Software

A practical guide to building an interactive and fully-featured web application from scratch with Node.js and MongoDB

Web development technology moves at a very fast pace with new tools and techniques being released daily. It is impossible to learn them all, but choosing similar technologies allows you to step up your game while developing web applications. Web applications are often split into two parts: the front end and the back end. Using Node.js for logic and MongoDB for persistence, a single person can develop a real-time web application in no time. Node.js is based on JavaScript, which makes it easily adaptable for a wide-variety of platforms. It is also lightweight, and handles a huge number of simultaneous connections.

Web Development with Node.js and MongoDB will show you how to build powerful web applications from the ground up. Starting with the simplest "hello world"-based script and moving on to more and more advanced techniques, this course will show you what is possible while building your application.

We'll begin with some of the basic concepts of Node.js, Express.js, and MongoDB and build on this knowledge with practical examples. With each concept, the application will get more powerful and you will be able to process any business logic you may need.

We will then learn about Express.js to make web applications and MongoDB to persist your data. Then you will find out how to build on the shoulders of giants by consuming a RESTful API or become a giant by serving your own API. Later on, you’ll get to grips with automatically testing your application to make sure it is functioning properly.

At the end, we will take a look at deploying our application and improving its performance. The course closes with suggestions on further improvements that can be made to the application.

Who this course is for

If you wish to build a complete web application using JavaScript, this course is for you. The course will teach you a lot about what is required to build web applications, but you should have a basic knowledge of HTML / CSS and most importantly JavaScript before starting the course.

What you will learn from this course

• Write scripts in Node.js and understand when Node.js is the right tool for the job and when it should be avoided
• Master the article of writing modular applications
• Improve the quality of the application by persisting and manipulating data with MongoDB database
• Build on the shoulders of giants by consuming your data through the RESTful API
• Focus on the value by better understanding and quality through automatic testing
• Improve customer retention and loyalty by ensuring your application stays fast and reliable
• Introduce your application to the world by deploying it on the cloud

Course Length: 3 hour and 54 minutes

• Learn how to set up your computer, install a local server, as well as find and use a hosting service
• Pick up the essentials of designing web pages, adding navigation, modifying images, and adding images
• Discover how to create a database and connect your website to that database
• Understand the purpose and need for server side and client side applications
• Learn how to make a website change colors, images, and more, when users interact with a page
• Discover how to set up user sign-ins, set up shopping carts, and use social media for marketing
• Learn how to test your site on all of the major browsers
• Understand how to make a mobile version of your site

This course shows you how to use a range of AWS services to create intelligent end-to-end applications that incorporate ingestion, storage, preprocessing, machine learning (ML), and connectivity to an application client or server. The course is designed for data scientists looking for clear instruction on how to deploy locally developed ML applications to the AWS platform, and for developers who want to add machine learning capabilities to their applications using AWS services. Prerequisites include: Basic awareness of Amazon Simple Storage Service (S3), Elastic Compute Cloud (EC2), and Amazon Elastic MapReduce; as well as some knowledge of ML concepts like classification and regression analysis, model types, training and performance measures; and a general understanding of Python.

• Understand how to use Amazon Web Service's best-in-class streaming analytics and ML tools
• Learn about Amazon data pipelines: A very lightweight way to deploy an ML algorithm
• Explore Redshift and RDS: Databases that stage input data or store model outputs
• Discover Kinesis: A streaming data ingestion service that performs streaming analytical functions
• Learn to apply streaming and batch analytical processing to prepare datasets for ML algorithms
• Gain experience building ML models using Amazon Machine Learning and calling them using Python

John Hearty is a data scientist with Relic Entertainment who specializes in using Amazon Web Services to develop data infrastructure and analytics solutions. He is the author or co-author of three highly regarded books on machine learning (e.g., Packt Publishing's "Advanced Machine Learning with Python") and holds a Master's degree in Computer Science from Liverpool John Moores University.