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What is a data science degree?

Think a degree in data science might be for you? You're in luck. Job opportunities in this area are expected to grow by 19 percent in the next decade—much faster than other sectors.

Why? In today's technologically connected world, data is everywhere. New tracking methods and systems are emerging every day. As a result, businesses are swimming in information—far more of it than any single person can make sense of.

That's where data science comes in. This ever-changing field concerns itself with gathering, organizing, analyzing, and understanding data. It combines aspects of statistics, computer science, and machine learning to identify patterns and trends, make predictions, and solve complex problems. It's a powerful field that plays a role in almost every industry, in almost every country.

With so many applications, it's not surprising that data science has a sunny career outlook. It's also a well-paid profession, with a median salary of more than $90,000 US. Pursuing a degree in data science may be one of the best things you could do for your career.

If you think data science might be the degree for you, read on. In this article, we'll look at:

  • What kinds of data science degrees are there?
  • What sets data science apart from related degrees, like computer science and statistics?
  • What skills do you learn in a data science degree?
  • What can you do with a data science degree?

Program options

Data science is constantly evolving, which means there are a wide range of educational paths to choose from—each with its own benefits and challenges. Here, we'll go through some of the most common ones.

Bachelor’s Degree in Data Science
Bachelor's programs in data science tend to take about four years to complete and are offered at larger colleges and universities. Students in this degree gain foundational skills, like computer coding and programming, and take courses in math, computer science, statistics, and more.

Currently, there are relatively few of these programs available, as most students study data science at the graduate level. But this is expected to change as demand grows.

Master’s Degree in Data Science
These advanced degree programs can be completed after a Bachelor's Degree in Data Science or a related subject. They usually involve another two years of full-time study. Master's programs cover similar topics and skills as bachelor's programs do, but in greater depth. They also open up more advanced career opportunities.

Data Science Certification Programs
For experienced data scientists who want to improve their options for career advancement, there's data science certification programs. These degrees can take as little as one year to complete, making them much less time consuming (and expensive) than master's programs. They tend to focus on building specific skills and techniques, like large-scale data extraction or data-based decision-making.

PhD in Data Science
A Doctorate in Data Science isn't a requirement for most data science careers. But if your goal is to become a university professor, an industry executive, or a leading scientist at a research institution, a PhD is your best bet. These highly specialized programs take at least three years to complete, after a master's. They combine coursework, research, and a dissertation.

Data Science Bootcamps
If you're trying to transition to data science from another career, consider a bootcamp. These fast-paced, intensive training programs offer training in practical data science skills and techniques. They are offered by private institutions, either in-person or online. Data science bootcamps often take as little as two weeks to complete.

DIY Degrees
Not ready to pursue a formal degree? Why not teach yourself!

From MOOCs to free coding academies, there are lots of ways to learn data science without ever setting foot inside a classroom. But whatever you do, remember that this is a very practical field. In other words, don't just read about programming, try it yourself. Getting hands-on experience working with data is one of the best ways to get into the field.

Start by teaching yourself some basic statistics, machine learning, and programming skills. Then dive into more advanced topics, like databases, workflows, and data visualization.

Degrees similar to data science

Data science degrees cover similar topics as many other degrees, but especially computer science and statistics. In fact, some people define data science as the merger of these two fields. As a prospective student, it can be hard to know the difference.

Let's take a look at what makes data science unique:

Statistics
Both data science and statistics are powerful ways of making sense of data; both allow you to identify trends, draw conclusions, and make predictions.

However, statistics is an older field that is primarily used to test hypotheses. It relies on established theories that have changed very little over the last century. Data science, on the other hand, has evolved as technology evolved. It applies some statistical methods, but to different kinds of data and, often, with different goals. Data science is primarily concerned with code-based data manipulation, digital visualization, and information from large databases.

Computer Science
Computer science degrees teach students the ins and outs of how computers work. It's a wide-ranging field of study that covers everything from programming to operating systems, software to algorithms. This degree tends to focus solely on how these topics apply to computers.

Data science, on the other hand, is much more interdisciplinary. Although the degrees can cover similar topics and techniques as a computer science degree, it also incorporates aspects of mathematics, machine learning, data visualization, deep learning, and databases.

Skills you'll learn

Whatever educational path you choose, studying data science will help you develop essential skills, including:

Technical
One of the most valuable aspects of a data science degree are the hands-on data skills you learn. The best degree programs will help you master Python, R, SQL database/coding, machine learning, data visualization, and more.

Business
Becoming an effective data scientist requires considering how the problems you're solving might impact a business's success. A good degree in data science will help you understand how businesses operate and what challenges they face.

Communication
You might find numbers and figures fascinating, but not everyone does. A data science degree will teach you how to tell stories with data—to share your findings in ways that anyone can understand.

Team Work
Working in data science is not a solitary pursuit—and neither is studying it. In your degree, you'll complete collaborative projects with large and small groups. This valuable training is ideal preparation for a future in any office job.

Eagerness to learn
Data science is constantly changing, so keeping abreast with the field requires a real thirst for knowledge. While there may be no official course in curiosity, you'll have a hard time getting through a data science degree without this quality.

What can you do with a data science degree?

Data science graduates are sought-after across a range of industries. Here are just a few directions a data science degree might take you:

Healthcare + Health Informatics
Data is playing an increasingly important role in the healthcare system. With a data science degree, you can help physicians and medical administrators track drug trials, predict the spread of disease, map the human genome, and more.

Finance + Business
Companies are using data in new and creative ways to help businesses grow and thrive. Careers in this area are diverse and evolving. You might find yourself using your data skills to track inventory, analyze in-store traffic, make financial predictions, or something else entirely.

Social Networking
Instagram, Facebook, Twitter—all of these platforms are data goldmines. In a social media-related career, data science students can use their skills to help companies better understand and serve their customers. Careers in this area apply data science techniques to develop location-based targeted advertising campaigns, tailor customer service by personal preferences, and more.

Sales + E-commerce
Data science skills are extremely valuable within the e-commerce sector. Professionals in this industry can apply their knowledge to help interpret web traffic data, predict customer preferences, develop targeted sales campaigns, improve products, and more.

Science
From climatology to biochemistry, almost every scientific field now relies on large data sets and analysis to some degree. Data science graduates with a love of research will thrive in this mentally stimulating and ever-changing career path.

Energy
As the demand for clean energy grows, so do the job opportunities in this area. Trained data scientists can make some valuable contributions to the energy section. By applying their knowledge and skills, they can help companies increase energy efficiency, cut costs, avoid power outages, and more.

Manufacturing
This industry currently employs almost 20 percent of all data scientists. Why? Product manufacturing is all about minimizing costs and maximizing productivity. Data science graduates can help companies achieve these goals by applying data techniques to inventory yield, quality control, supply chain analysis, and more.

Technology
The IT industry is always looking for experienced professionals with strong coding skills and statistical knowledge. In this industry, data science graduates can pursue a wide range of positions. Typical tasks include collecting data, processing and verifying it, and presenting the results to management to inform business decision-making. Fast-paced and mentally stimulating, this sector is the top employer of all data science graduates.

Data Science Careers

The career trajectory of people with a Data Science degree appears to be focused around a few careers.

Career % of graduates % of population Multiple
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Data Science Salary

Data Science graduates earn on average $k, putting them in the bottom percentile of earners with a degree.

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Data Science Underemployment

Data Science graduates are highly employed compared to other graduates. We have collected data on three types of underemployment. Part-time refers to work that is less than 30 hours per week. Non-college refers to work that does not require a college degree. Low-paying includes a list of low-wage service jobs such as janitorial work, serving, or dishwashing.

Employment Type Proportion of graduates
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