can be published to Microsoft Machine Learning Gallery to share with public users. The project can be published by clicking the **publish icon** at the bottom of the screen. 81 | ![img24](img/img24.png) 82 | 83 | 2. This pops up a window as shown below where user can fill in the details and description of the experiment. 84 | ![img25](img/img25.png) 85 | > [**NOTE**: In practice it is ideal to fill in detailed description of the experiment for other users and public to understand the experiment and its usage] -------------------------------------------------------------------------------- /Workshops/Git & GitHub/Git-handbook.md: -------------------------------------------------------------------------------- 1 | # Git Handbook 2 | 3 | ## Table of contents 4 | 5 | 6 | ## Downloading and setting up 7 | Git is a free software which you can download to almost any platform. Git is primarily used via the command-line interface, which we can access with our system terminals. 8 | However, we first need to make sure that we have Git installed on our computers. 9 | 10 | > You can download Git from here: https://git-scm.com/downloads 11 | 12 | After installing it, start your terminal/command prompt and type the following command to verify that Git is ready to be used on your computer. 13 | 14 | ```bash 15 | git --version 16 | ``` 17 | 18 | If you are using a Mac or Linux machine, then you can utilize the default Bash terminal that comes pre-installed on your machine. 19 | 20 | If you are using Windows, you can use its built-in Powershell terminal, or the Git Bash terminal which is bundled with the Git installation. For detailed windows Git and Git Bash install instructions, check out this [blog post](https://zarkom.net/blogs/how-to-install-git-and-git-bash-on-windows-9140) 21 | 22 | #### Configuring you name & email 23 | In your terminal, run the following commands to identify yourself with Git: 24 | 25 | ```bash 26 | git config --global user.name "Your Name" 27 | git config --global user.email "your@email.com" 28 | ``` 29 | 30 | Replace the values inside the quotes with your name and email address. 31 | 32 | ## Repositories 33 | 34 | When working with Git, it's important to be familiar with the term **repository**. A Git repository is a container for a project that is tracked by Git. 35 | 36 | We can single out two major types of Git repositories: 37 | 38 | - **Local repository** - an isolated repository stored on your own computer, where you can work on the local version of your project. 39 | - **Remote repository** - generally stored outside of your isolated local system, usually on a remote server. It's especially useful when working in teams - this is the place where you can share your project code, see other people's code and integrate it into your local version of the project, and also push your changes to the remote repository. 40 | 41 | In this video, we'll only work with local repositories. 42 | 43 | ## Initializing a repository 44 | 45 | To create a new repository and start tracking your project with Git, use your terminal software and navigate to the main folder of your project, then type the following command: 46 | 47 | ```bash 48 | git init 49 | ``` 50 | 51 | This command will generate a hidden **.git** directory for your project, where Git stores all internal tracking data for the current repository. 52 | 53 | ## Staging & Commiting 54 | 55 | Committing is the process in which the changes are *'officially'* added to the Git repository. 56 | 57 | In Git, we can consider **commits** to be checkpoints, or snapshots of your project at its current state. In other words, we basically save the current version of our code in a commit. We can create as many commits as we need in the commit history, and we can go back and forth between commits to see the different revisions of our project code. That allows us to efficiently manage our progress and track the project as it gets developed. 58 | 59 | Commits are usually created at logical points as we develop our project, usually after adding in specific contents, features or modifications (like new functionalities or bug fixes, for example). 60 | 61 | > Before we can commit our code, we need to place it inside the **staging area**. 62 | 63 | #### Checking Git Status 64 | 65 | While located inside the project folder in our terminal, we can type the following command to check the status of our repository: 66 | 67 | ```bash 68 | git status 69 | ``` 70 | 71 | This is a command that is very often used when working with Git. It shows us which files have been changed, which files are tracked, etc. 72 | 73 | We can add the untracked project files to the **staging area** based on the information from the `git status` command. 74 | 75 | At a later point, `git status` will report any modifications that we made to our tracked files before we decide to add them to the staging area again. 76 | 77 | #### Staging Files 78 | 79 | From the project folder, we can use the **git add** command to add our files to the staging area, which allows them to be tracked. 80 | 81 | We can add a specific file to the staging area with the following command: 82 | 83 | ```bash 84 | git add file.js 85 | ``` 86 | 87 | To add multiple files, we can do this: 88 | 89 | ```bash 90 | git add file.js file2.js file3.js 91 | ``` 92 | 93 | Instead of having to add the files individually, we can also add all the files inside the project folder to the staging area: 94 | 95 | ```bash 96 | git add . 97 | ``` 98 | 99 | By default, this adds **all the files and folders** inside the project folder to the staging area, from where they are ready to be committed and tracked. 100 | 101 | #### Making Commits 102 | A **commit** is a snapshot of our code at a particular time, which we are saving to the commit history of our repository. After adding all the files that we want to track to the staging area with the `**git add`** command, we are ready to make a commit. 103 | 104 | To commit the files from the staging area, we use the following command: 105 | 106 | ```bash 107 | git commit -m "Commit message" 108 | ``` 109 | 110 | Inside the quotes, we should write a **commit message** which is used to identify it in the commit history. 111 | 112 | The commit message should be a descriptive summary of the changes that you are committing to the repository. 113 | 114 | After executing that command, you will get the technical details about the commit printed in the terminal. And that's basically it, you have successfully made a commit in your project! 115 | 116 | > To create a new commit, you will need to repeat the process of adding files to the staging area and then committing them after. Again, it's very useful to use the **git status** command to see which files were modified, staged, or untracked. 117 | 118 | #### Commit History 119 | To see all the commits that were made for our project, you can use the following command: 120 | 121 | ```bash 122 | git log 123 | ``` 124 | 125 | The logs will show details for each commit, like the author name, the generated hash for the commit, date and time of the commit, and the commit message that we provided. 126 | 127 | #### Reverting Back to a Previous Version 128 | To go back to a previous state of your project code that you committed, you can use the following command: 129 | 130 | ```bash 131 | git checkout 132 | ``` 133 | 134 | Replace `` with the actual hash for the specific commit that you want to visit, which is listed with the `git log` command. 135 | 136 | To go back to the latest commit (the newest version of our project code), you can type this command: 137 | 138 | ```bash 139 | git checkout master 140 | ``` 141 | ## Branches 142 | 143 | A **branch** could be interpreted as an individual timeline of our project commits. 144 | 145 | With Git, we can create many of these alternative environments (i.e. we can create different **branches**) so other versions of our project code can exist and be tracked in parallel. 146 | 147 | That allows us to add new (experimental, unfinished, and potentially buggy) features in separate branches, without touching the '*official'* stable version of our project code (which is usually kept on the **master** branch). 148 | 149 | When we initialize a repository and start making commits, they are saved to the **master** branch by default. 150 | 151 | #### Creating a new branch 152 | You can create a new branch using the following command: 153 | 154 | ```bash 155 | git branch 156 | ``` 157 | The new branch that gets created will be the reference to the current state of your repository. 158 | 159 | > It's a good idea to create a **development** branch where you can work on improving your code, adding new experimental features, and similar. After development and testing these new features to make sure they don't have any bugs and that they can be used, you can merge them to the master branch. 160 | 161 | #### Changing branches 162 | 163 | To switch to a different branch, you use the **git checkout** command: 164 | 165 | ```bash 166 | git checkout 167 | ``` 168 | 169 | With that, you switch to a different isolated timeline of your project by changing branches. 170 | 171 | > For example, you could be working on different features in your code and have a separate branch for each feature. When you switch to a branch, you can commit code changes which only affect that particular branch. Then, you can switch to another branch to work on a different feature, which won't be affected by the changes and commits made from the previous branch. 172 | 173 | To create a new branch and change to it at the same time, you can use the **-b** flag: 174 | 175 | ```bash 176 | git checkout -b 177 | ``` 178 | 179 | To list the branches for your project, use this command: `git branch` 180 | 181 | To go back to the **master** branch, use this command: 182 | 183 | ```bash 184 | git checkout master 185 | ``` 186 | 187 | #### Merging branches 188 | You can merge branches in situations where you want to implement the code changes that you made in an individual branch to a different branch. 189 | 190 | For example, after you fully implemented and tested a new feature in your code, you would want to merge those changes to the stable branch of your project (which is usually the default **master** branch). 191 | 192 | To merge the changes from a different branch into your current branch, you can use this command: 193 | 194 | ```bash 195 | git merge 196 | ``` 197 | 198 | You would replace `` with the branch that you want to integrate into your current branch. 199 | 200 | #### Deleting Branches 201 | To delete a branch, you can run the **git branch** command with the **-d** flag: 202 | 203 | ```bash 204 | git branch -d 205 | ``` 206 | Read more about branching and merging [on this link](https://git-scm.com/book/en/v2/Git-Branching-Basic-Branching-and-Merging). 207 | 208 | ## Further Reading 209 | To learn more about Git, make sure to check the following resources: 210 | 211 | - Git official documentation: [https://git-scm.com/doc](https://git-scm.com/doc) -------------------------------------------------------------------------------- /AI & Advanced Analytics/README.md: -------------------------------------------------------------------------------- 1 | # MSA 2020 - AI & Advanced Analytics 2 | 3 | ## Table of Contents 4 | 1. [Introduction](https://github.com/AUMSA/2020-MSA-content/tree/master/AI%20%26%20Advanced%20Analytics#1-introduction) 5 | 2. [Resources](https://github.com/AUMSA/2020-MSA-content/tree/master/AI%20%26%20Advanced%20Analytics#2-resources) 6 | 3. [Assessment](https://github.com/AUMSA/2020-MSA-content/tree/master/AI%20%26%20Advanced%20Analytics#3-assessment) 7 | 5. [Submission](https://github.com/AUMSA/2020-MSA-content/tree/master/AI%20%26%20Advanced%20Analytics#4-submission) 8 | 6. [Deadline](https://github.com/AUMSA/2020-MSA-content/tree/master/AI%20%26%20Advanced%20Analytics#5-deadline) 9 | 10 | ## 1. Introduction 11 | Welcome to the Microsoft Student Accelerator Australia 2020 bootcamp on AI and Analytics. This module hopes 12 | to teach you the fundamental ideas behind Machine Learning and give you a picture of what it looks like to use Machine Learning and why it's useful. Machine learning is one of the emerging technologies which has the power to change the world and we would like to enable everyone to harness it power. Hence, in this bootcamp, students from all background will be taught on how to get started with Machine Learning. 13 | 14 | ### Low/No code Approach 15 | For those who don't have any prior coding experience, we will be leveraging Azure Machine Learning Studio to 16 | create a Machine Learning model without writing any code. The Designer tool in ML Studio enables us to 17 | develop our project by dragging and dropping appropriate layers. Click [here](https://github.com/AUMSA/2020-MSA-content/tree/master/AI%20%26%20Advanced%20Analytics/Non-Tech%20Stream/Setting%20up%20Azure%20Machine%20Learning%20Studio) for tutorial on setting up Machine Learning Studio. (Please note you need to have an [Azure Student Subscription](https://github.com/AUMSA/2020-MSA-content/tree/master/Azure%20For%20Students) to access this.) 18 | 19 | ### Coding Approach 20 | We have catered our program to code wizards to who want to get their hands dirty. In this bootcamp we will be 21 | exploring many core concepts of Machine Learning through creating the program from scratch using Python and 22 | Azure Notebooks. Click [here](https://github.com/AUMSA/2020-MSA-content/tree/master/AI%20%26%20Advanced%20Analytics/Tech%20Stream/Setting%20up%20Azure%20Notebook) for tutorial on setting up Azure Notebook. (Please note you need to have an [Azure Student Subscription](https://github.com/AUMSA/2020-MSA-content/tree/master/Azure%20For%20Students) to access this.) 23 | 24 | > **NOTE:** Due to COVID-19 related resource constraints many students are having issues with creating compute in Azure Machine Learning Studio. Students who are affected by this can do the coding portion/project in their local environment. Please read [local environment set-up guide](https://github.com/AUMSA/2020-MSA-content/blob/master/AI%20%26%20Advanced%20Analytics/Tech%20Stream/setting-up-local-environment.md) if you're unfamiliar. 25 | 26 | ## Bootcamp Slides 27 | 1. [Slides for 13th April](https://github.com/AUMSA/2020-MSA-content/blob/master/AI%20%26%20Advanced%20Analytics/Non-Tech%20Stream/MSA-Bootcamp-13-April-Slides.pdf) - Low/No Code 28 | 2. [Slides for 14th April](https://github.com/AUMSA/2020-MSA-content/blob/master/AI%20%26%20Advanced%20Analytics/Tech%20Stream/MSA-Bootcamp-14-April-Slides.pdf) - Code 29 | 30 | ## Technical Bootcamp Demo 31 | 1. [Project Walkthrough for Technical Bootcamp for 14th April](https://1drv.ms/v/s!ArEj5-yGzsb8ipssYmVC2liaIXd3HQ?e=Z9FuxC) - Good video & audio quality 32 | 33 | ## Bootcamp Recordings 34 | The recordings can be accessed using the same Bootcamp url that we sent to you via email. 35 | 36 | ## 2. Resources 37 | 38 | ### Low/No code Approach: 39 | - Although Microsoft AI Business School is a fantastic place for starting your Machine Learning journey: https://www.microsoft.com/en-us/ai/ai-business-school 40 | - Learn out what Azure Machine Learning Desinger is and how to utilise is through this guide 41 | https://docs.microsoft.com/en-us/azure/machine-learning/concept-designer 42 | - Get hands on with the Azure Machine Learning Studio by finishising your experiment: 43 | https://docs.microsoft.com/en-us/azure/machine-learning/studio/create-experiment 44 | 45 | #### Extra Resources: 46 | This YouTube playlist gives a very comprehensive walkthrough of the Azure Machine Learning Designer and we recommend checking it out: 47 | https://www.youtube.com/watch?v=uBYu_yrz_ZQ&list=PL8eNk_zTBST_WSR_KUBex8TDnQ21GetSG 48 | 49 | 50 | ### Coding Approach: 51 | - You can have a look at this MS learn 6 hours course which would take your skill from beginner to intermediate (yes you read it right 6 hours!!)- 52 | https://aischool.microsoft.com/en-us/machine-learning/learning-paths/ml-crash-course 53 | 54 | - Visit this cool MS learn link to know about many more conventional AI projects. Happy learning- 55 | https://aischool.microsoft.com/en-us/conversational/learning-paths 56 | 57 | - The MS learn video on Machine Learning is a good place to start. It'll give you a basic understanding of what Machine Learning is so you can understand the concepts discussed in this video a little better. We recommend reading through it beforehand. https://docs.microsoft.com/en-gb/learn/paths/intro-to-ml-with-python/ 58 | 59 | > **NOTE:** Due to COVID-19 related resource constraints many students are having issues with creating compute in Azure Machine Learning Studio. Students who are affected by this can do the coding portion/project in their local environment. Please read [local environment set-up guide](https://github.com/AUMSA/2020-MSA-content/blob/master/AI%20%26%20Advanced%20Analytics/Tech%20Stream/setting-up-local-environment.md) if you're unfamiliar. 60 | #### Extra Resources 61 | - General Data Analysis information: https://github.com/wesm/pydata-book 62 | - This Pandas cheat sheet is good to have by: https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf 63 | 64 | - If you want to go deeper and then this Full course on Machine Learning by Stanford university might come handy. You could find it here- 65 | https://www.youtube.com/watch?v=PPLop4L2eGk&list=PLLssT5z_DsK-h9vYZkQkYNWcItqhlRJLN 66 | 67 | ## 3. Assessment: 68 | To complete AI & Advanced Analytics bootcamp, you are required to compete this assessment. You can complete this assignment using either using **Low/No code Approach** or **Coding Approach**. 69 | 70 | - [Project Submission Guidelines](https://stdntpartners-my.sharepoint.com/:w:/g/personal/kaif_ahsan_studentpartner_com/EaMdIgV5WvhIlX1zWslTnesBhuRgZ9eAT39ISCr8GRePyg?e=v8uteh) 71 | - [Marking Rubric](https://stdntpartners-my.sharepoint.com/:w:/g/personal/kaif_ahsan_studentpartner_com/EXyDSEz4XyxHrayBgvFt08gBxykSHItKfz27TOaNO6EGOA?e=YwYXpa) 72 | 73 | ### Low/No code Approach: 74 | #### Part-1 75 | If you're using Azure Machine Learning Designer then choose one of the following Learning Paths on Microsoft Learn and complete it. We recommend doing multiple if possible and would give you extra points. 76 | 77 | 1. [AI for Manufacturing](https://docs.microsoft.com/en-us/learn/paths/ai-business-school-manufacturing/) 78 | 2. [AI for Retail](https://docs.microsoft.com/en-us/learn/paths/ai-business-school-retail/) 79 | 3. [AI for Healthcare](https://docs.microsoft.com/en-us/learn/paths/ai-business-school-healthcare/) 80 | 4. [AI for Finacial Servises](https://docs.microsoft.com/en-us/learn/paths/ai-business-school-financial-services/) 81 | 5. [AI for Government](https://docs.microsoft.com/en-us/learn/paths/ai-business-school-government/) 82 | 6. [AI for Education](https://docs.microsoft.com/en-us/learn/paths/ai-business-school-education/) 83 | 84 | 85 | #### Part-2 86 | Complete one project from the ideas mentioned in [Project section](https://github.com/AUMSA/2020-MSA-content/tree/master/AI%20%26%20Advanced%20Analytics#project) or of your choice using Azure Machine Learning Studio. 87 | 88 | > Please follow the project completion guidelines in [Project section](https://github.com/AUMSA/2020-MSA-content/tree/master/AI%20%26%20Advanced%20Analytics#project) and the submission guidelines in Submission section. 89 | 90 | ### Coding Approach: 91 | #### Part-1 92 | If you want to code your own project then complete this [Microsoft Learn Learning Path](https://docs.microsoft.com/en-gb/learn/paths/intro-to-ml-with-python/). 93 | 94 | #### Part-2 95 | Complete one project from the ideas mentioned in [Project section](https://github.com/AUMSA/2020-MSA-content/tree/master/AI%20%26%20Advanced%20Analytics#project) or of your choice using Azure Notebooks or similar tools. 96 | 97 | > Please follow the project completion guidelines in [Project section](https://github.com/AUMSA/2020-MSA-content/tree/master/AI%20%26%20Advanced%20Analytics#project) and the submission guidelines in Submission section. 98 | 99 | ## Project 100 | To consolidate your learning from this bootcamp, you are required to complete a project. Apart from learning purposes, 101 | you can also share this project in your CV/resume and it might be useful in your future job search. 102 | The projects are mandatory and part of this bootcamp's assessment. You **must** complete the project with the following guidelines: 103 | 104 | #### Low/No Coding Approach: 105 | - This guidelines are valid if you're using Azure Machine Learning Designer. 106 | - You have to add a proper description and summary of the project. 107 | - In the description section explain the source of the dataset 108 | 109 | #### Coding Approach: 110 | - You have to upload and maintain a GitHub repository for your project 111 | - Your project **must not** have only one commit. We need to check commit history to ensure the validity of the project 112 | - If it's a code file, it **must** have comments to explain the major steps in your code 113 | - Add a README.md file explaining your project idea. 114 | 115 | #### Sample projects: 116 | Here's a list of cool projects ideas to inspire you: 117 | 118 | 1. A ML model to classify flowers based on their species - [Dataset](http://archive.ics.uci.edu/ml/datasets/Iris) 119 | 2. A ML Model to detect if a person has Parkinson's disease - [Dataset](https://www.kdnuggets.com/2020/03/20-machine-learning-datasets-project-ideas.html) 120 | 3. A ML model to identify emails are spam or not - [Dataset](https://archive.ics.uci.edu/ml/datasets/Spambase) 121 | 122 | If you have our own project idea then feel free to implement that. However, please make sure you have a README file that contains enough information about what your project is about. 123 | 124 | Here are some open datasets to help with your projects: 125 | - [Microsoft Open Datasets](https://azure.microsoft.com/en-au/services/open-datasets/) - Curated open data made easily accessible on Azure 126 | - [Kaggle](https://www.kaggle.com/datasets) - One of the largest datasets in the world. From the latest COVID-19 data to Formula 1 races, Kaggle has it all. 127 | - [UCI Machine Learning Dataset](http://archive.ics.uci.edu/ml/datasets.php) - Oldest machine learning dataset available in the internet. 128 | 129 | ## 4. Submission 130 | Review the submission guidelines again here: 131 | - [Project Submission Guidelines](https://stdntpartners-my.sharepoint.com/:w:/g/personal/kaif_ahsan_studentpartner_com/EaMdIgV5WvhIlX1zWslTnesBhuRgZ9eAT39ISCr8GRePyg?e=v8uteh) 132 | 133 | To submit your work please fill in the submission form below. This will require you to submit GitHub links and screenshots of your completed tasks: 134 | **Project Submission Link:** https://aka.ms/MSAAusProjectSubmission 135 | 136 | Please read through the criteria on the respective GitHub documentation prior to submitting to ensure you have covered off everything. 137 | > For *tech stream*, if your repository is private please add the username: **msa-australia** as a collaborator. 138 | 139 | > For *non-tech stream*, you would need to add user to your workspace. Click [here](https://github.com/AUMSA/2020-MSA-content/blob/master/AI%20%26%20Advanced%20Analytics/Non-Tech%20Stream/Adding%20User%20to%20Workspace.md) for the tutorial. 140 | 141 | ## 5. Deadline 142 | The assessment of this bootcamp is due by **28th June 2020**. Any submission after the deadline **will not** be accepted. 143 | 144 | ## Points 145 | Your progress will be measured based on a point system. A maximum of 100 points will be awarded for a project and a maximum of 3 points will be awarded for the completion of a Microsoft Learn Learning Path. 146 | 147 | - [Marking Rubric](https://stdntpartners-my.sharepoint.com/:w:/g/personal/kaif_ahsan_studentpartner_com/EXyDSEz4XyxHrayBgvFt08gBxykSHItKfz27TOaNO6EGOA?e=YwYXpa) 148 | -------------------------------------------------------------------------------- /Workshops/Git & GitHub/GitHub-Handbook.md: -------------------------------------------------------------------------------- 1 | # GitHub Handbook 2 | Git is used to store projects inside *repositories* and track the complete history of all changes to the project code. Using GitHub, we can upload a local project repository to a remote cloud-based GitHub repository. We can also interact with public repositories published by other developers. 3 | 4 | > GitHub could even be looked at as a social networking website for developers. Users can follow each other, give ratings, collaborate and communicate. 5 | 6 | GitHub allows developers to utilize, change or improve software from its repositories. Each repository contains all project files and the code history. Repositories can have multiple collaborators and can be either public or private. 7 | 8 | GitHub is also a popular way developers to publish their project portfolio online. It's an easy way to showcase skills and experience to potential employers or clients. It's an important technology to be familiar with, especially for a new developer who is just starting out. 9 | 10 | > GitHub homepage: [github.com](http://github.com) 11 | 12 | 13 | ## Getting started with GitHub 14 | 15 | GitHub allows developers to access a **remote** central repository hosted on the internet. A developer can clone(basically download) the hosted remote repository to their computer and work on a local version of the project. They can work on the code or develop new features on their local computer and whenever they're ready, those changes can be pushed to the remote repository hosted on GitHub, where other developers or team members can download it to their computer and stay synchronized with the project development. 16 | 17 | Before we can start using GitHub, we need to register our own GitHub account. 18 | 19 | To register a new account, visit [GitHub.com](http://github.com) and find the 'Sign up' option on their website, or visit this page directly: [**https://github.com/join**](https://github.com/join) 20 | 21 | - **Step 1: Set up your account** 22 | 23 | Choose your new GitHub **username**, specify your existing **email** address (it's important to use your real email address because we will need to verify our account when we finalize the registration process) and the **password** of your choosing. 24 | 25 | After that, verify your account and you should be able to click the **'Create an account'** button at the bottom. 26 | 27 | - **Step 2: Choose your subscription** 28 | 29 | In the second step, you can choose the **Free** subscription plan to use GitHub free of charge. 30 | 31 | After choosing the **Free** plan, click the **'Continue'** button to go to the next step. 32 | 33 | - **Step 3: Tailor your experience** 34 | 35 | This is an optional step where you can share some information about yourself if you want to. Otherwise, you can scroll down the page and skip that step to continue the registration process. 36 | 37 | > Finally, you need to check the inbox of the email that you provided to **verify your email address** with GitHub. 38 | 39 | ## Using GitHub 40 | 41 | **Common Workflow: Push an Existing Repo to Github** 42 | 43 | 1. Add/commit your code locally 44 | 2. Go to Github and make a new repository 45 | 3. Connect your local repo to the github repo (add a remote) 46 | 4. Push your code up to github using the new remote 47 | 48 | The first thing we will do is create our local repository which we want to push to GitHub. In these notes, we'll create a very simple project repository to demonstrate how it can be uploaded to GitHub. 49 | 50 | - **Step 1: Create a new local Git repository** 51 | 52 | Based on what we learned in Git Handbook, open up your terminal and navigate to your projects folder, then run the following command to create a new project folder and navigate into it: 53 | 54 | ```bash 55 | mkdir hello-world 56 | cd hello-world 57 | ``` 58 | 59 | Then, to initialize a new local Git repository we need to run the `git init` command: 60 | 61 | ```bash 62 | git init 63 | ``` 64 | 65 | After you run that command, you should get feedback that an empty Git repository was initialized for your project. 66 | 67 | - **Step 2: Adding a new file to our Git repository** 68 | 69 | Create a new file in your project folder, we will call our sample file `README.md` 70 | 71 | You can use the graphical interface of your operating system to create the file, or use the following terminal commands: 72 | 73 | > Windows Powershell: `ni README.md` 74 | >Bash (Mac/Linux) terminal: `touch README.md` 75 | 76 | Save the file changes and then switch back to your terminal window. 77 | 78 | - **Step 3: Making our initial commit to the local repository** 79 | 80 | As learned in Git Handbook, run the following commands to track your files and make the initial commit in the local repository: 81 | 82 | ```bash 83 | git add . 84 | git commit -m "Initial commit" 85 | ``` 86 | 87 | When that's done, it means that we successfully prepared our new local repository to be pushed to GitHub! 88 | 89 | Make sure to use the `git status` command frequently when working with Git. It's a great way to check the status of your project files and the whole repository. 90 | 91 | #### Creating a new GitHub Repository 92 | To create a new GitHub repository, navigate to [github.com](http://github.com) and press the plus symbol in the top-right corner, then select the '**New repository**' option, as shown in the screenshot here: 93 | 94 | 95 | ![Clicking new repo button](img/creating-a-repo.png) 96 | 97 | 98 | You can also navigate to the GitHub page for creating new repositories by visiting this link: https://github.com/new 99 | 100 | 101 | ![Creating a new github repo](img/creating-new-repo.png) 102 | 103 | 104 | On that page, we first need to specify a **Repository name** and an optional **Description.** 105 | For the **Repository name**, we can specify the same project name (**hello-world**) as the local repository that we are using in our example. If you want, you can also write a **Description** of your repository, but you can also skip that field as we did in the screenshot above. 106 | 107 | You can set your repository to be **Public** or **Private**. 108 | 109 | If you choose **Public**, it means anyone can see this new repository. When uploading your code to a public directory, always make sure that it does not contain any sensitive data that you don't wish to share with others. 110 | 111 | On the other hand, if you choose **Private** then you can manually choose who can access the new repository. 112 | 113 | If you wanted, you could initialize the repository with a **README** file, which usually contains information or documentation about the project. We don't need one for this simple project, so we can skip those options and click the green **'Create repository'** button to finalize the creation procedure. 114 | 115 | #### Pushing code to the GitHub repo 116 | After the last step, you will be forwarded to the starting page of your new GitHub repository that looks like this: 117 | 118 | ![Quick setup screen](img/quick-setup-screen.png) 119 | 120 | 121 | Since we've already created our Git repo locally, we can focus on the **`…or push an existing repository from the command line`** section of the page. 122 | 123 | If we didn't already have a local repository created, then we would follow the first set of commands to create a local repository from the remote GitHub one that was just created. 124 | 125 | The **git remote add origin** command will associate our local repository with the remote GitHub repository that we just created. We're essentially telling your Git repo that we have a URL we want it to know about, and we give it the name "origin". You do not have to name the remote "origin" but it is standard if you only have a single remote. 126 | 127 | The **git push** command will then push our local Git repository code to the remote GitHub repository (if you chose a public repository, this will publish your code on the internet - via GitHub). 128 | 129 | Therefore, switch back to your local terminal and run the specified commands from your project folder: 130 | 131 | ```bash 132 | git remote add origin https://github.com//.git 133 | git push -u origin master 134 | ``` 135 | 136 | When you run the **git push** command you will be prompted to enter your GitHub username and password, to log in to your GitHub account from the terminal. 137 | 138 | After the repository was pushed, you can navigate back to your GitHub account page or the repository link and refresh it: `https://github.com//` 139 | 140 | Now, you can use that link to share your project repository with other people. 141 | 142 | 143 | ![Commit screen](img/commit-screen.png) 144 | 145 | For example, anyone can click on the **README.md** repository to their local computer (or **download** it), by clicking on the green button highlighted in the screenshot. 146 | 147 | You can also see many other data from the repository, including past **commits**, existing **branches**, etc. 148 | 149 | #### Making changes to the GitHub repository 150 | 151 | Now, any changes that we make to our local project files won't automatically affect the remote GitHub repository, until we **push** those changes again, to update it. 152 | 153 | For example, open the **README.md** file with your favorite code editor and change the code to this: 154 | 155 | ```md 156 | Hello world! Welcome to my awesome project! 157 | ``` 158 | 159 | Save the file changes, and commit those changes to your local repository using the following commands: 160 | 161 | ```bash 162 | git add . 163 | git commit -m "Change greeting" 164 | ``` 165 | 166 | Then, push your updated local repository to the remote GitHub repository with this command: 167 | 168 | ```bash 169 | git push origin master 170 | ``` 171 | 172 | After that, when you navigate back to your remote repository page on [github.com](http://github.com), you should see the updated code, and one more **commit** in the list. 173 | 174 | #### Cloning an existing GitHub repository 175 | 176 | Another approach would be to first create a GitHub repository online, and then download it to our computer and initiate the project that way. 177 | 178 | From [github.com](http://github.com), go to the **New repository** page: [https://github.com/new](https://github.com/new) 179 | 180 | Go through the same steps but specify a new repository name: 181 | 182 | 183 | ![Cloning a repo](img/creating-new-repo.png) 184 | 185 | 186 | To clone the repository, visit its page and select the green 'Clone or download' menu button, then click on the icon shown in the screenshot to copy the repository URL that we will need to use: 187 | 188 | 189 | ![Cloning an existing repo](img/cloning-existing-repo.png) 190 | 191 | 192 | Then, to clone the remote repository to your computer, execute the **git clone** command with the link that you just copied: 193 | 194 | ```bash 195 | git clone 196 | ``` 197 | 198 | That will create a new folder with the remote GitHub repository name and download all the project files and repository data into it. You can then change directories (**cd**) into that folder and normally continue working on the project, as we learned in the previous example. 199 | 200 | You can also clone public GitHub repositories from other developers using the same steps where you first find a copy the repository URL and then use it in the **git clone** terminal command. 201 | 202 | ## Branching and Merging 203 | The general rule is that the **master** branch of your GitHub repository should always contain working and stable code. However, you may want to also push some code that you are currently working on, which may be unstable or not fully tested. Usually, that happens when you are adding a new feature to your code, but still want to push that code to GitHub. 204 | 205 | With branching, we can create a separate copy of our project code, without touching the **master** branch which holds our stable code. We can make a new branch that creates a separate version of our code, which we can then work with to implement our feature. Then, when we fully integrate and test our new feature, we can merge it back to our **master** branch. 206 | 207 | #### Pushing a branch to GitHub 208 | So, when we are working on code modifications or a new feature locally, we usually want to create a new branch for that feature, so we don't make changes directly on the main **master** branch, which should only contain stable code. 209 | 210 | For example, if we wanted to add a new file to our **hello-world** project, you can switch to a new branch by typing this from the project folder: 211 | 212 | ```bash 213 | git checkout -b new-feature 214 | ``` 215 | Then, you can create a new sample file called **example.js**, and add the following code: 216 | 217 | ```jsx 218 | console.log("New greeting!"); 219 | ``` 220 | After that, run the standard steps to commit the new changes to the **new-feature** branch: 221 | 222 | ```bash 223 | git add . 224 | git commit -m "Add new greeting" 225 | ``` 226 | 227 | To push the **new-feature** branch to the **hello-world** remote repository on GitHub, run this command: 228 | 229 | ```bash 230 | git push origin new-feature 231 | ``` 232 | If you refresh the **hello-world** GitHub repository page, you will see that there is a new branch pushed. 233 | 234 | 235 | #### Creating a Pull Req 236 | 237 | We create a pull request to notify the project owner (or the team leader) that we want to implement some changes from our custom branch to the main **master** branch. 238 | 239 | The pull request will allow developers to review and verify the changes, before allowing them to be applied to the **master** branch, which usually only holds the **stable** version of our code. 240 | 241 | To create a pull request, we need to press the following button (from the same interface shown in the last screenshot): 242 | 243 | ![Creating a pull req](img/pr-requests.png) 244 | 245 | After that, we will be redirected to a page that allows us to open a pull request. There, we can specify the title of our pull request and leave a comment describing the changes we have made: 246 | 247 | 248 | ![Creating a pull req description](img/pull-request-description.png) 249 | 250 | 251 | To submit your pull request, click the green **'Create pull request'** button, as shown in the screenshot. 252 | 253 | After that is done, other collaborators can review the pull request, analyze the code changes directly, and add their comments about the pull request. 254 | 255 | When the changes from the request are reviewed by yourself (or other team members if you are not working alone) and they don't have any conflicts with the **master** base branch, then the pull request can be approved and merged. 256 | 257 | After you merge the pull request, it offers to delete the *new-feature* branch since the code is now added to the **master** branch. 258 | 259 | After a successful merge, you should see the changes on the **master** branch, and the commits from the custom (*new-feature*) branch will also be added to the **master** branch. 260 | 261 | >> Keep in mind that in some scenarios the branch can have conflicts with the base branch, so the button may not be green. This happens where there is a change in a file that conflicts with a different file, so Git cannot automatically decide which version to use. In this situation, a developer may need to manually review the code and solve the conflicts in order to finalize the merge. 262 | 263 | Also, if you are the only person working on the project (or in a very small team where you don't have a specified project leader), then you may not need to go through the process of creating a pull request via GitHub to integrate your changes. However, it still may be a good practice to have a complete history of the project updates listed as pull requests. 264 | 265 | Check the following GitHub guides: 266 | - [Understanding the GitHub flow](https://guides.github.com/introduction/flow/) 267 | 268 | 269 | #### Pulling changes from GitHub 270 | After making changes or merging branches via pull requests on GitHub, the remote repository may look different from the local repository on your computer. To get the latest changes from the remote GitHub repository, we use the **git pull** command. 271 | 272 | When we are working on a team project which is hosted in a remote GitHub repository, we want to use the **git pull** command to get the latest version of the code in our **master** branch, which may have been updated by other developers in our team. 273 | 274 | If we associated the GitHub remote repository link to the **origin** alias (like we did in the **hello-world** repository example), then we can use the following command to pull any changes from the remote repository to the main **master** branch in our local project: 275 | 276 | ```bash 277 | git pull origin master 278 | ``` 279 | 280 | When we are up to date with the remote branch, we can then work to further develop the project code or add new features. 281 | 282 | ## Forking projects on GitHub 283 | When using GitHub, you may find yourself wanting to use someone else's repository as a starting point of your project. Also, you may want to contribute to a third-party project, which is very popular in the open-source community. Contributing to other projects can also be a great way to build your knowledge and experience, as well as your portfolio! 284 | 285 | The process where we create our copy of someone else's project is called **forking**. 286 | 287 | So, a **fork** is your personal copy of a repository owned by someone else. 288 | 289 | If you are looking to contribute to a project, you can create new *pull requests* from the **forked** project to offer your changes to the owners of the original repository. 290 | 291 | #### Forking a repository 292 | 293 | There is a sample repository called *Spoon-Knife* hosted by GitHub, which they created for testing purposes: [https://github.com/octocat/Spoon-Knife](https://github.com/octocat/Spoon-Knife) 294 | 295 | We will be using this repository to test the **Fork** feature of GitHub. Go to the repository page by following the link above and click the '**Fork'** button, as shown in the screenshot below: 296 | 297 | 298 | ![Forking a repo](img/forking.png) 299 | 300 | 301 | #### Working with a forked repo on your local machine 302 | To clone the forked repository, visit its page from your GitHub profile and select the green 'Clone or download' menu button, then click on the icon shown in the screenshot to copy the repository URL that we will need to use: 303 | 304 | 305 | ![Opening the repo in local device](img/cloning-existing-repo.png) 306 | 307 | 308 | Then, to download the remote repository to your computer, execute the **git clone** command with the link that you just copied: 309 | 310 | ```bash 311 | git clone https://github.com//Spoon-Knife.git 312 | ``` 313 | 314 | That will create a new folder called *Spoon-Knife* and download all the project files and repository data into it. You can then change directories (**cd**) into that folder and start working on the project. 315 | 316 | After making changes or implement new things to the forked project, you can normally add and commit those changes as you would do for any other repository. 317 | 318 | Also, you can push the changes that you made to the forked (remote) repository tied to your GitHub account. 319 | 320 | #### Proposing changes to the original project 321 | 322 | After you made changes to the project which could potentially benefit the original project that you forked and you want to help improve the open-source community, you can consider offering to contribute your changes. 323 | 324 | This can be done using a similar procedure that we went through in the last section, by creating **pull requests** to the original project repository. 325 | 326 | After pushing the changes that you made to your fork, you can create a **New pull request**: 327 | 328 | 329 | ![Creating a pull request](img/pr-requests.png) 330 | 331 | 332 | That will lead you to the new pull request page where you can also add information about your changes. 333 | 334 | In situations where you are trying to contribute to a third-party project of a developer that you don't know, it's especially important to provide a good detailed description of everything that you've done. Based on that and the code changes, the original project owner can decide if they want to implement your changes to their project. 335 | 336 | After adding information about your changes, you can finally send a new pull request to the original project owner. 337 | 338 | ## Concluding words 339 | 340 | GitHub offers the possibility to have a centralized remote repository when using Git with our project. We can publish our projects and efficiently work with other developers and teams using GitHub. We can also browse all the available open-source projects on GitHub, use them to create our projects or contribute to someone else's project. 341 | 342 | To learn more about GitHub and it's powerful features, check their Help page and Guides: 343 | 344 | - [https://help.github.com](https://help.github.com/) 345 | - [https://guides.github.com/](https://guides.github.com/) 346 | 347 | GitHub also has [a desktop application](https://desktop.github.com/) which offers a graphical user interface when working with their service. However, it's a much less popular method of using GitHub (compared to the command-line interface using a terminal). 348 | 349 | Also check **GitHub Gist**, which is an easy way to share your code, notes or other snippets: [https://gist.github.com/](https://gist.github.com/) 350 | 351 | **GitHub Pages** is a popular service for hosting web pages via GitHub. You can learn more about it here: [https://guides.github.com/features/pages/](https://guides.github.com/features/pages/) 352 | 353 | They also have official video guides which you can find [on this link](https://www.youtube.com/githubguides). 354 | --------------------------------------------------------------------------------