From virtual reality to cybersecurity to office productivity and bookkeeping, the applications of technology continue to expand into almost every aspect of our daily lives. And, because of this growth, learning to program can not only lead to a stable, fulfilling career but also help you reach out to and help those in need.

There are a variety of tech-based jobs and volunteer opportunities where you can apply your programming knowledge to social good projects. If this is something you’re interested in pursuing, our courses can give you the skills you need to improve the world around you however you choose. Continue reading to learn about just a few of the many opportunities available for you to do some social good.

Open-source projects

Open-source projects for social good can range from helping a non-profit organization create an app to helping improve government services. These projects encourage collaboration from people around the world and allow anyone to use the final product for whatever purpose that can help their organization.

Contributing to these open-source projects can help countless individuals that may not otherwise have the resources to access technological guidance. But not only would your skills help support those in need, you’d also be joining a community of programmers helping each other to assist organizations and non-profits, which is a great networking opportunity.

If you’re interested in building your coding skills to pursue a job or volunteer position in the open-source sector, our courses can get you started with the basics.

And, if you’re not sure where to start, check out our Learn Java course. Java is one of the most popular programming languages — used for software development, large systems development, and mobile applications — and it’s a great place to begin your coding journey. Another popular language is Go, which powers much of Google’s cloud platform and can be used in web and application development. Take a look at our Learn Go course for more information.

Each of these programming languages will give you a strong base to start working on whatever open-sourced project you’re interested in.

Teach coding

The programming community is one of collaboration, and whether you’ve been a long-time programmer or are just starting out, you’ll always have something to learn and share. Using the programming knowledge you’ve gained — whether it’s to build websites, mobile apps, or chatbots — to teach others can make a world of difference in someone’s life.

For teaching opportunities, there are several organizations that focus on teaching the youth of varying backgrounds to focus their talents on learning tech skills they can use now and in the future. Two popular organizations are Teens Exploring Technology and Girls Who Code Another great nonprofit is MotherCoders, if you’re interested in teaching adults.

Support social change

Humanitarian projects are often in need of technical support to both organize their efforts and keep them running smoothly. This is an opportunity for you to use your programming skills to help organizations continue their vital work while not having to worry about technical issues.

Some organizations, like Bayes Impact, focus on creating new public services under the support of local governments. The citizens themselves design and promote services that are relevant and aid the people in their communities.

Other projects involve using programming skills to assist non-profit groups around the world, like Code the Change. This has resulted in meaningful work, such as programmers creating an application to track malnutrition in foreign countries. Using your coding skills for projects like this can have impactful results that you’ll be proud to share with others.

Computer science is a Career Path we offer to help you gain a strong foundation for a professional programming career. Learn Python is another course that can teach you skills to use for anything from software and web development to scientific applications. These courses can give you the skills to support a variety of projects aimed at promoting social good.

Work remotely

Using your programming skills can do a lot of good for many different types of companies, non-profits, and educational programs. A number of these positions can be done remotely. This could increase the opportunities you have to help organizations not only in your neighborhood but around the world.

You may be able to help create applications for projects that don’t require you to be on-site. This can allow you to collaborate with a nationally or globally distributed team working toward the same goal. Each of these jobs requires different skills, so starting your coding education can get you on the right track to support social good without needing to leave your home.

Also, keep in mind that there are organizations that support remote workers and volunteers in their own continued education. So  while you’re helping an organization meet their goals, you can also continue advancing your career goals as well.

Our courses are a great stepping stone to first educate yourself, which enables you to then educate and support others. Organizations around the world need programming and technical support to accomplish their missions. They need programmers willing to give their time and resources to support them so they can help those in need.

To get started with web design, check out courses like Learn HTML, Learn CSS, and Learn Navigation Design. You can also start a Skill Path towards creating web applications by taking Build Python Web Apps with Flask.

Each of these courses will help you to gain the knowledge necessary to start helping organizations around the world that need your technical skills. Begin your path to programming for social good by signing up for our courses today, free of charge.

Web Development Courses & Tutorials | Codecademy

Web Development is the practice of developing websites and web apps that live on the internet. Whether you’re interested in front-end, back-end, or going full-stack, the content in our Web Development domain will help you get there.

Java Tutorial: Learn Java Basics For Free | Codecademy

Learn the basics of the popular Java language in this introductory course. ☕️

When most people think of virtual machines, they tend to think of those once-futuristic virtual reality sets or a way to play old video games on your modern computer. But those aren’t the virtual machines we’re talking about here. So, what is a virtual machine exactly, and what do they have to do with developers?

We all swear by our operating systems. Whether you use macOS, Windows, Linux, iOS, or Android, you probably have a list of reasons why your operating system is superior. That’s okay — we’re the same way.

But, if you’re going to make it as a developer, you’ll have to explore other operating systems if you want your applications and web pages to work everywhere. If you’re working on a Mac, how exactly will you know that your program works in Windows? And who’s to say that the amazing web app you designed for Android will look the same in iOS?

This is why developers love virtual machines. And, after reading this article, you will too once you understand what they are, how they work, and why people use them.

Your operating system and you

Before we get into the details of virtual machines, it’s important first to understand what an operating system is and how it works.

Computers, smartphones, and tablets are all made of physical components or hardware. Hard drives, processors, batteries, fans, and memory cards are all part of the hardware.

An operating system (OS) is software that directly controls the hardware components in your computer or device. macOS, Windows, Linux, iOS, and Android are all programmed to control hardware in different ways.

When you use an application on your computer or device, your OS uses the device’s hardware components to run that application.

What is a virtual machine?

As long as your computer or device has the hardware capacity — enough memory, processing power, and so on — you can run just about any application through your OS, as long as the software code is compatible with it. You could even run an application that looks and feels like you’re using an entirely different OS.

And that’s exactly what a virtual machine is. It’s a software application designed to look and run like an OS different from the OS installed on a computer, mobile device, or even server.

How a virtual machine works

To run a virtual machine (VM), you need to work with a host computer or server that provides the hardware resources. This is called the host machine. Each virtual machine on a particular host machine is called a guest machine.

To manage hardware resources, host machines and guest machines rely on a special type of software called a hypervisor. A hypervisor partitions — or reserves — some hardware capacity for the virtual machine, such as CPU, memory, and storage. That way, the virtual machine is kept isolated from the rest of the host machine system.

When you use a virtual machine, the operating system will only recognize the resources allocated to it. For example, if you have a computer with 16 GB of RAM and your hypervisor gives 4 GB of RAM to the virtual machine, then the system settings in your virtual machine OS will show that you’re using a computer with 4 GB of RAM.

If the virtual machine requires more than its allocated resources at any point, then the hypervisor manages the request to ensure that the host machine is always performing within its limitations.

Why use a virtual machine?

Anyone involved in software development — Front-End Developers, Back-End Developers, and Full-Stack Developers — can benefit from using a virtual machine. That’s because VMs offer a lot of testing flexibility. You can even break things without consequences!

Here are the biggest advantages of virtual machines:

Run multiple operating systems at the same time

The biggest advantage of using a virtual machine is running another — sometimes several — different operating systems at once. The only limiting factors are the hardware resources of the host machine.

This means that whenever you’re developing applications or software, you can effectively test your work on multiple operating systems without having to buy another physical machine or use a different server.

Access the power of a server from anywhere

If you’re using a server or host machine, then you have access to the server’s processing power as long as you have an online connection to it. Theoretically, you can write, run, and test high-performance programs from a laptop or even a tablet.

Complete system isolation

If you’re designing an application, the last thing you want is for the program to crash your entire system because of a bug you overlooked.

Virtual machines give developers a virtual sandbox to test their applications before running them directly on a physical machine. If there’s a disk crash within your virtual machine environment, it won’t affect the disk’s partition of the host machine.

Disadvantages of virtual machines

Although virtual machines offer plenty of advantages that make them a great choice for developers, they don’t offer the perfect solution. In particular, virtual machines reduce system efficiency and add network complexity.

Virtual machines are less efficient

When you run an application on your computer’s native OS, the OS can directly access the computer’s hardware resources. But, with a virtual machine, partitioned hardware resources are available only indirectly. When you run an application on a virtual machine, the VM first requests access to hardware resources through the host machine OS. This makes virtual machines slower and less efficient than if they were running as a native-installed OS.

Virtual machines add network complexity

It can be challenging enough to manage and secure a network of physical machines, and adding virtual machines doesn’t make it any easier. If you’re planning to use a virtual machine in your next development project, make sure you’re ready to do a little extra IT work to keep your VM secure or talk to your IT team.

Use a virtual machine for your next development project

When you’re ready to start learning how to create your first app — whether it’s a front-end React app, a back-end JavaScript app, or a Python app with Flask or Django — consider using a virtual machine to see how it works in different OS environments.

If you’re not sure how to get started with your first app, take a look through our Career Paths. We’ll help guide you toward picking up the skills you need to succeed in your new development career.

Web Development Courses & Tutorials | Codecademy

Web Development is the practice of developing websites and web apps that live on the internet. Whether you’re interested in front-end, back-end, or going full-stack, the content in our Web Development domain will help you get there.

Deep learning is one of the hottest up-and-coming job sectors in the world, with a market currently ranging between $3.5 and $5.8 trillion. On average, a Deep Learning Engineer earns $135,878 a year, but salaries can climb even higher.

The job prospects for Deep Learning Engineers are looking good as well, with a projected growth rate of 11% a year between now and 2029.

Deep learning, a subset of machine learning, plays a critical role in the way people gather and analyze data and how they use it to automate everything from statistical analysis to self-driving cars. Read on to learn what deep learning is, how it works, how it’s used, and the programming languages you need for a career in deep learning.

The basics of deep learning

Deep learning is a kind of machine learning where a computer analyzes algorithms and their results to “learn” ways of improving processes and creating new ones.

A deep learning system consists of a series of levels. Each level learns how to translate its input data into a composite representation that is slightly more abstract than before it reached that level.

Then, that information is passed to the next level, which does the same thing before passing it to the subsequent level, and so on. In this way, the system acquires an increasingly accurate representation of the data it’s processing.

For example, a deep learning system designed for facial recognition may process an image of a face in this manner:

1. Layer 1 may turn the overall shape of everything in the image of the face into pixels, assigning them to a grid.
2. Layer 2 may group different sets of edges according to shapes. Instead of one grid of all the pixels in the image, there may be several smaller grids representing the contours of different elements of the face.
3. Layer 3 may recognize that the shapes organized in Layer 2 correspond with a nose, eyes, and mouth.
4. Layer 4 may then take the information from layer 3 and recognize that this image has a face in it.

The deep learning system can also decide which features belong at which level all by itself. Even though it can do a lot without human intervention, the system may need to be manually told how many layers it needs to have to attain a deep enough understanding of the data.

In the facial recognition example above, for instance, a few more layers would have to be added to enable the system to differentiate one person’s face from another’s. The computations of a deep learning system depend on artificial neural networks to function.

What are artificial neural networks?

Artificial neural networks consist of nodes that receive data from and send data to other nodes in the network. They’re designed to imitate the neural network of the human brain.

Each node is programmed with a specific weight and threshold. If the output value of a node falls above the threshold, the node gets activated, and it then sends data to the following layer in the neural network.

In deep learning, a neural network is used to discover patterns, more efficient ways of doing things, and new processes designed to accomplish specific goals.

How deep learning works

Deep learning hinges on programming a neural network to learn.

Each node in the neural network activates according to programming rules, and the deep learning model studies how and when the nodes get activated. It then learns about the process and can provide insights into how it can be improved.

Here’s a simple example of how deep learning can use a neural network to teach itself how to improve a process:

Suppose you have a machine in a factory with a few moving parts that could pose a safety hazard if touched by a human or their clothing. Proximity sensors are set up near the machine, as well as at specific distances away from it. Each proximity sensor indicates when someone has crossed that specific distance from the machine, and their data is fed into a deep learning system.

The nodes in the deep learning model collect information regarding where someone goes after passing each proximity sensor. It also calculates the likelihood of someone going to the next sensor after crossing the one before it.

It could output data such as “There’s an 85% chance that someone 12 feet away from the machine will eventually get 3 feet away from it as they travel between sensors A, B, C, and D.”

The deep learning model can then use the data it collects to learn:

• When people should be warned about getting too close to the machine
• When to automatically shut the machine off if someone gets too close
• The safest way to pass by the machine without getting too close or unnecessarily inhibiting your movement through the factory

With this data, the system can help employees move around safely while still traveling freely enough to get things done quickly. It can even be used to project the optimal path of travel on the factory floor or guide automated vehicles as they transport people by the machine.

All of this learning hinges on how the nodes in the neural network process data.

Deep learning vs. other types of machine learning

As we explained earlier, deep learning is a subset of machine learning. In other words, all deep learning is machine learning, but not all machine learning is deep learning. Other types of machine learning are often more basic and simple than deep learning.

For example, basic machine learning can be used to examine a database that holds information about sales revenue, month-by-month marketing costs, when sales associates work, and the times of day sales are made.

It can then tell a Sales Manager who the most effective sales reps are on Friday afternoons in August and how to adjust their compensation to reward outstanding performance.

Deep learning, on the other hand, can figure out more complex problems. For example, deep learning is used to provide vision to self-driving vehicles. The deep learning system can collect data regarding:

• Objects surrounding the vehicle
• How fast objects are moving in relation to the vehicle
• The direction of travel of moving objects

It then uses this data to make decisions like:

• How hard and when to apply the brake if there’s a danger of collision
• How to differentiate objects from each other, such as a ball from a dog or human
• How to adjust the steering of a vehicle given the speed and trajectory of another vehicle alongside it

How deep learning is used

Along with industrial automation and automated driving technologies, deep learning is used in:

• Defense systems. It can identify objects and areas of interest, ensuring it’s safe for troops to land in a specific spot.
• Medical research. Deep learning can automatically differentiate cancer cells from healthy cells.
• Automatic speech. You can use deep learning to listen to and study speech, as well as generate more human-like speech patterns.
• Cybersecurity. With deep learning, computer software can detect cyber threats based on their behavior within a network.
• Image recognition. Deep learning can be used to recognize the kinds of images presented to the system, such as people’s faces, vehicles, machinery, and the vehicles or weapons of enemy combatants.
• Text generation. A deep learning model can learn the grammar and punctuation rules of a language and generate text that reads like a human wrote it.
• Adding color to pictures and videos. Before deep learning, people had to add color to black and white images manually. Now, deep learning systems can automatically add a full-color spectrum.

Programming languages for deep learning

Deep learning systems can be programmed with several different languages. Sometimes, the language chosen may depend more on the computer or system processing it than the problem the deep learning system is trying to solve, especially because algorithms can be written in a variety of languages.

We can teach you some of the most popular deep learning languages, including:

With our courses, you’ll gain a solid foundation in the languages used to write deep learning programs, such as those above. You can also take advantage of specific Skill and Career Paths that incorporate deep learning, such as:

We’ll also help you develop an extensive portfolio of your work while you learn, making it easier to land a job as a deep learning professional. Get started today!

Machine Learning Courses & Tutorials | Codecademy

Machine Learning is an increasingly hot field of data science dedicated to enabling computers to learn from data. From spam filtering in social networks to computer vision for self-driving cars, the potential applications of Machine Learning are vast.

Swift first appeared on the scene in 2014, but it’d been in development behind the scenes for years before then, thanks to some hush-hush development by Apple. When it finally emerged, it was hailed as a user-friendly language that enables the development of fast, effective solutions.

There are several other languages to choose from, so you may be wondering if you should invest the time in learning  Swift or not. Keep reading to learn how it’s used, the kinds of developers that should learn it, and how our courses can help you get started learning this up-and-coming language.

What is Swift?

As a programming language that was developed by Apple as an alternative to Objective-C, Swift is used for a wide variety of applications. But, it’s most commonly used by developers to build apps for Mac OSX, iPhone, Apple Watch, and Apple TV.

Since every operating system Apple has released after OSX 10.9 and iOS7 is compatible with Swift, it’s a great language to learn if you’re interested in iOS and MacOS development.

With some of the best aspects of Objective C, Swift is also a convenient language for developers working outside iOS and MacOS development, like Game Developers who rely on it to produce fast and readable code.

Also, as of September 2020, there’s official support available for the full Swift ecosystem on the Windows platform, opening up an even wider range of developers who may want to tap into this powerful, general-purpose language.

Why learn Swift?

One of the most appealing features of Swift is its efficiency, which ultimately saves programmers time during the dev life cycle. The Apple developers who created Swift actively sought to make it a more convenient programming alternative, and based on its popularity, their hard work paid off.

As Swift has grown in popularity, it’s become a to-go for many organizations. So, learning Swift will make you an appealing candidate for open roles and make it easier for you to address concerns and improve application performance immediately after starting a new job.

Here are some other reasons to learn Swift, some of which may appeal to new programmers and others to developers who are already fluent in other languages.

Swift provides better management of memory

Swift’s ability to help you manage memory more efficiently is a big plus for many developers, mainly because of the significant role memory plays in developing and operating applications.

If a function of an app uses too much memory, it can cause the app to slow down, and other apps running simultaneously can also suffer performance issues. Plus, in some cases, if too much memory is being used it can cause the app to shut down or force a reboot.

Because Swift makes it easier to manage memory through automated management features, you have a few convenient options. You can check how much memory is allocated to specific functions of your app and make decisions with a higher degree of certainty, but you can also rely on Swift’s own automatic memory management functions.

This memory management feature could make a big difference for end-users, particularly those that run several apps at the same time.

Compatibility with Apple devices

As mentioned above, Swift was designed by Apple engineers, partly to make a solution that’d play well with Apple devices. Apple reported $274 billion in revenue in 2020, and half of that came from the sales of iPhones.

Apple’s iPhones have become ubiquitous in the mobile device universe, so knowing Swift will make it easier to make apps for businesses without having to worry about compatibility.

Swift offers convenient error handling features

Errors are a natural part of the development process, and Swift’s creators understand this reality. Swift’s error handling system is designed to make it easier to recover in the event of an unexpected error.

This feature can save you time, effort, and human resources. As a result, the cost of development, whether you’re on a large DevOps team or doing freelance work, goes down, increasing relative profits.

Who should learn Swift?

Swift is useful for the majority of programmers, but the following types of developers may see the most benefit.

iOS Developers

Anyone who wants to code for the following Apple operating systems should learn Swift:

• iOS
• iPadOS
• tvOS
• macOS
• watchOS

While it’s possible to design apps for these devices without Swift, having this language in your portfolio can make it easier to develop quality Apple solutions in a shorter period of time.

Those who want an easy-to-learn programming language

Apple is known for making its operating systems and devices as user-friendly as possible. This tradition was carried through to the design of the Swift language as well.

Swift streamlines the development process, and even though some may, at first, feel it’s a “young” language, it can still be used to create comprehensive, end-user-friendly solutions.

Because Swift is relatively new and typically not among the top 10 most popular languages, its development community is a tight-knit group that’s known to be supportive of each other.

This can be a comfortable safety net for someone just getting their feet wet with Swift. The general advice and specific help you get may make it easier to get into the Swift swing of things.

How to learn Swift

Learning Swift is straightforward with our help. Our courses and Skill Paths simplify the process while giving you the knowledge and practice you need to become a Swift expert. Check out the following courses and Skill Paths to get started:

Learn Swift | Codecademy

A powerful programming language developed by Apple for iOS, macOS, and more.

Markdown is a text-to-HTML conversion tool for web writers. It can make writing text for the web a breeze and simplify formatting. As John Gruber, one of the co-creators of Markdown, explains:

“Markdown allows you to write using an easy-to-read, easy-to-write plain text format, then convert it to structurally valid XHTML (or HTML).”

In other words, a variety of programs understand Markdown and can convert it to readable text.

In this article (and in the video below), we’ll take a closer look at Markdown and how it works.

Why do we use Markdown?

Markdown is a simple, beginner-friendly way to format plain text. It’s not the best tool for everything, but it definitely has its place. Here’s an analogy that might help:

If you had an intensive project building furniture, a nail gun would be helpful. It’s fast and powerful. But, if you were hanging up a picture on your wall, a nail gun wouldn’t be right for the job — a hammer and a nail would work just fine and be just as fast.

Similarly, Markdown may not be as full-featured as HTML, but it’s fast, simple, and beginner-friendly. In fact, you may use it from time to time already. Reddit and GitHub both encourage users to format their comments using Markdown. You can also use it in text editors like Evernote.

How does Markdown work?

Gruber, who we heard from earlier, goes on to explain that Markdown is composed of two things:

• A plain text formatting syntax.
• A software tool, written in Perl, that converts plain text formatting to HTML.

Markdown vs. HTML comparison

To help illustrate how Markdown works, let’s take a look at how it compares to HTML. Here’s how you’d create a header, hyperlink, and list in Markdown:

## What is Markdown?
See [Markdown](www.markdownlink.com)
**List of tips**
1. *One asterisk makes the text italicized.*
2. **Two asterisks make the text bold.**

And here’s how the code above will look once rendered:

Of course, you can achieve these effects using Microsoft Word, but it tends to be more tedious. Unless you know the shortcuts for everything, you’re constantly stopping the flow of your writing to bold, italicize, change headings, and make bulleted or numbered lists.

Of course, another option is HTML.

What is Markdown?
See Markdown
List of tips

  
One asterisk italicizes
  
Two asterisks bold

This HTML code is written to produce the same result as the Markdown code above. Here’s how it looks once rendered:

As you can see, HTML is more complicated, especially for a beginner. You have to remember to close every tag. It’s very easy to make mistakes. While HTML is somewhat intuitive once you know it, Markdown is significantly more so.

How to use Markdown

You can save files written in Markdown with .Markdown or .md as the extension. From there, you need a Markdown application that’s capable of processing the Markdown file.

Markdown applications use a Markdown processor to take the Markdown text and convert it into HTML, which is then viewable on the web. Or, you can export the Markdown into other formats like PDF or Docx.

Where can Markdown be used?

The best places to use Markdown include:

• Websites: Markdown was designed for the web. It’s especially good for straight-forward, text-heavy sites like blogs. It’s also used on websites with a significant amount of user-generated content, like Reddit and Evernote.
• Documents and notes: If you want to write a quick note or document without having to stop, reach for your mouse, and click buttons to format, Markdown can come in handy. It’s also handy for writing to-do lists, and several apps support it, including WriteMonkey and SublimeText.
• Email: Some email clients (like MailMate and Airmail) support Markdown. You can also write an email in Markdown and export it to your email client or install a browser extension.
• Technical documentation: Writing technical documentation is already involved. It makes sense to use a streamlined formatting system that allows you to focus on what you’re saying rather than your formatting.

How to learn Markdown

The best way to learn Markdown is to use it. Here are some of Markdown’s formatting symbols and what they mean.

There are several online Markdown editors that you can take for a test drive. Markdown Tutorial walks you through a basic tutorial. Dingus is another option for trying out Markdown, and you can find more options here.

Next steps

Markdown is useful and easy to learn, but it’s also limited. For example, you can’t change colors or fonts. If you want to do more, you’ll need to branch out into other languages, such as HTML/CSS.

HTML provides the structure of web pages. CSS takes things a step further by defining the layout of the page and adding stylistic elements. To start learning either language, check out the courses below:

We also have a Skill Path that teaches you how to build websites from start to finish. It covers HTML, CSS, responsive design, accessibility, and more. You’ll also complete projects that you can add to your portfolio to show off your skills to current or prospective employers.

Web Development Courses & Tutorials | Codecademy

Web Development is the practice of developing websites and web apps that live on the internet. Whether you’re interested in front-end, back-end, or going full-stack, the content in our Web Development domain will help you get there.