The best coding languages for your next job

Learn these languages to launch your career

Programming languages

Career changes are tough, but you’re tougher. Here, we’ve gathered advice from TripleTen grads to help you along your tech journey — let’s land that dream job!
The most common programming languages
Highest-paying coding languages
Coding language comparison
Is it hard to learn to code?
How to learn to code
Our pitch to you
The most common programming languages
List of programming languages
Choosing the best programming language can be hard for novices. When beginners decide to pursue tech careers, questions inevitably come up. What’s the easiest programming language to learn? What are the highest-paying programming languages? Is coding hard?
Don’t worry. This article will give you an inside line on the most in-demand programming languages, web programming languages, and front-end languages. If you’re looking to land an entry-level coding job, these languages are your best bet.
Top languages by career
Software Engineer
  • JavaScriptFor years, JavaScript has been the most popular language. It’s easy to see why. It’s one of the easiest languages to learn, and it’s also key in web development applications. Software developers use this language to craft games, bring interactivity to web pages, build apps, and more. Many coders spend most of their time using this language.
  • HTML/CSSWe’ve combined these two into one entry because they rely on each other. HTML says what should go where on the page, and CSS adds to what HTML can do. It provides instructions on styling. In short, HTML is about the basic content and structure, and CSS handles the design and display.

    These are both key pieces of technology to know in addition to JavaScript, as all three work together. JavaScript handles interactivity, HTML handles what goes where, and CSS handles how it all should be presented.
    ‍Note: HTML is a markup language as opposed to a programming language, and CSS is a stylesheet language. But, no matter what you call them, they are crucial for software developers.
  • PythonThis is a powerful programming language. It is a top choice for machine learning applications. In addition, it is also one of the most-used programming languages — it’s behind everything from self-driving cars to online video recommendation algorithms.

    Programming skills in Python are in demand across diverse industries. That means this language is a reliable choice if you want to be a software engineer on the cutting edge of tech. Interested in working as an artificial intelligence engineer? Python might be for you.
  • SQL (Structured Query Language)When data needs to be accessed, SQL is often invaluable. It enables programs to interact with databases. Software engineers apply this capability for a wide array of uses. For example, when you sign up for an account via an app, your username and password are stored in a database. When you log in later, that information needs to be verified, and if you’ve forgotten your password, that information needs to be changed. That’s where SQL comes in.

    Being able to interface with data is crucial beyond apps, too. In fact, SQL is a key language for healthcare and marketing. This makes SQL a great language to master for aspiring software engineers.
Data Scientist
  • PythonData science is heavy on building predictive models. That means it uses the machine learning and artificial intelligence capabilities of Python. As such, data scientists often spend a good deal of their time working in this language. In fact, data scientists and software engineers frequently collaborate to generate scalable predictive systems. Read more here.
  • SQLData scientists focus on understanding data and then building systems to put it to use. This data is stored in databases, and SQL is the language that lets people talk to databases. Because of this, knowledge of SQL is crucial for professionals in this field.
  • RData scientists use R due to its statistical capabilities that enable in-depth data analysis and modeling. When this is augmented with visualization, data comes alive. It is made informative, accessible, and visually appealing. This can help a data scientist wrangle their main focus: data.
  • Other common tools for data scientistsWhile data science and data analysis seem quite similar, the focuses are different. This is reflected in the tools that augment these languages. For example, data scientists need to know more than basic Python. They also need to be fluent in Python libraries such as Pandas, Scikit Learn, NumPy, and Torch.

    And just as data science asks for deeper and wider expertise in Python, it also requires a little bit more knowledge of databases and SQL. For example, data scientists also should have a good understanding of data warehouses like Snowflake and Redshift.

    Also, since data scientists spend so much time using AI, they should be skilled in machine learning programs such as Keras.

    Want to know what all that means? We can teach you.
Data Analyst
  • PythonData analysts, much like data scientists, focus on extracting value from data. However, instead of building predictive models, their responsibilities lie more in understanding data and deriving insights from it. While they should know Python to perform forecasting and to automate some of the data analysis, they do not need to be as well-versed in Python libraries.
  • SQLData analysts need to access data. That means they should know SQL, the language that lets people interact with databases. For more info, check out the sections on SQL in the Software Engineer and Data Scientist sections above.
  • Other common tools for data analystsData analysis and data science overlap in their languages, but they differ in the additional tool sets used. Whereas data scientists really go deep into machine learning, data analysts focus on tools for visualizing data, exploratory data analysis, and hypothesis testing. This can include Tableau, Power BI, Google Sheets, and Excel.
Business Intelligence
  • SQLBusiness intelligence applies data analysis techniques to business information. That makes it similar to the previous two roles, but it differs in important ways. It focuses on reporting, dashboards, and data visualization and storytelling. As it is a data profession, knowing SQL to interact with databases is crucial.

    Other BI tools include Excel, Tableau, and Power BI.
Quality Assurance
  • JavaScriptQA is about breaking software, catching bugs, and pushing programs to make sure they’re robust. To accomplish this, QA engineers often use simple scripts. This makes it possible for them to run tests that would be tedious or unfeasible for a human. Think of things like load testing, in which thousands and thousands of requests are sent in seconds. This makes sure that the software doesn’t break under high demand, but one tester can’t generate that volume. Scripts can.
  • BashQA engineers use this for the same reason they use JavaScript. This and other shell scripting languages help them automate repetitive testing tasks. This makes their work more efficient, less error-prone, and adds to the range of cases they can test.
  • SQLSometimes, QA engineers need to make sure the right data was stored, deleted, or updated. As such, they need to know the language that will let them interact with databases: SQL. Knowing this language will make QA testers more desirable to employers because QA professionals who know SQL will be able to generate tests for a wider range of scenarios.
  • NoneThis is an important caveat for QA. So far, we’ve been discussing automated QA. However, there is also manual QA, and the market for manual testers is quite strong. In manual QA, engineers interact with software in unintended ways without writing scripts or code. For example, they enter words in fields that should only accept numerals and document what happens.

    Knowing scripting and programming languages will expand your professional prospects in QA. But it is still easy to find a QA job if you have experience with tools such as Postman, Charles, Jira, and Android Studio.
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Highest-paying coding languages
A recent survey by StackOverflow looked into the highest-paying programming languages. As you’ll see, niche languages can often be the highest-paid. Here they are:
This is in contrast to the most popular programming languages as demonstrated in the survey:
There is a correlation between having rare skills and getting a high salary. One thing to note is that Python, JavaScript, HTML, and SQL were all on the list of well-paid languages as well. They simply did not place in the top 10. Their salaries were:
Coding language comparison
We could get into the weeds in this section. We could talk about how Python is different from other coding languages in excruciating detail. We could explore full stack languages and even go deeper and talk about how to convert JavaScript to Python. Instead, we’re going to give you an introduction to common programming concepts for background. Then, we’ll get into a quick summary of the differences between the most used coding languages. See which seems best for you.
Common programming concepts
Each programming language accomplishes things in its own way. However, there are still core concepts that most share:
Remember variables from math class? This is basically the same thing. They store information so that programs can use it later.
Data types
Data types classify the elements that a program is handling. These can include:
  • Strings
    Groups of characters (i.e., words and phrases)
  • Integers
    Whole numbers
  • Floating point numbers
    Numbers with decimal points
  • Boolean
    One of two values: true or false
Control structures
These tell the computer how a program should go from one step to the next. This can include:
  • Sequential flow
    Module A → Module B → Module C
  • Conditional flow
    If condition A → Module A
    If condition B → Module B
  • Iterative flow
    While condition A is true → Repeat module A
This is a general term that includes the above-listed concepts. It is the rules for how to write the language. Similar to spoken languages, programming languages have conventions for where elements should be placed. You don’t say “Dog ball chased the the,” and you don’t randomly write control structures and variables into your code.
Python vs. JavaScript
A taste of syntax differences:
In Python, variables should be lowercase, with each word separated by an underscore (i.e., variable_name). In JavaScript, variables should start with a lowercase letter, and new words should not be separated. Instead, their first letters should be capitalized (i.e., variableName). In addition, JavaScript has a control structure known as switch that Python doesn’t have. Finally, JavaScript has seven data types — three more than Python.
  • Python vs. JavaScript: which is better for jobs?According to the survey referenced above, Python jobs earn more — $71,105 to JavaScript’s $65,580. However, JavaScript is the most commonly used language, meaning there are more jobs using it and it is thus more in-demand, so there’s a tradeoff.
  • What is each language good at?JavaScript is the language of the internet. It is used for web development, servers, and even interactive features. Python is great for scientific applications. It is used in data science and data analysis. In fact, it is even the language of choice for machine learning and artificial intelligence.
  • Is Python or JavaScript easier to learn?Python is easier to learn. It is often taught as an introductory programming language because it is quite readable. That means that as you look through the code, it is easy to grasp what each element is doing. In addition, Python’s syntax is more forgiving.

    But ultimately, is JavaScript hard to learn? Not as hard as other languages. Python is simply known for being friendly to beginners.
JavaScript vs. C++
A taste of syntax differences:
JavaScript is more flexible. For example, variables can change type at runtime. That means JavaScript code is less strict about whether a variable is a string or an integer. That is as opposed to C++, in which variables are declared with a specific type. In addition, both have similar control structures, but in conditional statements and the switch statement, JavaScript is more forgiving. The most important difference in the syntax is that JavaScript is high-level and C++ is mid-level. That means JavaScript is more akin to natural human language.
  • JavaScript vs. C++: which is better for jobs?As mentioned above, JavaScript is the most popular language. That means there are more opportunities available that involve using JavaScript. However, C++ jobs are more lucrative. In the study, the median C++ salary was $68,000 and the median JavaScript salary was $65,580.
  • What is each language good at?JavaScript and C++ are remarkably different. JavaScript is used for web programming, server programming, and developing websites. C++ is a prime choice for game development. It is also used in system programming, which focuses on building the software that glues a whole system together. In addition, C++ is used for programming embedded systems — i.e., writing code for small chips in consumer devices.
  • Is JavaScript or C++ easier to learn?JavaScript is easier to learn. As mentioned above, it’s a flexible, high-level language. That means it’s easier for a human to understand and use. In addition, there are additional concepts C++ programmers need to master. These include static type systems and garbage collection. Read more.
Python vs. R
A taste of syntax differences:
Variables in Python are assigned using the = sign. For example: “x = 42”. R has this same capability, but variables can also be assigned using “<-”. For example: “x<-42”. For control structures, as mentioned above, Python does not have switch. R does. As for data types, Python represents strings with str whereas R uses character. The two languages also have similar data structures. However, for indexing, Python uses lists whereas R uses vectors. In addition, the first item in a list in Python is labeled as the 0 entry, whereas the first item in a vector is the 1 entry in R.
  • Python vs. R: which is better for jobs?We once again turn to the survey mentioned above. Python jobs earn a median of $71,105, whereas the median R job salary is $67,734. However, as opposed to the languages compared above, the relatively lower salary doesn’t come with an increase in popularity. R was used by 3.56% of survey respondents, and Python was used by 43.51%. However, R is mainly used in data science whereas Python has wider applications. This likely informs the statistic.
  • What is each language good at?
    Data. Both languages absolutely excel when handling data. However, there are nuances. Python is a powerful general data science tool whereas R shines in statistical analysis.

    But there’s one big thing to talk about: machine learning, R vs. Python. One key advantage R has here is its speed. Easy-to-read languages such as Python can take longer to do calculations. Nonetheless, for machine learning, Python is usually the right choice. It has lower barriers to entry for beginners, is more flexible than R, and has robust support for AI applications.
  • Is Python or R easier to learn?Python is easier to learn than R, but there’s a caveat. The learning curves for the two languages are different. R is fairly straightforward when you’re just starting out because the basics are easy to master. However, many people exploring R encounter a spike in complexity. For Python, the process of gaining expertise is much smoother and more linear.
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Is programming hard?
If you haven’t started learning to code, this is a legitimate concern. Is coding hard? If so, why is coding so hard?
Here’s the thing: Coding is a skill, and like any other skill, you can work on it. It can be a breeze if you study and practice. So how hard is coding? As hard or as easy as speaking a second language. It’s just about developing the know-how.
However, not all languages are similarly easy to master. Some are more like spoken languages, which makes them easier to understand.
Easiest languages to learn and hardest languages to learn
If you’re looking for the easiest programming language to learn, here’s a chart. Because trying to list all languages would be an information overload, only 20 are included. These are the top 10 most popular languages as well as the top 10 most well-paid languages. The data for this were extracted from the survey mentioned previously.
Here they are from easiest to hardest:
These are markup and styling languages, respectively. They are easier to grasp as they focus on structuring web content and styling web pages.
2. SQL
As mentioned, SQL is a specialized language for databases. While it has a narrow scope compared to general-purpose languages, SQL requires developers to understand specific concepts and querying techniques. Is SQL hard to learn? Not as hard as you might think.
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3. Python
As noted, Python is widely regarded as one of the most beginner-friendly languages. It has a clean and readable syntax, extensive documentation, a large supportive community, and a wide range of libraries.
4. JavaScriptJavaScript is a versatile language used for web development. It has forgiving syntax and extensive resources, but it can be challenging in certain areas due to its quirks and complexities.
5. Ruby
Ruby is known for its elegant and beginner-friendly syntax. It prioritizes developer happiness and has a strong focus on simplicity and readability.
6. TypeScript
TypeScript adds optional type checking to JavaScript. It is slightly more challenging than JavaScript due to the additional layer of static typing.
7. Bash/Shell
Bash and Shell are scripting languages used for automating tasks in the command-line interface. People generally believe that it is easier to learn Bash and Shell because they focus on scripting and executing commands.
8. PHP
PHP is a server-side scripting language used for web development. It has a large user base, extensive documentation, and numerous online resources, but it can be a little more challenging due to its inconsistent design and historical quirks.
9. Perl
Perl is a flexible and powerful scripting language. It has a diverse set of features and expressive syntax, but it can be a little difficult for beginners due to its idiosyncrasies and less structured design.
10. Java
Java is a widely used general-purpose language with a large ecosystem. It has verbose syntax and requires developers to understand concepts like object-oriented programming, but it has extensive documentation and learning resources. Read more.
11. C#
C# is a statically-typed language used for developing Windows applications and web services on the .NET framework. It is similar to Java and has a moderately steep learning curve. Read more.
12. C++
C++ is a powerful and complex language with a steeper learning curve. As discussed above, it provides low-level control and is commonly used for system programming, game development, and performance-critical applications.
13. Scala
Scala is a statically-typed language. It combines object-oriented and functional programming concepts, which can make it more challenging to learn.
14. Clojure
Clojure is a modern Lisp dialect with a focus on functional programming. It may be more challenging for beginners due to its syntax and concepts like macros.
15. Go
Go is a language designed for simplicity and efficiency. It has a minimalist syntax and focuses on ease of use, but it may require familiarity with concurrent programming concepts. Read more.
16. Lisp
Lisp is a family of programming languages with a unique syntax and a strong emphasis on functional programming. It may be challenging for beginners due to its unconventional syntax and concepts like macros.
17. Erlang
Erlang is a concurrent and fault-tolerant language primarily used for building scalable and distributed systems. Its unique features and functional programming style may make it more challenging for beginners.
18. Rust
Rust is a systems programming language that is great for safety, concurrency, and performance. While it provides unique features and guarantees memory security, it requires a deep understanding of more obscure concepts.
19. Elixir
Elixir is a functional language. It focuses on concurrency and fault tolerance, which can make it more challenging for beginners.
20. F#
F# is a multi-paradigm language that combines functional and object-oriented programming. Its strong typing and functional concepts require users to already have experience programming.
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Can you teach yourself to code?
This is a question many people ask when wondering how to become a coder. The answer: Teaching yourself to code is indeed possible. In fact, many people learn Ruby, learn MongoDB, or learn Kotlin on their own. However, opening a textbook on a language isn’t going to make you a professional programmer. Here are some accessible ways to develop your programming skills.
Best apps to learn coding
If you choose to go for solo learning, programming apps can help you on your journey. Here are five of the best coding apps:
1. Grasshopper
This is a go-to coding tutorial app for good reason. It was developed by Google to gamify learning JavaScript. It has interactive coding challenges and puzzles that help beginners intuitively grasp fundamental programming concepts.
2. Enki
Enki customizes coding lessons to your goals and interests. It covers a wide range of programming languages and technologies and provides daily challenges and quizzes.
3. SoloLearn
This app offers courses on Python, JavaScript, Java, C++, and more. In fact, it can teach you several technologies and languages. It has interactive lessons, quizzes, and a robust community of learners.
4. Mimo
This app has bite-sized coding lessons that focus on mobile app development, web development, and data science. It provides a hands-on approach with its practical exercises and projects.
5. Encode
This app is all about web development. It has step-by-step lessons on HTML, CSS, and JavaScript. While not as comprehensive as the other apps on this list, it is nonetheless a powerful tool that can help beginners learn key tech skills.
Free resources to learn to code
Apps aren’t the only way you can teach yourself to code. There are also tons of free resources that can help you start your programming journey. Here are our top five:
1. Mozilla Developer Network (MDN)
MDN has extensive documentation and in-depth tutorials on HTML, CSS, and JavaScript. If you’re focusing on learning web development, this is a great resource.
2. W3Schools
Even in college courses, W3Schools is recommended as a place to find supplemental practice. It provides tutorials, references, and examples for HTML, CSS, JavaScript, and other web-related topics. It’s simple, interactive, and effective.
3. GitHubThis is for people who learn by doing. GitHub is a platform that programmers use to collaborate on projects and host code repositories. It’s where you can find a vast collection of open-source projects to explore, learn from, and start tinkering with. It also has numerous coding tutorials that were crafted by developers for developers.
4. YouTubeThis may come as no surprise, but YouTube has a wealth of great free content. The site hosts an extensive collection of coding tutorials as well as channels dedicated to teaching programming languages, frameworks, and various other coding concepts. Channels like Traversy Media and The Coding Train offer valuable coding instruction for beginners.
5. Your local library
You can find books on all sorts of coding languages and related technical topics. From HTML to Clojure and everything in between, it’s likely your local library has a book that can help you get started. In addition, if you can’t make it to a branch, many libraries also offer ebooks.
What about coding bootcamps?
This is a good question. While there are many free ways to learn to code, they fall short in certain key aspects. If you’re looking to land coding jobs without a college degree, you should consider joining a coding bootcamp.
Benefits of coding bootcamps
Bootcamps are purpose-built programs that help people land jobs in tech. Some focus on single languages. Some provide a broader introduction to tech. Others split the difference to make sure their grads have robust but diverse programming skills. In any case, by joining a bootcamp, you’ll gain unique benefits:
1. Interaction with peers and experts
In most bootcamps, you will be placed among a cohort of fellow learners. That means you’ll have peers to bounce ideas off of. If you need clarification on something, or if you just want to have a chat about the latest lesson, you’ll have a community at your fingertips. In addition, you’ll be given access to tutors who will be able to address your specific questions. So, instead of looking for another YouTube video or posting a question on a forum, you can get quick, relevant answers. This will help make sure you keep progressing in your studies.
2. Up-to-date instruction
Free resources are great, but because tech develops so rapidly, the information taught can quickly become outdated. Videos, written tutorials, and documentation have to be constantly updated to stay relevant.

The people behind bootcamps make sure their information is up to date. Programs are reviewed for relevance and efficacy, meaning you don’t need to worry that you’re learning something from half a decade ago. In fact, the tutors are often professional coders themselves. This means they are in-the-know about the things that up-and-coming programmers should learn.
3. Code reviews and feedbackWhen you teach yourself programming, you have no one to check your code. A core tenet of bootcamps is that experts go through your code and show you where you can improve.

This is a valuable tool for budding developers. The comments from seasoned tech professionals will give you an immediate understanding of your progress. They can help you uncover places where you need improvement and highlight where your skills are strongest.
4. Career coachingBootcamps often do more than just teach you the basic skills. Some offer extensive career coaching services. This can include mock interviews, assistance with portfolio preparation, and advice on how to write a compelling resume.

After all, landing a job in tech is about more than how well you can code. It’s also about knowing how to present yourself. Many bootcamps employ experts from the industry who can give you inside information on what employers look for. That means you’ll graduate with more than just technical know-how.
5. Job placement
Not all bootcamps provide job placement, but those that do can give you a leg up. This is a powerful way to get your first job in tech.

Some bootcamps have externships in which students take on projects for tech companies. That means that grads leave the program with real-life experience already under their belt. This gives learners hands-on experience in working in tech day-to-day.
People who have taken part in externships stand out to recruiters because of this. Not only do they have the resume, skills, and portfolio. They also have on-the-job expertise.
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Our pitch to you
So, is coding hard? Not after studying with us. If you want to gain skills in the most in-demand programming languages to land an entry-level coding job, TripleTen can help.
Looking for the easiest programming language to learn? We can teach it. Want to master the highest-paying programming languages? We can teach them, too. Whether you’re interested in web programming languages, front-end languages, or just the best programming languages in general, TripleTen has you covered.
Check us out here, and if you want to see what path is right for you, take our career quiz.
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