Learn Glamorous, Next and Python

### Accept payments & sell products powered by Stripe and the best of the JAMStack

There are as many ways to build an e-commerce store on the internet as there are products to sell. One thing is for certain, e-commerce is here to stay and as professional developers we need to understand how to build fully custom stores for our clients using the best modern tools available.

- React: flexible and customizable while following modern best practices
- Next.js: lightening fast with guide rails to help your project perform as consumers expect
- Stripe Checkout: lets you offload reams of complicated business logic to a trusted third party that maintains regulatory compliance, global payments, and a standard UX.

Your store will have well managed local component state using React Hooks and you'll also have clear and cohesive shared (global) state with React Context.

Finally you'll deploy your custom store to Vercel (the platform behind Next.js) as well as how to make your Next.js e-commerce store portable to deploy to other platforms.

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

Create an eCommerce Store with Next.js and Stripe Checkout

With the release of `Next.js` v9+, we've been handed the tools to create full-stack react apps with ease. 

This collection will dive into the fundamentals of API & Dynamic routing, handling data from local json and a DB, plus deployment options. 

This collection will be an ongoing collection, where I continue adding more videos over time 😃

Next.js is a minimalistic framework for server-rendered React applications.

Next.js 9 Fundamentals

Add Conversation Intelligence to your video or voice application without training Machine Learning models. Integrate speech to text and all of the below capabilities, out of the box:

- Speaker Diarization
- Sentiment Analysis
- Contextual Insights
- Conversational Analytics
- Topics of Discussion
- Entity and Intent Recognition
- Pre-built UI and Symbl JS Elements

In this course we will use [Symbl.ai](https://symbl.ai/) to get transcripts for the video we will upload as well as more meaningful insights. 

Additionally, you will pick up NextJS for the main stack and will use Symbl's RESTful APIs for processing a conversation from a video and rendering transcripts to screen. Get your Symbl account [here](https://platform.symbl.ai/) and start building.

Create Contextual Video Analysis App with NextJS and Symbl.ai

(This collection is still WIP)

Databases are essential for any full-stack applications, but working with them is traditionally very difficult. Prisma is here to change that. It's a powerful database toolkit that helps us think in data itself - not SQL, not classes, just the data we care about in our apps.

In this series, we will learn how to leverage the power of Prisma to automatically generate a type-safe, autocomplete-ready, and efficient query builder, all based on a simple and easy-to-read schema. We will integrate all this good stuff into a Next.js project to complete a simple social network app.

In the end, you will be able to understand how Prisma works, and confidently start using Prisma in your own project.

Prisma is a next-generation open-source ORM For Node.js and TypeScript that helps developers build faster and make fewer errors.

It supports the following databases: PostgreSQL, MySQL, MariaDB, SQL Server, SQLite, and more recently, MongoDB (Preview).

Prisma provides a complete toolkit:

- Prisma Client: Auto-generated and type-safe database client
- Prisma Migrate: Declarative data modeling and customizable migrations
- Prisma Studio: Modern UI to view and edit data


prisma

Build a full-stack app with Prisma

[Next.js](https://nextjs.org/) is a fantastic framework that allows us to build performant server-side rendered React apps with ease.

In this series, we will learn how to utilize the powerful features of Next.js 9, like API routes and Static Site Generation (SSG), to build full-stack React apps. We will use [Auth0](https://auth0.com) to handle user authentication and authorization, and we'll also learn how to integrate the excellent [Chakra UI](https://chakra-ui.com/) component library into our Next.js project to make it a breeze to build beautiful and modularized user interfaces. Finally, we will import and deploy our project from GitHub to [Vercel](https://vercel.com), the deployment platform built by the creators of Next.js.

This collection will still be continuously updated with new and more advanced content. Subscribe to the RSS feed to get notified of the latest lessons!

Introduction to Next.js 9

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

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

After completing this course, you will be able to build well-designed user interfaces without spending a lot of time (if even) styling every component and element. You will drastically simplify your front-end work and learn to modify and build on top of existing design systems.

Chakra UI is a React components library with built-in accessibility. It comes with a modern-looking design system that's easily extendable and configurable. The simple styling API significantly reduces development time, so developers can quickly prototype their ideas and achieve the desired style and "brand" by editing a single file. 

**The result of using Chakra UI is a well-designed app that's accessible out-of-the-box, achieved with minimal effort and time.**

In this course, you'll learn how to build a checkout UI. 

![checkout UI](https://res.cloudinary.com/dg3gyk0gu/image/upload/v1631148385/Chakra-UI-Course.png)

In the first phase of the course, you will learn all about the built-in components. Then we will override the theme, add custom fonts and colors, and make our UI unique.

This course provides all the design files to follow along. [You can download them here](https://www.figma.com/file/vOcnzw9yT05grSCD1ji7ax/egghead.io---Introduction-to-Chakra-UI?node-id=802%3A9205).

Build a Modern User Interface with Chakra UI

Supabase is an open-source tool for rapidly building application backends with real-time data and authentication. In this course, you'll learn the fundamentals of Supabase. You'll learn how to model complex data using PostgreSQL and SQL, build authentication flows with Oauth, and add real-time data to a Next.js application to build a fully-featured chat application, similar to Discord.

The chat app will have different "channels," which will be powered by data inside of Supabase. Users can visit these channels and write messages, which will be sent in real-time to other current users of the platform.

After this course, you will be able to model real-world scenarios in actual relational databases, understand how to manage real-time data, and leverage key functionality provided by Supabase, such as authentication, instant APIs, and real-time subscriptions.

Supabase is an open source Firebase alternative. A service to:

- Listen to database changes.
- Query your tables, including filtering, pagination, and deeply nested relationships (like GraphQL).
- Create, update, and delete rows.
- Manage your users and their permissions.
- Interact with your database using a simple UI.

Supabase is not a 1-to-1 mapping of Firebase. Most notably, Supabase uses Postgres rather than a NoSQL store. 

supabase

Build a Real-Time Data Syncing Chat Application with Supabase and Next.js

Notion is a note taking application that empowers super productive workflows, without compromising on beautiful UI or intuitive UX. Next.js is a React framework that sprinkles in server-side logic in the places it is needed. This allows each page to be dynamically rendered by the client, rendered by the server or entirely static and rendered at build-time. This makes it an incredibly flexible option that can start off as simple as `create-react-app` and incrementally introduce complexity as the application evolves. 

In this course, you will learn how to pre-render static pages with data from the Notion API. We will cover querying `page`, `block` and `database` data, as well as updating properties with mutations, and some helpful techniques for transforming raw responses into convenient data structures for our React components. Using Incremental Static Regeneration (ISR), we will learn about dynamically creating static pages any time new data is available in Notion. 

We will be building two example applications - a recipe app and a movie picker. The data for these applications will live in Notion, and be queried by Next.js at build time. This allows us to use Notion for its delightful authoring experience, and Next.js to make this data publicly available via super performant static pages.

Build Static Pages Dynamically using Next.js and the Notion API

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). 

Using DynamoDB with Next.js

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

Next.js is a React framework that provides a solutions to problems such as:

- 🌟 bundling & transpiling your React code
- 🌟 code splitting
- 🌟 being able to switch between client side rendering & server side rendering depending on the page (e.g. landing page vs. settings page)
- 🌟 client-side routing

In this collection we're going to learn how to harness the power of Next.js + TypeScript and how to work with Netlify in order to deploy our site for others to enjoy!

Learn how to:
- 🔥 Create a new Next.js project
- 🔥 Add TypeScript support
- 🔥 Create styled components with Emotion
- 🔥 Use both static and dynamic routes
- 🔥 Generate fully typed static pages
- 🔥 Set up Netlify deployments
- 🔥 Add a Netlify Form to our site
- 🔥 and more!

Build a site from scratch with Next.js, TypeScript, Emotion and Netlify

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

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. 

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