Learn Aws, Mac and Python

In this course, we'll build a video course platform using the AWS Amplify Admin UI. 

The Admin UI provides simple yet powerful tools to model database tables, add authentication and authorization, and manage app content, users, and groups. It also offers the ability to manage the application users and content. 

The AWS Amplify Admin UI focuses on data types rather than backend infrastructure. 

All the backend resources generate infrastructure as code (IaC) templates that can be committed in the team repository and integrated with AWS Amplify continuous deployment workflow to manage the different environments.

Before taking this course, you should have a basic understanding of React Hooks.

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

Get Started with the AWS Amplify Admin UI

Amazon AWS is one of the most popular cloud providers in the world, but it can also be daunting to learn thanks to the alphabet soup of service acronyms.

Once you've figured out which subset of services to use, you've got a lot of clicking around to do in order to get things configured.

Not anymore!

With the AWS Cloud Development Kit (CDK), you are able to configure AWS services from your terminal & editor.

Even better, you can do your configuration, frontend, and backend all with the same language. 

In this course, Tomasz Łakomy will guide you through using TypeScript to complete the lifecycle of an application powered by AWS CDK. You'll see how to start a project, develop it locally, deploy it globally, then tear it all down when you're done.

The services & development approach Tomasz demonstrates in this course are used by countless companies around the world. 

Is yours next?

Amazon Web Services (AWS) is a powerful expansive cloud infrastructure platform for building modern web applications.

AWS provides services for data, presentation, authentication, security, video encoding, and much more. Offering over 175 fully-featured services from data centers globally, AWS powers a large percentage of the internet.

Build an App with the AWS Cloud Development Kit

We generally tend to avoid paying for things unless we actually need them, and the same goes for AWS

When using a cloud provider like AWS sometimes an unexpected charge may occur and we'd like to understand what are we being charged for and how to be notified whenever an unexpected charge occurs (especially when we're trying to stay within a free tier).

In this quick (4 minutes, 2 lessons) collection we're going to learn how to:

- Review the AWS Billing & Cost Management Dashboard
- Set up a billing alarm to be notified whenever our bill is larger than $5
- Review the AWS bill to understand how much are we going to pay this month and why

Use AWS Billing & Cost Management Dashboard to keep your AWS bill to minimum

**View and Contribute to the [Community Notes](https://github.com/eggheadio-projects/learn-aws-dynamodb-from-scratch)!**

Learn AWS DynamoDB from scratch

This collection includes introductory level material for AWS DynamoDB. We cover what DynamoDB is, when you'd use it, and the vocabulary you'll need to understand documentation and talks in the ecosystem.

You'll come out of this playlist with the ability to understand what people mean when they say DynamoDB and the base you need to get started yourself.

**View and contribute to the [Community Notes!](https://github.com/eggheadio-projects/intro-to-dynamodb)**

Intro to DynamoDB

Building larger serverless applications can be tricky - creating many lambda functions as well as other resources such as DynamoDB tables, S3 buckets, API Gateways using AWS Console takes quite a lot of time. Not to mention other problems such as redeploying the app to a different region, reviewing the infrastructure etc.

**AWS Serverless Application Model** (**AWS SAM** for short) simplifies a lot of those issues 🤩

Built with with best practices in mind, SAM allows you to:

🌟define your infrastructure as code using a YAML template (which can go through code review!)

🌟define resources such as lambda functions, DynamoDB tables etc. in a much simpler way than doing it directly in CloudFormation (which SAM is built on top of)

🌟build and deploy a serverless application from a command line

🌟debug and test lambda functions locally using SAM CLI

🌟debug and test lambda functions from WITHIN your editor with AWS Toolkit extension


Add AWS SAM to your toolkit with this quick collection!

**View and Contribute to the [Community Notes!](https://github.com/eggheadio-projects/build-serverless-applications-with-aws-sam)**

Build serverless applications with AWS Serverless Application Model (AWS SAM)

Bash makes automation easy. Just a few lines of code can take care of repetitive tasks for you and your teammates. 

In this course, we’ll dive deep into the automation potential of bash. You’ll learn to leverage common hooks that open up interesting automation possibilities, like git hooks, adding functions and aliases in your bash_profile, and running scheduled jobs in launchd.

For example, we’ll write a git hook that checks package.json for changes, and if there are changes, the hook runs npm install for you automatically. 

Along the way, you’ll also learn:

- more advanced bash commands like exec
- syntax such as redirecting stdout and stderr to the same destination
- timesaving tricks like brace expansions

Automation is all about saving you time — and at only 52 minutes, this course is well worth yours. Enjoy!

Bash is a Unix shell and command language written by Brian Fox for the GNU Project as a free software replacement for the Bourne shell. Bash is a command processor that typically runs in a text window, where the user types commands that cause actions. Bash can also read and execute commands from a file, called a shell script.

bash

Advanced Bash Automation for Web Developers

This collection is a sequel to the [Building a Serverless JAMStack Todo app with Netlify, Gatsby, GraphQL, and FaunaDB](https://egghead.io/playlists/building-a-serverless-jamstack-todo-app-with-netlify-gatsby-graphql-and-faunadb-53bb) collection. In this collection we take the TODO application we built and convert it to run using Netlify Identity, AWS Lambda (using the serverless framework) and DynamoDB. We cover

* Fauna vs DynamoDB and when to use each
* Setting up AWS accounts
* Creating DynamoDB tables and data modeling differences between Fauna and Dynamo
* Converting our Netlify Functions deployment to a Serverless Framework deployment
* Implementing Custom authorizer functions on AWS

It uses tools that remove as many of the barriers as possible. Netlify Functions grows into Serverless Framework adn AWS Lambda, Netlify Identity is kept around, and FaunaDB can grows into DynamoDB.



FaunaDB is a global serverless database that gives you ubiquitous, low latency access to app data, without sacrificing data correctness. It eliminates layers of app code for manually handling data anomalies, security, and scale, creating a friendlier dev experience for you and better app experience for your users.

faunadb

Converting a Serverless App to run on AWS Lambda and DynamoDB with Serverless Framework

React makes it intuitive to build real-world web application. But in reality, you need to use a host of other services to get the app in front of real users. 

This course walks you through setup and implementation to get your cloud-based application up and running. 

You’ll learn to set up:
* a new project in AWS Amplify configured to your React app
* user authentication with Amazon Cognito 
* managed GraphQL with AWS AppSync
* image storage and retrieval with Amazon S3
* text translation via Lambda functions
* and finally, deployment of your application on AWS using Amazon S3

You’ll finish the course ready to quickly and easily deploy your serverless React application, so users can start using and enjoying it right away.

React Native lets you build mobile apps using only JavaScript. It uses the same design as React, letting you compose a rich mobile UI from declarative components.

react-native

Building Serverless Web Applications with React & AWS Amplify

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.

python

Fully Connected Neural Networks with Keras

With GraphQL, you can define the shape of your data in a schema, and GraphQL will fulfill the request with the precise data you need. When you need it. This doesn't come without a cost. GraphQL adds a lot of complexity to your application by requiring you to define your schemas through types, mutations, and resolvers.

AppSync is a fully managed serverless GraphQL service that fast-tracks your API development. You can define a single type, and AppSync auto-generates a schema, queries, mutators, and subscriptions for you.

In this course, Nader Dabit will show you how to:

- build a production-ready GraphQL API through AWS AppSync
- create and modify data through the AWS AppSync console
- connect a React application to the GraphQL API
- execute queries, mutations, and subscriptions for data through the API in React

GraphQL is a query language for APIs and a runtime for fulfilling those queries with your existing data. GraphQL provides a complete and understandable description of the data in your API, gives clients the power to ask for exactly what they need and nothing more, makes it easier to evolve APIs over time, and enables powerful developer tools.

graphql

Scalable Offline-Ready GraphQL Applications with AWS AppSync & React

AWS Lambda, Serverless, FaaS - there is a lot of noise around those topics online (and for a very good reason!) and it can get confusing at times 🤯

In this collection we're going to take a look at AWS Lambda from scratch, in order to get **YOU** from:

"_I have no idea what a lambda function is_" 

to 

"_I know quite a bit about AWS Lambda, and I'm going to use it to solve my problems_"

Checkout the [community notes for this collection on github](https://github.com/theianjones/egghead.io_learn_aws_lambda_from_scratch).

Learn AWS Lambda from scratch

The core of serverless architectures are auto-scaling systems and a pay-per-execution pricing. Two traits that allows developers to significantly reduce operational cost and complexity, by outsourcing infrastructure management to cloud providers and focus on building business logic.  

In this course we walk through the basics on how to create a serverless API. We start off creating a simple HTTP endpoint. Then we build the first two endpoints of a REST API for a simple Todo Application backend storing the data in DynamoDB. After watching this course you will be ready to get started building you first serverless backend.

Develop a Serverless Backend using Node.js on AWS Lambda

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

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

This playlist will get you going with the Amplify Console, including showing you how to host your website, integrate continuous integration and continuous delivery, set up a custom domain, and enable pull request previews.

Up and Running with Amplify Static Site Hosting

This playlist covers all of the ways to use the node.js DocumentClient to interact with one or more DynamoDB tables.


note: We do not cover scan() as it is not recommended for most usage and if you need it you'll know how to read the documentation to use it by the end of this collection.

Node.js is a platform built on Chrome's JavaScript runtime for easily building fast, scalable network applications. Node.js uses an event-driven, non-blocking I/O model that makes it lightweight and efficient, perfect for data-intensive real-time applications that run across distributed devices.

node

DynamoDB: The Node.js DocumentClient

Joe Previte is an active egghead instructor and blogger. This is a collection of screencast versions of selected blog posts. You can find his blog here: [joeprevite.com](https://joeprevite.com/)

Joe's Blog Posts as Screencasts

The videos in this playlist will get you started building serverless applications using AWS SAM. It covers

* Setting up your AWS credentials
* Building and deploying a Lambda
* Testing your Lambda locally
* Cleaning up your AWS account once you've finished

Introduction to AWS SAM

Learn how to use the [AWS Cloud Development Kit (CDK)](https://docs.aws.amazon.com/cdk/latest/guide/getting_started.html#getting_started_install) to create and deploy a [DynamoDB table](https://aws.amazon.com/dynamodb/) with [Next.js](https://nextjs.org).

- 🛠 API Route to handle CRUD actions
- 📦 AWS CDK for Infrastructure as Code
- 🔓 IAM role to restrict permissions
- 🚀 Deploy instantly to [Vercel](https://vercel.com)

You can view the completed code [here](https://github.com/leerob/nextjs-aws-dynamodb). 

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