Coding vs. Data Science: What’s the Difference?

Coding and data science are two distinct areas that are constantly conflated. Because they both include training in programming languages, there are many similarities between the two. Despite these commonalities, there are plenty of key differences between coding and data science as well. 

This article compares coding and data science by outlining the key differences between the two, including the careers and skills of coding vs. data science. 

The Difference between Coding and Data Science

The differences between coding and data science relate to their scope and specificity. Coding is a general term for computer programming that covers an enormous range of careers and skills. Coding is a verb used to describe the process of writing computer programs or giving instructions to a machine or robot. In contrast, data science is a field that focuses on the storage, organization, analysis, visualization, and sharing of information and data. Data science is commonly associated with data analytics, which includes coding as one method of analyzing data. In this sense, coding and data science are related to each other but accomplish unique tasks. 

For example, a computer programmer can use their coding skills to take on a data science project or find a data scientist job. However, there are many ways to use and create code that is not considered data science. Similarly, while many data scientists know how to code, computer programming is not a requirement of data science. Many data scientists rely more on mathematics and other statistical skills to analyze data than on writing programs using a coding language. But, because so many students combine coding and data science in their work, it has become more common to use the two in conjunction.

Introduction to Coding: Skills and Careers

As a shorthand for computer programming, many skills fall under coding. There are numerous coding languages that one can learn, and each one is geared towards a specific programming skill or type of product development. For example, while a web developer should learn how to code in Javascript, a database architect might learn how to code using SQL. There is no specific coding language that a programmer needs to know. Instead, you should build your skills in whatever coding language is required for the type of work that you want to do.

Popular Programming Languages and Skills

There are numerous programming languages that coders can learn. The following list includes some of the most popular programming languages and skills for programmers.

• Python is one of the most popular programming languages amongst data scientists and developers, making learning how to code with Python an incredibly versatile skill. 
• SQL is the primary programming language for communicating with and managing relational databases. SQL is a required skill of database administrators and architects.
• Java is the go-to programming language for object-oriented programming and is a necessary skill for coders interested in mobile application development. 
• Javascript is a programming language commonly used with HTML and CSS to script a web page's appearance. It is an ordinary skill amongst web designers and UX/UI developers.

Jobs in Coding and Computer Programming

Coding is a popular skill due to the rising demand for a technologically skilled workforce. By taking part in coding bootcamps or pursuing certifications or degrees, any student or professional can learn how to code and find a job to apply their skills. The following list includes jobs that require learning how to code.

• Computer Programmer is the most general career for anyone learning how to code. As a general title, computer programmers can specialize in one or multiple programming languages, as they use their coding skills to test and develop programs and code.
• Web Developers apply their coding skills to the development of websites. Most web developers specialize in multiple programming languages that apply to the design and aesthetics of a platform, such as Java, Javascript, and HTML.
• Software Engineers use multiple programming languages to create digital tools and technologies. These engineers can work in many roles due to the versatility of their skills.
• Full Stack Developers are similar to software engineers. Their work combines front end and back end development to create products and services for websites, mobile applications, and digital platforms. Developers also need to know multiple programming languages and coding skills. 
• Database Administrators use their knowledge of programming languages like SQL to manage the accessibility of a database, making this a popular job in offices, educational institutions, and technology companies.

Introduction to Data Science: Skills and Careers 

As a field and an industry, data science also includes several skills, as well as coding languages, in addition to unique careers and job opportunities. One essential skill to have is understanding the data science lifecycle and the process of turning data into information or making meaning of raw data. This cycle begins with collecting data, sharing it, and making it accessible to key stakeholders. Each stage of the data science lifecycle includes a specific set of skills and tools.

Data Science Lifecycle and Skills

Building on the data science lifecycle, the following list includes each stage of the cycle and the corresponding required skills:

• Data Collection requires skills in finding and storing data from various sources. Some common data collection skills include web-scraping and using spreadsheet software.
• Data Cleaning and Organization require skills in automation, machine learning, and artificial intelligence platforms that clean large datasets. For some data science professionals, data cleaning and organization can also include working with advanced functions in Microsoft Excel. 
• Data Analysis requires skills in coding using programming languages like Python and R or statistical analysis software.
• Data Visualization requires skills in data analytics technology like business intelligence tools and platforms.
• Data Storage and Sharing require skills in database management systems, virtual machines, cybersecurity, data governance, collaborative tools, and cloud systems. 

Jobs in Data Science 

The most popular career within data science is the role of a data scientist or analyst—however, multiple careers within and outside the industry focus on using data science skills. The following list includes some potential data science jobs and careers: 

• Data Engineers make data more accessible to a team by building the data architecture of database management systems. Data engineers are highly skilled in data collection, storage, and sharing. 
• Business Analysts are skilled in using business intelligence platforms and data science tools to predict a company or brand's present and future wellness. Business analysts focus on data analysis, visualization, and sharing.
• Machine Learning Engineers capitalize on the popularity of automation and machine learning by using their data organization and analysis skills to craft algorithmic models and artificial intelligence.
• Financial Analysts are similar to business analysts in that they use predictive analytics to make financial decisions. Financial analysts use their data analytics and visualization skills in baking and financial institutions, investing, and algorithmic trading.
• Cybersecurity Specialists protect the information and data of computer and technology users by defending networks against cyber-attacks. Additionally, cybersecurity specialists analyze computer systems to strategize how to make the system less vulnerable and more secure.  

Want to find a Coding Bootcamp for Data Science?

While coding is a broad skill set, data science is an ever-growing field. Many of Noble Desktop’s coding bootcamps are geared toward students that want to build a career in data science. For example, their Data Science Certificate program includes a series of bootcamps designed for aspiring data scientists and analysts. Prospective students can also check out the lists of in-person coding bootcamps and live online coding bootcamps to find more certificate programs and coding bootcamps for data science.