Bachelor’s Degree

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Bachelor’s Degree in Data Science

A bachelor’s degree is often the minimum level of education required to get a job in the data science field. A ‘data science’ bachelor’s degree program is rare, but numerous degrees fall under the data science label. If you’re interested in a data science career, consider obtaining a bachelor’s degree in a related field.

But is a data science degree worth it? In most cases, yes, a data science bachelor’s degree is worth it if you’re looking for a high-paying and future-proof career. Here, we’ll cover the most common data science degree options, along with admissions information and everything you need to know before applying.

A bachelor’s degree in data science is often the base-level requirement for jobs in the field. Bachelor’s degrees take four years to complete at an accredited university. Roughly one-third of Americans have a bachelor’s degree, and it still provides somewhat of a competitive edge in the workforce.

Students have several options when it comes to earning a bachelor’s degree. The most economical option is to spend two years in a community college then transfer to a university for the remaining two years of the program. Others attend university right after high school or enroll at a later date. However, it’s never too late to earn a degree or switch careers.

Here on Study Data Science, we’ll cover the key points and get you up to speed on data science degrees. You’ll also find top career paths, tuition costs, and alternative data science education pathways.

Here are some essential facts about bachelor’s degrees and college education in general.

According to the U.S. Census, about 33% of Americans currently have a bachelor’s degree.

The average cost of a bachelor’s degree is $23,091 per year.

Students can transfer from a 2-year community college to a 4-year university to save money.

College admission requires a GED or a High School Diploma. Standardized test scores are also required.

Regionally-accredited universities are the best choice for most data science students.

What is a Bachelor’s (BS) Degree in Data Science?

A Bachelor of Science (BS) in Data Science is a four-year college degree available through accredited public and private universities. It’s important to distinguish universities from colleges and community colleges, as ‘college’ is the blanket term for all, but they are not the same. 

A bachelor’s degree is the entry-level university program. Many data science jobs list a bachelor’s degree as a minimum requirement, though industry trends indicate a gradual easing of this qualification in the tech industry. 

A degree in data science can mean several things. ‘Data science’ is an umbrella term that applies to multiple degrees. Data science professionals come from backgrounds including business analytics, data analytics, statistics, and even software engineering.

BS in Data Science Benefits

The benefits of a college degree are common knowledge in America. According to some metrics, professionals with a bachelor’s degree earn an average of one million dollars more over their lifetimes. 

A bachelor’s degree isn’t the ‘meal ticket’ that it used to be, but many Americans still strongly believe in the utility of a college education. And despite tech industry trends, a bachelor’s degree in a data science field is still highly beneficial during a job search as it demonstrates commitment and capability.

Data science is a lucrative and fast-growing career path. Bachelor’s degree holders hold most entry-level positions in the field and earn a six-figure average salary for their work. And while six-figure incomes aren’t uncommon in the tech industry, data science offers one of the highest-paying jobs for graduates.

  • Data Science Salary: $118,370
  • Data Science Job Growth: 16%
  • Job Openings
  • Jobs Filled

The U.S. Bureau of Labor Statistics predicts a 16% growth in the information sciences field for the period between 2018 and 2028. This means that a high number of jobs will be created during that time, likely continuing to outpace the supply of qualified professionals.

Data science outpaces the 5.2% national average job growth prediction for the same period. And due to continuous supply-and-demand issues for the field, data science workers will likely have the advantage for the foreseeable future.

Certifications are an asset to any data science professional, especially during hiring time. Most certifications cost between $200 and $1,000. Data science is a highly specialized field, which is why professionals with multiple certifications have an advantage. Here are the most popular programs used by data scientists to increase their professional skills:

Data analytics is a popular data science career specialization. These professionals benefit from certifications like the CAP (Certified Analytics Professional). The CAP organization course costs $695.

Cloudera offers a 120-minute certification test for SQL development and data analytics. The test covers analytics, Cloudera software, and programming. The exam costs $295, and a passing grade earns a certificate that is valid for two years.

Amazon offers a $300 big data certification program for professionals with at least two years of experience in the field. The test includes material on big data ecosystems and data science. If passed, students earn a certificate that requires renewal in two years.

Oracle is a cloud computing and data industry Titan. Oracle systems are common across America. As a result, many data professionals take Oracle’s $245 exam. Once completed, the certificate allows data scientists to work with Oracle systems. 

Data Science Bachelor’s Degree Jobs

Data science jobs outnumber qualified professionals, which means it’s an employee’s market. A bachelor’s degree guarantees consideration for many data science positions. Here are the most common job titles for data professionals, along with salaries and general employment statistics.

Data Scientist

Data science is the all-purpose term applied to jobs that require knowledge of databases, data analytics, algorithms, machine learning, and more. Data scientists often earn six-figure salaries.

  • Salary: $118,370
  • Job Growth: 16%
  • Total Employment: 31,700

Data Analyst

Data analysts work with large data sets. They specialize in data interpretation and help businesses make sense of the information they receive. 

  • Salary: $62,453
  • Job Growth: 11%
  • Total Employment: 100,000

Machine Learning Engineer

Machine learning and artificial intelligence are promising industries. Emerging opportunities for data scientists in the field make it an attractive option to work with fascinating new technology.

  • Salary: $114,121
  • Job Growth: 344% (growth in the field 2015-2018)
  • Total Employment: 10,000+

Database Administrator

Database administration is an entry-level data science career. These professionals are responsible for database maintenance, operation, and oversight.

  • Salary: $82,050
  • Job Growth: 5%
  • Total Employment: 383,900
TitleMedian SalaryEntry-Level SalaryMid-Career SalaryLate-Career Salary
Data Scientist$118,370$83,000$113,309$154,000
Data Manager$52,861$37,000$50,000$81,000
Database Administrator$82,050$59,000$78,779$104,000
A.I. Engineer$114,121$78,000$114,000$150,000
Machine Learning Engineer$114,000$80,000$115,000$150,000
Data Analyst $62,453$43,000$70,000$95,000
TitleMedian SalaryLate-Career Salary
Web Developer$68,500$111,000
Software Developer$76,500$107,000
Computer Support Specialist$48,600$70,000
Systems Administration Specialist$64,800$93,000
Data Scientist$113,300$154,000
Information Technology (IT)$84,800$125,000
Network Administrator$63,000$85,000
Help Desk Technician$41,800$58,000
Support Analyst$69,00$95,000

University Accreditation

Independent accrediting agencies certify the legitimacy of college programs, and thus, the validity of the degrees that students graduate with. Accreditation is a complex element that’s easy to overlook when choosing a school. However, it’s essential to make sure you choose the right kind of accreditation. 

National Accreditation

National accreditation, despite the name, is not the most common kind of college accreditation. In fact, national accreditation is somewhat of a niche in the world of higher education. This type of accreditation is common among online colleges and certain degree programs. 

Institutional Accreditation

Institutional accreditation is valid within an institution, such as a university or a series of connected schools (examples include university business and engineering colleges at different locations). Institutional accreditation is common for certain in-house courses.

Specialized Accreditation

Specialized accreditation is for specific programs, such as career training and certification courses. Generally speaking, students seeking a bachelor’s degree in a data science field won’t need to concern themselves with specialized accreditation.

Regional Accreditation

Regional accreditation is the most common choice for university programs. The majority of well-known schools are accredited by one of seven regional entities. The vast majority of undergraduate data science programs are regionally accredited.

Universities are known for complex and tedious admissions processes. Each school sets its own admissions requirements. Some schools within the same college system (such as the University of California, or UC system) set vastly different admissions standards. Furthermore, many colleges accept a common application called the Common App, which further streamlines the process. Here are the most common university admissions requirements for undergraduate students:

High School Diploma

A high school diploma and grade point average (GPA) is almost a universal requirement for college admissions. Universities use your GPA and course history as a metric to gauge your eligibility to attend. Keep in mind that there’s no ‘magic GPA’ to get you into a specific school. 

GED

A GED is the high school diploma equivalent that people use to get into colleges. If you didn’t earn a high school diploma, you can earn a GED instead. GED programs generally cost about $30 per subject. When it comes to hiring, a diploma and GED are usually legally equivalent.

Standardized Testing

Standardized testing is required for college admissions. Tests like the SAT and the ACT are the most common. Over the last few years, students increasingly choose the ACT over the SAT, but each school has different requirements. Many students take both tests. 

Make no mistake about it—bachelor’s degrees cost a lot of money. According to the National Center for Education Statistics, the average cost of a bachelor’s degree program (in 2016 and 2017) was $23,091 per year. Remember, you’ll need between two and four years to complete the program. Thankfully, there are ways to reduce the financial burden of tuition.

Thousands of college scholarships are available, and it’s important for everyone to check if they qualify. A single scholarship (or a combination of scholarships) can save you thousands in tuition costs and student debt. Here are the most common ways to pay for a bachelor’s degree in data science:

Scholarships for Data Science Bachelor Degrees

Scholarships are the best way to cover tuition. Given that the alternative is often student debt, there’s absolutely no reason not to do some research and see if you qualify for any scholarships. There’s no shortage of funding available for students today.

Bachelor in Data Science Financial Aid

Financial aid and tuition discounts are also available at many institutions. In this case, we’re not referring to student loans. Financial incentives are also available to some students who, for example, meet special requirements set by schools.

Student Loans and Financing Rates

Student loans are available to help students cover tuition costs. However, America is experiencing a student loan crisis, and student loan debt isn’t forgivable through bankruptcy. If you need student loans, be sure to apply with caution and get the facts upfront. 

Bachelor’s degrees are the second rung up the higher education ladder. However, they share some curriculum with associate’s degree programs. That’s part of the reason why it’s relatively easy to spend two years in a community college then transfer to a university. Due to the varying degree options in the field, we won’t include an exhaustive list of course subjects. Instead, here are the most common data science-related subjects:

General Education and Humanities

All college students are required to complete some level of general education and humanities, regardless of their major. The only exception is if they complete the required courses before attending university. These courses include English and basic math classes.

Mathematics

Mathematics plays a big role in data science, which is why students often take several high-level math courses. And while you don’t have to be a math genius to succeed in data science, you should work to develop strong general mathematical skills. 

Coding and Programming

Data scientists spend days immersed in programming languages like Python and SQL. So, as you can imagine, any reasonable data science college program will cover coding languages at some point. Depending on your major, you could take a deep-dive into the subject. 

Statistics

Statistics is one of the most important courses for data science students. The level of stats classes and statistical analysis training you receive depends on your specific course of study. If you don’t have any statistics classes, consider adding one or two. 

Specialty Courses

Each degree program has its own set of specialty course options. Software engineering, for example, often includes high-level programming and project-building classes. Students can use these courses to choose a field to specialize in after graduation.

Electives

Elective courses, while sometimes optional, are an enriching part of the college experience and shouldn’t be discounted. Each school offers its own set of elective courses—often including everything from foreign languages to art. 

Data Science course requirements vary widely because, for one, most colleges don’t offer a ‘data science’ degree. Instead, students who become data scientists major in fields such as computer science or software engineering. Nonetheless, these students often take data-related classes to learn the basics. Here are some of the most common classes taken by data scientists:

Computer Programming

Students in most technology programs wind up in a programming course or two. For data science, SQL and Python are the most important languages to learn in college.

Analytics

Data analytics is a huge part of data science. Students often take intermediate and advanced data analytics and data structures courses while attending a university.

Databases

Data scientists deal with databases regularly. Many universities incorporate database training into technology career programs such as computer science.

Applied Predictive Modeling

Predictive modeling is the basis of many data science positions. This highly specialized task is covered in university programs, often alongside other analytics courses. 

Statistics

Statistics classes are a universal requirement of data science degrees. Students learn this form of mathematical analysis throughout the data science degree program.

Data Visualization

Data visualization is the process of turning raw information into visuals such as charts and graphics. Students learn these skills to help businesses interpret data. 

Online Bachelor’s Degree in Data Science

Online degree programs have revolutionized education. Today, thanks to remote learning, a college education is accessible to people with non-traditional backgrounds. Over the last decade, the quality of online education has improved drastically. 

Scheduling options vary between schools. Courses are either synchronous or asynchronous. Synchronous courses take place live, usually on a regular schedule with interactive video calls and a full virtual class. Asynchronous courses are flexible and allow students to learn and complete coursework on their own time. Here are some features and benefits of online bachelor’s degree programs:

Flexible Degrees

Flexible asynchronous courses allow students to work where they want and when they want. This is one of the primary draws of remote learning.

Transfer Opportunities

Online degrees (when issued by real universities) are valid and transferable. A degree earned online looks (and is) exactly the same as a degree earned in-person.

Cost Effective Education

Sometimes, online tuition and fees are less costly than in-person programs. Plus, you’ll save on fuel and transportation costs, along with room and board.

Multiple Programs

Flexible online degrees allow students to attend multiple programs at the same time. Students often choose a college program and a coding bootcamp to graduate with extra experience.

High-Quality Education

Online bachelor’s degree programs offer the same top-notch curriculum as in-person courses. Nationally and regionally accredited institutions also offer online degree options.

Learn and Work

Working your way through school is more flexible than ever thanks to online degrees. Many students use the time as an opportunity to get ahead of the game with their finances.

Data Science Education Pathways

Data science is a dynamic and complex career path. As a result, education requirements aren’t the same across the board. In a way, this gives students the flexibility to choose the route that’s best for them. The most common types of education for data science careers are community colleges, universities, and coding bootcamps.

Master’s Degree

After earning a bachelor’s degree, students can complete a master’s degree with an additional year or two of study. On average, a master’s degree costs $40,000 from a graduate school.

  • Program Length: 1.5 – 2 Years
  • Average Cost: $40,000 Total

Advanced Degrees

After earning a master’s degree, students can earn a doctorate or post-doctorate degree. These degrees are the most advanced education available in the field, and take years to complete.

  • Program Length: 3 – 7 Years
  • Average Cost: $48,900 Total

Coding Bootcamp

Coding bootcamps are job training programs designed to equip students with marketable tech skills. These short-term programs cover only what students need in the data science field, and many offer job guarantees after graduation.

  • Program Length: 3 – 12 Months
  • Average Cost: $13,500 Total

Data Science Degree Options

As we discussed previously, few universities offer dedicated data science degrees. Instead, students major in a data science-related field. Graduates with STEM degrees (especially in computer science) can readily transition into data science careers. Here are the degrees that many data scientists enter the field with:

Bachelor’s Degree in Computer Science

Computer science is the primary degree chosen by data science professionals. The program is an excellent choice for those who need a general technology education. Computer science is also one of the leading technology degree choices for undergraduate students.

Bachelor’s Degree in Data Administration

Data administration degrees are useful for prospective data science. The program focuses on the intricacies of managing data and large data sets. A bachelor’s degree is usually an entry-level requirement for data administration jobs.

Bachelor’s Degree in Software Engineering

Software engineers are advanced programmers with a keen ability to design systems that work. This degree path is also a common (and good) choice for data science students. Software engineers also come from coding bootcamps and self-educated backgrounds.

Bachelor’s Degree in Business Analytics

Business analytics is a highly profitable career path. Today, many institutions offer business analytics degrees for future data scientists. Business analytics is an increasingly important career path in the age of big data and data mining.

Data Science Professional Organizations

Professional organizations are an excellent way to get the most out of a data science career. Students also benefit from joining a professional organization. These groups formed to discuss ideas, distribute resources, and provide networking opportunities for professionals. The following are some of the top data science professional organizations in the United States and abroad:

INFORMS is the Institute for Operations Resources and Management services. This well-known professional organization hosts conferences on business analytics and data. Members are also invited to attend the organization’s annual meetings.

AIST is the Association for Information Sciences and Technology. Data scientists attend AIST events for networking, job opportunities, conferences, and more. The organization also offers numerous member perks.

The IIA, or International Institute for Analytics, is a worldwide data analytics organization. The organization also caters to professionals from around the analytics field. The IIA offers leadership training, local events, advisory services, and more.

The AIS, or Association for Information Systems, is a world-class professional organization catered towards data and information science workers. The organization offers webinars, conferences, events, and job resources.

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