{"id":22884,"date":"2023-01-12T08:43:50","date_gmt":"2023-01-12T16:43:50","guid":{"rendered":"https:\/\/www.springboard.com\/blog\/?p=22884"},"modified":"2024-02-08T08:41:39","modified_gmt":"2024-02-08T16:41:39","slug":"data-science-coding","status":"publish","type":"post","link":"https:\/\/www.springboard.com\/blog\/data-science\/data-science-coding\/","title":{"rendered":"Does Data Science Require Coding?"},"content":{"rendered":"\n

One of the counterintuitive things about the tech industry is that you don\u2019t necessarily need to know how to code in order to land a high-paying job. No sector exemplifies this quite like data science. In fact, some data scientists do their jobs with little to no coding. <\/p>\n\n\n\n

But the number of data scientists that do code far outweighs those who don\u2019t, R and Python being two of the most commonly used languages. So if you\u2019re looking to jumpstart your career in data science, then you may be wondering\u2014do I need to know how to code?<\/p>\n\n\n\n

To answer that question, we\u2019ve compiled this guide. Below, we\u2019ll tell you all about no-code data science roles, and the benefits of learning how to code if you\u2019re a data scientist. <\/p>\n\n\n\n

Does Data Science Require Coding?<\/h2>\n\n\n\n

Traditionally, data science roles do require coding skills<\/a>, and most experienced data scientists working today still code. However, the data science<\/a> landscape continues to change, and technologies now exist that allow people to complete entire data projects without typing code. <\/p>\n\n\n\n

Arguably, the purpose of these technologies is not to remove coding from a data scientist\u2019s skill set, but to make basic data analysis accessible for others in less technical roles. When these technologies are used as intended, data scientists continue to use code for more complex and bespoke solutions.<\/p>\n\n\n\n

Popular Data Science Programming Languages<\/h2>\n\n\n\n
\"Popular<\/figure>\n\n\n\n

There are a number of popular programming languages in the data science community for different purposes.<\/p>\n\n\n\n

Python<\/h3>\n\n\n\n

Python<\/a> is the most widely used programming language in data science. It\u2019s used to engineer data, perform machine learning algorithms, and even create data visualizations. Python has a vast amount of data science libraries, like Pandas for manipulating databases, or Matplotlib for generating data visualizations.<\/p>\n\n\n\n

R<\/h3>\n\n\n\n

Unlike Python, which is also used in many areas other than data science, the R programming language<\/a> was created specifically for data science purposes. It\u2019s commonly used for machine learning and statistical analysis, plus data manipulation and visualization. <\/p>\n\n\n\n

SQL<\/h3>\n\n\n\n

Structured Query Language (SQL)<\/a> is a domain-specific language for interacting with databases. Most who learn SQL start with Python or R first. SQL has a very simple syntax and is considered easy to learn compared to other languages.  <\/p>\n\n\n\n

JavaScript<\/h3>\n\n\n\n

Javascript<\/a> is a very popular scripting language and very easy to learn. It\u2019s not traditionally a data science language, but some in the community have started using it in recent years. It doesn\u2019t yet have the robust set of data science libraries that Python and R do, but many believe it has potential. <\/p>\n\n\n\n

Related Read: 12 Best JavaScript Courses To Boost Your Skills<\/a><\/em><\/p>\n\n\n\n

Learning Coding for Data Science<\/h2>\n\n\n\n

There are lots of ways to learn coding for data science, with free, independent options<\/a> and paid classes. <\/p>\n\n\n\n

What Programming Language Should I Learn First?<\/h3>\n\n\n\n

It\u2019s most common to choose between either Python or R as your first data science programming language<\/a>. If you come from a certain background with other software engineering<\/a> experience, you may find one more intuitive than the other. But for most beginners, there isn\u2019t much reason to choose one or the other.<\/p>\n\n\n\n

Many people would argue that making the choice and getting started is the important part, and which language you go for doesn\u2019t matter. That said, Python is currently more popular, so if you want to use the most popular language, choose Python. <\/p>\n\n\n\n

Where Can You Learn Coding for Data Science?<\/h3>\n\n\n\n

Learning to code can involve attending a school, completing a course, or creating your own self-study curriculum. <\/p>\n\n\n\n

Dedicated Coding Education Websites<\/h4>\n\n\n\n

Starting your coding education can be as easy as clicking on a website and starting “Lesson 1.”<\/p>\n\n\n\n

W3Schools<\/h5>\n\n\n\n
\"does
Source: W3Schools<\/a><\/figcaption><\/figure>\n\n\n\n

W3Schools is a completely free coding website with courses on every programming language you can think of, plus a selection of popular libraries. You can learn R, Python, SQL, and Java all on their site.<\/p>\n\n\n\n

Codecademy<\/h5>\n\n\n\n
\"does
Source: Codecademy<\/a><\/figcaption><\/figure>\n\n\n\n

Codecademy is also free and includes courses on Python, R, SQL, and Javascript. It also has special sections focusing on data science and machine learning. <\/p>\n\n\n\n

Bootcamps<\/h4>\n\n\n\n

The best data science bootcamps<\/a> are intensive courses taken either online or onsite that often aim to take beginner-level learners and produce job-ready graduates. With online communities, mentor programs, and hands-on projects, you can enroll in Springboard\u2019s Data Science Bootcamp<\/a> and graduate in just six months.\u00a0\u00a0<\/p>\n\n\n\n

Online Courses<\/h4>\n\n\n\n

Online courses<\/a> are typically an independent type of study, consisting of structured resources and quizzes to help you progress through a topic. You can find hundreds of programming courses for all purposes and levels on sites like Coursera, and some courses will provide a data science certification upon completion. <\/p>\n\n\n\n

Online Communities<\/h4>\n\n\n\n

Online communities such as Reddit, Discord, Slack, and independent forums are all great tools to complement your learning journey. <\/p>\n\n\n\n

Kaggle<\/h5>\n\n\n\n
\"does
Source: Kaggle<\/a><\/figcaption><\/figure>\n\n\n\n

Kaggle is a large online community where data scientists and machine learning practitioners share data sets and projects, work together, and compete against each other. <\/p>\n\n\n\n

Coding Challenges and Hackathons<\/h4>\n\n\n\n

While you\u2019re studying, coding challenges and hackathons can give you a chance to put your skills to the test and socialize with other programmers as you do. The Advent of Code is a popular yearly coding challenge suitable for both senior and junior programmers.<\/p>\n\n\n\n

Tips for Non-Programmers Learning Data Science<\/h2>\n\n\n\n
\"Tips<\/figure>\n\n\n\n

If programming isn\u2019t something you\u2019re interested in pursuing, but you really want to work in data science, then we recommend developing some of the following skills. <\/p>\n\n\n\n

Learn to Use GUI-based Tools<\/h3>\n\n\n\n

Graphical User Interface (GUI) tools employ pre-written programs so that you don’t have to write code. They are the primary tools used by non-programmer data scientists, and give you the ability to prototype, test, and deploy advanced analytics and statistical models. <\/p>\n\n\n\n

Two popular low-code tools are KNIME and RapidMiner. They are also different types of visualization software like Google Charts and Tableau. <\/p>\n\n\n\n

Become a Great Storyteller<\/h3>\n\n\n\n

As a data scientist, it\u2019s your job to do the work to understand what our data is telling us, for the purpose of communicating it to others. This means you need to combine storytelling, presentation, and persuasion skills to explain your uncovered insights and convince business decision-makers to act on them. You don’t need to know how to code to do that. <\/p>\n\n\n\n

Build Your Credibility With Business Acumen<\/h3>\n\n\n\n

Finding the right insights to share requires in-depth knowledge of the company and industry you\u2019re working in. This means knowing the goals and principles of the company and understanding the stakeholders\u2019 motivations. <\/p>\n\n\n\n

Get a Foundational Knowledge in Programming<\/h3>\n\n\n\n

Even with the no-code tools available, most well-paid data scientists make use of their programming skills. While you can enter the data science industry without knowing how to code, you should consider picking it up as a skillset along the way to advance your career. <\/p>\n\n\n\n

What Data Science Jobs Require Coding?<\/h2>\n\n\n\n
\"What<\/figure>\n\n\n\n

Data scientists make use of deep learning algorithms and AI-fueled programs to find patterns and make predictions using data. But it’s often the case that data scientists have to build these sorts of algorithms and programs themselves, which definitely requires coding. <\/p>\n\n\n\n

These data scientists usually have software engineering experience and enjoy many career options, as businesses are constantly looking for even more efficient and accurate statistical models. <\/p>\n\n\n\n

Some role titles that fit into this category could include:<\/p>\n\n\n\n