Learn Git, Leaflet and Python

If you've ever worked on a website for a business, there's a good chance you've included a map.

A Google Map embed is sufficient for showing a location, but doesn't leave you many customization options.

React Leaflet to the rescue!

In this course, Colby Fayock will guide you through a series of lessons and challenges that will build your map making skills as you build out a web app for a fictional restaurant.

You'll get practice with handling API keys and using React Hooks to implement a custom interactive map complete with metadata and additional overlays.

This course has built-in challenges that you are encouraged to pause and work through, but feel free to just watch.

React is one of the web’s most popular frameworks for building JavaScript applications. 

If you know what you’re doing, React can drastically simplify how you build, use, and maintain code.

Whether you’re a React newbie or you’re ready for advanced techniques, you can level-up with egghead. Explore our in-depth courses, lessons, and community resources to build more powerful applications and crack open your career.

react

Build Maps with React Leaflet

This workshop will start by breaking down the four states in which a file can exist, and we'll build up our mental model of git from there. Then, we'll look at how to move files between those states in different ways.

Once we've developed a new model for how git operates, we'll be able to purposefully get ourselves into some sticky situations, and then gracefully recover from them.

If you can handle git add/commit/push, but not much more - then this workshop is perfect for you.

You can finally get some proper git training, and will never have to worry about losing data or messing up the repo again!

Git is a free and open source distributed version control system designed to handle everything from small to very large projects with speed and efficiency.

Fix Common Git Mistakes

In this collection, you'll learn the basics of creating a new map in your React application with React Leaflet. We'll walk through adding the map itself as well as adding markers with popups, different shapes, and increasingly complex features to your map!

Mapping with React Leaflet

Knowing your everyday toolset increases your productivity as a developer. And Git is one of those tools you use on a daily basis. Mastering Git is tough; it has hundreds of different commands, often even inconsistent at how you pass in flags and configuration options. On the other side, there are a lot of good Git courses out there already, explaining all of these commands in detail. 

With this course, I aim at a different goal. You will walk through a series of scenarios which you’ll most commonly encounter in your daily work life as a developer. I’m talking:
 - updating your feature branch with the latest changes from master
 - polishing your git history to make it ready for being peer-reviewed
 - moving a set of commits to another branch
 - undoing accidental commits

The goal is not to cover everything, but those tasks that will greatly improve your daily productivity with Git.


Productive Git for Developers

Neural networks, with Keras, bring powerful machine learning to Python applications. They can answer questions like “How much traffic will hit my website tonight?” or answer classification questions like “Will this customer buy our product?” or “Will the stock price go up or down tomorrow?”

In this course, we’ll build a fully connected neural network with Keras. This is the most basic type of neural network you can create, but it’s powerful in application and can jumpstart your exploration of other frameworks. 

We’ll start the course by creating the primary network. Then we’ll:

- build and configure the network, then evaluate and test the accuracy of each
- save the model and learn how to load it and use it to make predictions in the future
- expose the model as part of a tiny web application that can be used to make predictions

You don’t need to know a lot of Python for this course, but some basic Python knowledge will be helpful. Enjoy!

Python is a widely used dynamically typed programming language. It allows for many different programming paradigms including object-oriented, imperative, functional programming, and procedural styles.

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Fully Connected Neural Networks with Keras

In Introduction to Python, we will start at the beginning: Installing python 3 and using virtual environments. With a working environment, we will learn how to manipulate strings and numbers, and gain working knowledge of data structures and flow control. We will build on that by introducing modules and classes and learn how to interact with our python applications using command line switches, console input and files.

At the end of this course, you’ll have a great working knowledge of Python, fully capable of creating your own Python projects from scratch or jumping into an existing application with the capability to read, understand, and contribute to the application.

Check out these [**community notes for this course on Github**](https://github.com/eggheadio-projects/introduction-to-the-python-3-programming-language-notes).

Introduction to the Python 3 Programming Language

Artificial intelligence. Machine learning. Bots. Computers learning and communicating with us to do our bidding. But, where do you start? How do you get a machine to even begin to understand what you speak or type at it? There are several common machine learning algorithms that will help us begin to answer these questions.

In this course we’ll learn about common machine learning algorithms that don’t require implementing a neural network. We will not be going too much into the math behind them, but instead learn what each algorithm is good for, and how to train them. We'll also learn about a few metrics for evaluating models.

We’ll implement these in Python using `scikit-learn` using `scikit-learn`’s built-in data sets. The focus of this course is on implementation and a high-level understanding of these algorithms. 

We'll look at a few ways to evaluate our models, for both classification and regression models. We'll touch on mean squared error and coefficient of determination (for regression), and accuracy score, logarithmic loss, confusion matrices, and classification reports (for classification). 

Python 2.7 is used in the lesson videos but the code provided has Python 3 available. The only breaking change is the `print` statement API.

For additional information on installation, vocabulary, and common errors visit the `README.md` to the course code attached to each lesson.

Simple and efficient tools for data mining and data analysis

scikit-learn

Introductory Machine Learning Algorithms in Python with scikit-learn

As modern web developers, we are likely to use git on a daily basis. It's a wonderful distributed version control system, and with only a few commands in our toolbelt it is quite powerful and convenient.

In this course, you will learn the basics of using git, as well as some more advanced commands that you should find useful!

Check out these [**community notes for this course on Github**](https://github.com/eggheadio-projects/practical-git-for-everyday-professional-use-notes).

Practical Git for Everyday Professional Use

“Feel free to submit a PR!” - words often found in GitHub issues, but met with confusion and fear by many. Getting started with contributing open source is not always straightforward and can be tricky. With this series, you’ll be equipped with the the tools, knowledge, and understanding you need to be productive and contribute to the wonderful world of open source projects. Much of this series speaks about GitHub, but most of the concepts are generally applicable to contributing to any open source project, regardless of where it’s hosted.

So enjoy the course and start contributing to the projects you use and love today!

How to Contribute to an Open Source Project on GitHub

AWS Amplify allows developers to create, configure, and deploy Serverless APIs and functions directly from their front-end environment.In this collection, you'll learn how to deploy various types of APIs and functions using the Amplify CLI. You'll also learn how to share code among various functions using Lambda layers and schedule functions to run at an interval to implement Serverless cron jobs.

JavaScript® (often shortened to JS) is a lightweight, interpreted, object-oriented language with first-class functions, most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic, and supports object-oriented, imperative, and functional programming styles.

javascript

Up and Running with AWS Amplify Functions

Learn how to create tuples in Python. The videos in this collection will also cover more advanced features of tuples

The Ins and Outs of Python Tuples

Misunderstanding scope can cause problems in your application. Watch this lesson to learn how Python scope works and the hidden implications it presents. Local scope, nonlocal scope, and global scope variables are demonstrated and explained.

Understand Scope in Python

A module is a function extracted to a file. This allows you to import the function and use it in any other code you may write. You’ll learn how to create modules, import them, and make them stand-alone as you learn what `if __name__ == “__main__”` means in Python.

Reuse Code in Multiple Projects with Python Modules

Why should you have to write all the code? Why can’t you leverage code written by others? I’ve got great news: you can. You’ll learn how to search pip, Python’s package installer, to find and install packages to add new features and functionality to your application.

Manage packages with pip in Python

Object oriented classes work much like classes in other languages. Learn how to create them and use them, learn the difference between class variables and instance variables, creating class methods, and learn how to create classes that inherit from other classes.

Use Python Classes

Most projects have automatically generated files or folders from the operating system, applications, package managers etc. Usually, we don't want to include these types of things in our remote repos because they can clutter the git history/storage and are not applicable to everyone that works on the project. In this lesson, we show how to create a `.gitignore` file to ignore files and folders from being tracked by git.

Practical Git: Remove unnecessary git tracking with .gitignore files

Getting input from the user via a console command can be done with `input` in Python. Learn how to implement it and validate user input in this lesson.

Read Input in Python from the Console

Exceptions cause your application to crash. Handling them allows you to recover gracefully and keep your application running. Learn how to handle exceptions, find what exceptions you should be handling, and exit gracefully in this lesson. You will also learn how you should *not* handle exceptions and when it is better to let your application crash rather than swallowing an exception. 

Handle Exceptions to prevent crashes in Python

When working with Git, the most common thing developers do is stage, commit, and push the changes they make to a code base - this "edit -> stage -> commit -> push" cycle is the main workflow when using Git; it lets developers make "snapshots" of changes to their codebase which they can share and revert back to. In this lesson, we make some changes to our codebase and then `git add` (stage), `git commit` (store in history), and `git push` (sync with our remote repository) those changes. We also use `git status` along the way to see an update of where our repository is at.

Practical Git: Capture code history snapshots with git add/commit/push

`git pull` lets us get the latest changes from our project's remote repo (most likely from co-workers or other developers working on our project) and merge (combine) them with our local code. It's kind of like Dropbox for code, but you tell git when you want it to get the latest changes from the remote when it is most convenient for you. In this lesson, we use `git pull` and discuss how it is a shortcut for running `git fetch` and `git merge`.

Practical Git: Sync local and remote repos with git pull

When working on a project, it is much easier to work on features and bugs in isolation of the rest of the project. We can do this with git branches; a branch is a copy of the working directory, staging area, and project history; we create a branch, then check it out, then add commits. After our feature has been built, we can then merge it back into the main stable branch - which is `master` by default. In this lesson we go over how to create a branch with `git branch {branch-name}`, viewing all branches with `git branch`, switching branches with `git checkout` plus a few helper commands.