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CONTRIBUTING.md

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+# Contributing to Learn.co Curriculum
+
+We're really exited that you're about to contribute to the [open
+curriculum](https://learn.co/content-license) on [Learn.co](https://learn.co).
+If this is your first time contributing, please continue reading to learn how
+to make the most meaningful and useful impact possible.
+
+## Raising an Issue to Encourage a Contribution
+
+If you notice a problem with the curriculum that you believe needs improvement
+but you're unable to make the change yourself, you should raise a Github issue
+containing a clear description of the problem. Include relevant snippets of
+the content and/or screenshots if applicable. Curriculum owners regularly review
+issue lists and your issue will be prioritized and addressed as appropriate.
+
+## Submitting a Pull Request to Suggest an Improvement
+
+If you see an opportunity for improvement and can make the change yourself go
+ahead and use a typical git workflow to make it happen:
+
+* Fork this curriculum repository
+* Make the change on your fork, with descriptive commits in the standard format
+* Open a Pull Request against this repo
+
+A curriculum owner will review your change and approve or comment on it in due
+course.
+
+# Why Contribute?
+
+Curriculum on Learn is publicly and freely available under Learn's
+[Educational Content License](https://learn.co/content-license). By
+embracing an open-source contribution model, our goal is for the curriculum
+on Learn to become, in time, the best educational content the world has
+ever seen.
+
+We need help from the community of Learners to maintain and improve the
+educational content. Everything from fixing typos, to correcting
+out-dated information, to improving exposition, to adding better examples,
+to fixing tests—all contributions to making the curriculum more effective are
+welcome.

LICENSE.md

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+# Learn.co Educational Content License
+
+Copyright (c) 2018 Flatiron School, Inc
+
+The Flatiron School, Inc. owns this Educational Content. However, the Flatiron
+School supports the development and availability of educational materials in
+the public domain. Therefore, the Flatiron School grants Users of the Flatiron
+Educational Content set forth in this repository certain rights to reuse, build
+upon and share such Educational Content subject to the terms of the Educational
+Content License set forth [here](http://learn.co/content-license)
+(http://learn.co/content-license). You must read carefully the terms and
+conditions contained in the Educational Content License as such terms govern
+access to and use of the Educational Content.
+
+Flatiron School is willing to allow you access to and use of the Educational
+Content only on the condition that you accept all of the terms and conditions
+contained in the Educational Content License set forth
+[here](http://learn.co/content-license) (http://learn.co/content-license).  By
+accessing and/or using the Educational Content, you are agreeing to all of the
+terms and conditions contained in the Educational Content License.  If you do
+not agree to any or all of the terms of the Educational Content License, you
+are prohibited from accessing, reviewing or using in any way the Educational
+Content.

README.md

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+
+# Running Jupyter Notebooks Locally
+
+## Introduction
+
+In this lesson you will practice the workflow you will be using when you want to work _locally_ instead of in IllumiDesk on Canvas, and also get some hands-on practice with important tools that you will need to be familiar with as a professional Data Scientist: the command line, git, GitHub, and running Jupyter Notebooks locally.
+
+## Objectives
+You will be able to:
+
+* Use basic commands to navigate the command line
+* Use bash commands to create new files and folders
+* Use git clone to clone a repository
+* Work on your labs locally
+
+## Setting the Stage
+
+Remember **Code Lessons** and **Labs** on Canvas and how you need to use Illumidesk (by clicking the grey button below) to start coding? 
+
+<img src="images/illumidesk_4.png" width="900">
+
+When you're a professional Data Scientist you won't have access to Illumidesk, but you'll need to get everything up and running to work on your local machine. Luckily, you've already set up a professional data science environment a few lessons back, but in this lesson you'll learn how to actually run your code on your local machine instead of by using Illumidesk!
+
+## The Command Line
+
+In order to be able to work locally, we first need to tell you a tiny bit about command line. On Mac computers, this is the terminal application. On Windows computers, we'll use "Git Bash". The command line serves as a low-level interpreter through which you, the user, can send commands directly to the computer. As a computer user, you previously have probably sent commands to the computer through a graphical user interface (GUI) such as a web browser, text editor, photo editor, or any other of the myriad of computer programs now in existence. While the command line is initially daunting with its cryptic looking text, we will quickly see some of the many advantages it can have.
+
+One of the many useful features of the command line will be using *git* to clone (download) a local copy of the curriculum hosted on Canvas. This will allow you to work offline and to save changes as you work through exercises and start programming! 
+
+To start, **for Mac users, open the terminal application**, **for Windows, open “Git Bash”**.
+
+### pwd
+
+The first command to try out is **pwd** which stands for **print working directory**. This will tell you where you currently are in the computer's directory structure. Try it out.
+
+### cd
+
+The next essential command is **cd** which stands for **change directory**. This allows you to navigate to different folders on your computer's hard drive. Typing cd by itself will automatically take you to your home directory. Typing cd and a folder name will take you to that folder. Typing cd .. will move you one folder up in the hierarchy. Play around and trying moving between folders for a minute or two.
+
+### Tab Completion
+
+An extraordinarly useful feature when working with the command line is tab completion. This allows you to hit the tab button to autocomplete names once you have made a unique specification.  
+
+
+For example, if you navigate to your root directory by running the command **cd**, if you're on a Mac, you will probably have 2 folders within your root directory named "Downloads" and "Documents" (these are standard folder names created by default in most systems, although you may have renamed them, or your system may be different). With these, or longer folder names, it can sometimes become cumbersome to type the full folder name. instead, you can start typing the command and folder name such as **"cd Dow"** and then press **tab** to autocomplete. Like magic, the command line should complete the statement correctly to be **cd Downloads**. (Note: this will not work if you have another folder that begins with "Dow". Similarly, if you just typed **cd D** or **cd Do** followed by **tab**, the command line will not autocomplete, as the selection is not unique, because **D** or **Do** could both refer to either **Documents** or **Downloads**. Also note that these commands are case sensitive, and folder capitalization much be matched exactly.
+
+### ls
+
+Continuing with navigating the computer's hard drive, it's useful to know how to **list files**. This is done with the **ls** command, short for list.
+
+You can also pass optional parameters to ls such as **ls -a** which lists **all files** (including hidden files), **ls -l** gives a **long listing** of files (including file size and last edit times). You can also pass multiple parameters simultaneously such as **ls -al** to produce a detailed listing of all files.
+
+### * the wildcard parameter
+
+Also very useful is the wildcard parameter. For example, if you wanted to list all files in the current working directory that begin with a, you could type **`ls a*`**. Here, the asterix (`*`) denotes anything is allowed following the a. Similarly, to list all pdf files in the current working directory you can use **`ls *.pdf`**, or to list all text files, you can use **`ls *.txt`**.
+
+### mkdir
+
+Finally, as you continue to navigate the file directory from the command line it can be useful to be able to create new folders. To do this, use the **mkdir** command, which stands for **make directory**. Try it out with **mkdir NewFolderName**. Afterward, use the **ls** command to see that there is indeed a new folder, and if you wish, move into the new folder using the **cd** command.
+
+## Cloning GitHub repositories and Learn.co lessons
+
+You have already read a little bit about GitHub and how it's used to share code. Since you can now navigate the file directory using the command line, you're ready to download some course materials from GitHub to your local environment. In practice, you will do the following:
+
+* **Fork** the course material repository: Forking is the process of making a personal copy of the Canvas course materials on your own GitHub account.
+
+* **Clone** the forked course material repository: Cloning is the process of downloading a repository from Github onto your personal computer. 
+
+Don't worry if this process seems a little confusing. It will be explained in more detail soon. For now, you can just follow the steps below: 
+
+* Create a folder on your computer for your course materials and navigate into it  
+* Then create a subfolder titled "module_1" and navigate into that 
+* Return to your web browser and navigate to the lesson you want to download 
+* Click the GitHub icon 
+
+<img src="images/illumidesk_3.png">
+
+You'll be redirected to the associated GitHub repository like this.  
+
+* **Click the fork button**, as shown in order to create a copy to your personal account which you can edit and update.
+* 
+<img src="images/before-fork.png">
+
+One of two things will happen. Either it'll pop up a modal (window) and if you scroll to the bottom of it you'll see it says that you already have a fork. That is quite possible - Learn auto-forks certain lessons for you. If that's the case, just click on the link to view your existing fork.
+
+If you don't already have a fork, you'll be redirected to your new personal copy of the repository:
+
+<img src="images/after-fork.png" width="900">
+
+## Finally 
+* Press **cmd + L** to highlight the url bar and **cmd + c** to copy the url (whenever we use `cmd` to refer to holding down the command key on a Mac computer, on a Windows computer, hold down the control key instead)
+* Return to the terminal (you should be in your "module_1" folder)
+* Type: **git clone** and paste your repo url (**cmd + v** for Mac; for Windows, in git bash, **shift + insert**)
+* Et Voila! The repository and all of its contents will be downloaded locally to your computer!
+* Remember that you then need to **cd** into the new repository once you've downloaded it
+* The next step is to open your Jupyter Notebook locally (**not on Canvas**) using the command line
+
+## Starting the Jupyter Notebook
+
+Make sure to activate your conda virtual environment in your terminal first by typing `source activate learn-env`. Then type `jupyter notebook` in your command line and press enter. Next, your default browser will open a new window or tab and you will see the list of files that are in your current directory (*remember you want to be in the GitHub repo directory that we just downloaded*). 
+
+> **Note:** *To stop a Jupyter Notebook, go to your command line where the notebook is running and press the **control** key + the letter **c*** (**`ctrl`**+**`c`**).
+
+Then click on the `index.ipynb` file which is the Jupyter Notebook we will be using in this and future labs and lessons. This will open a new tab where you will see the same content from Learn!
+
+## Summary
+
+In this lesson, you learned about the command line, cloning GitHub repositorites, and how to work with Jupyter notebooks locally. In the next lab, you'll put what you learned into practice!