Associate’s Degree

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Associate’s Degree in Data Science

Obtaining an associate’s degree in a data science field is a great way to launch a high-paying career. As the world becomes more reliant on technology, data science careers professionals will become increasingly important in many industries.

But is an associate’s degree in data science worth it? If you’re looking to get your career in motion (and save money doing it), then an associate’s degree in a data science field is worth it. Here, we’ll go over the essential facts about community college data science programs, along with what you need to know before applying.

An associate in data science is a great first step in your technology education. Associate’s degrees are cost-effective, the education is local, and the curriculum is essential to success in the field.

Furthermore, students often earn an associate’s degree then transfer to a four-year university to earn a bachelor’s degree. Starting your education with an associate’s degree (instead of university) can save time and money, and offers a low-risk introduction to the field.

Here on Study Data Science, we’ll go over some key facts about community colleges, associate’s degrees, and data science programs so you can proceed with confidence. We’ll also cover data science job opportunities, salaries, professional organizations, and more.

Here’s a rundown of what an associate’s degree in data science entails—from cost to admissions requirements. Associate’s degree programs at community colleges generally take two years to complete:

An associate’s degree program costs, on average, less than $4,000 per year.

Associate’s degrees are transferable to universities for students looking to earn a bachelor’s degree.

Simply earning a high school diploma or GED is sufficient to get into community college.

Regionally-accredited community college programs are easily transferable.

What is an Associate’s (AS) Degree in Data Science?

An associate of science degree in data science is a 2-year education program available through community colleges. An associate’s degree is a step below a bachelor’s degree on the higher education scale, and it opens the door to many job opportunities.

An associate of science (AS) degree in data science encompasses multiple degree paths that ultimately lead to a career in data science. Associate’s degrees in statistics, machine learning, and similar subjects count under the ‘data science’ degree umbrella term. Meanwhile, some institutions offer dedicated data science degrees.

AS in Data Science Benefits

An associate’s degree in data science or a related field has numerous benefits. The most pronounced advantage of an AS degree in a technical field is increased job prospects. Compared to high school graduates, individuals with an AS degree are 37% less likely to be unemployed

An associate’s degree in data science is a great introduction to the tech industry and opens the door to additional education. Many students attend community colleges before a university. The popular transfer option allows students to save money and ease into the subject, as opposed to spending thousands on a room, board, and tuition at a four-year university right after high school.

Data science is one of the most lucrative and fastest-growing tech careers. Data scientists enjoy a hot job market, stable employment, and high starting salaries. Here are some essential facts about a career in data science:

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

According to the Bureau of Labor Statistics, the greater information sciences career field (including data science) will experience a growth at a much faster pace than average. These fields will grow by 16% between 2018 and 2028, which is much faster than the national average of just 5.2%.

  • Job Openings
  • Jobs Filled

Having a degree in data science or a related field is advantageous in good and bad economic times. And though you’ll get the most benefit from a bachelor’s degree, having an associate’s degree is still a good first step. You’ll learn the essentials and demonstrate your abilities to employers.

To sum it all up, a degree in data science is a great option if you’re looking for a future-proof tech career. Opportunities for data scientists continue to grow, and the importance of the field will be difficult to overstate in the 2020s. 

In short, computer science is a future-proof career field that’s worth considering. Computer science salaries are high, and opportunities are plentiful. An associate’s in computer science is an excellent way to test the waters and see if an IT career is right for you.

Data science is a highly technical profession with numerous specialization opportunities. In addition to an associate’s degree, students can obtain certifications to beef-up their resumes. Certifications for data science careers range in price from a few hundred dollars to over a thousand. These certifications vary in topic and scope, but any additional training is useful for data scientists. 

Data analytics is one of the largest data science subfields. Data analysts often benefit from additional certifications, as the job requires specialized skills. CAP (Certified Analytics Professional) training and certification cost $695 from the CAP organization.

Cloudera offers a 120-minute SQL development and data analytics certification test. The exam tests your knowledge of analytics, programming, and Cloudera software. The test costs $295 per attempt, and the certification is valid for two years.

Amazon offers big data certification for data scientists and data analysts. Test takers must have two years of experience in the field before attempting the exam. The $300 test covers big data ecosystems, and the certificate is valid for two years.

Oracle is a leading provider of business cloud computing and data services. Data scientists who want to work with Oracle systems can take a business intelligence certification course with the company. The certification exam costs $245, and the certificate never expires.

Data Science Associate’s Degree Jobs

Data science jobs are abundant, especially for well-educated professionals. Today, an associate’s degree can help you qualify for entry-level data positions at some companies, though a bachelor’s degree or additional education is often required.

Nonetheless, data science jobs offer some of the highest salaries and best career growth opportunities in the industry. This broad field includes several distinct career paths, covering everything from big data to business intelligence. Here are some of the most common data science jobs and career opportunities:

Data Scientist

Data scientists are general experts in the field and work for a wide range of industries. Data scientists use their knowledge of complex algorithms, data structures, and databases to help businesses make sense of large volumes of information. 

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

Data Analyst

Data analysts share some roles with generalized data scientists with an emphasis on the interpretation of data. When businesses collect information (through data mining or similar means), data analysts help turn numbers into actionable and meaningful information.

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

Machine Learning Engineer

Machine learning and artificial intelligence are the new frontiers for data scientists. Machine learning engineers work on systems that, in essence, teach themselves information. This field is becoming increasingly important in this new era of automation.

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

Database Administrator

Database administrators are in charge of maintaining databases. These professionals are the go-to technology professionals for data-driven businesses. Due to the shortage of database expertise today, administration careers look promising.

  • 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

Community College Accreditation

Community college accreditations certify the validity of the degree program. There are several types of accreditation, both within each school and from external agencies. It’s essential to understand the types of community college accreditation before choosing a degree program, especially if you intend to transfer to a university for a bachelor’s degree. Here, we’ll discuss the most common kinds of accreditation, and what you need to look for when applying to earn an associate’s degree.

National Accreditation

Although national accreditation sounds the best, it may not be the kind of accreditation you’ll likely want to have as a data science student. Nationally accredited programs are for special degrees such as theology and music. These programs are accredited by the Accrediting Commission of Career Schools and Colleges (and others) to ensure schools meet certain requirements for specific degrees.

Institutional Accreditation

Institutional accreditation is designed to validate courses within a single school or group of related schools. This form of accreditation carries no weight outside of the college that uses it. You’ll find institutionally accredited course options for your degree program. For example, a data science student could choose an accredited programming course that counts towards their degree.

Specialized Accreditation

Specialized accreditation is exactly what it sounds like. Schools often provide specialized courses for local training and certification programs. These special courses have their own accreditation, making them valid within whatever field they cover. Data science students generally won’t deal with specialized accreditation.

Regional Accreditation

In most cases, data science students should look for (and choose) regionally accredited community college programs. An associate’s degree from regionally-accredited school is valid everywhere, and students can seamlessly transfer credits to a four-year university. There are seven accrediting agencies in each region of the United States that grant this accreditation to community college degree programs.

Community colleges exist for the betterment of the local community, and admissions are often painless and inclusive. You don’t need to meet many requirements to get into a local data science program, though there are a couple of common prerequisites for associate’s degree programs. And though requirements may vary between schools and regions, most community colleges require the following to attend:

High School Diploma

A high school diploma is a basic requirement to attend an associate’s degree program at most institutions. This proves your basic education level, and anyone with a diploma should be capable of succeeding in the next level of education. If you don’t have a diploma, don’t worry; you can earn a GED instead.

GED

A General Education Development (GED) is a legally-valid high school diploma alternative. Community colleges will accept a GED in place of a high school diploma. In most of the United States, earning a GED is highly affordable. The test costs around $35 per subject and extensive study materials are available online for free.

An associate’s degree in data science is an economical choice. The National Center for Education Statistics reports that a typical associate’s degree costs a total of $10,091, and many programs cost significantly less. Plus, numerous scholarships and tuition discounts are available, further decreasing the financial burden of a degree program. In short, you don’t need to accept decades of debt for a degree.

A 2019-2020 College Board survey reported that the average annual cost at public community colleges is $3,730 per year, for a total of $7,460. And while that’s not a trivial expense, it’s significantly less expensive than even the most economical four-year universities. An associate’s degree can save you thousands, especially if you choose to attend a community college for two years before transferring to a university.

Scholarships for Data Science Associate Degrees

Everybody (yes, everybody) who applies for a degree program should search for scholarships. An unbelievable amount of scholarship funding goes unused each year, and you’d be surprised at what you qualify for. Scholarships can save students thousands of tuition costs.

Associate in Data Science Financial Aid

Financial aid makes college accessible to those who don’t have thousands saved up for an education. Most people qualify for some form of financial aid, and plenty of institutions offer loans and other programs to students who can’t afford school.

Student Loans and Financing Rates

It’s essential to pay attention to interest rates before taking out a loan. Interests will have a profound effect on how much you end up paying for an education. In the world of student loans, a fixed APR of less than 5% is considered quite good, though most loans end up being double that or more. Generally speaking, the smaller the better, and be wary of high-rate loans from sketchy lenders.

Popular private lenders for community college and associate degree programs include Wells Fargo, PNC, Earnest, Sallie Mae, MPower, Risla, LendKey, SoFi, and Navy Federal. Government-backed loans are also available. 

It’s important to remember that, at this time, most student loan debt is not forgivable through bankruptcy. That doesn’t mean you shouldn’t have them, but students should be informed about the risks and approach lenders with caution. 

Data science degree programs share a similar curriculum across the board, covering essential subjects such as statistics, algorithms, and programming. Due to the technical nature of the field, data science is usually an ‘associate of science’ or AS degree. In most AS degree programs, students are required to complete a total of about 60 semester credit hours. These credits are split between degree-specific courses and core classes, which are made up of general education courses such as English and mathematics. 

General Education and Humanities

General education is a staple of the college experience and helps produce well-rounded graduates who are skilled in multiple areas. These courses don’t take up the majority of your time, but they’re still essential. Accreditation agencies require students to complete a minimum of 12 semester credit hours to graduate. 

Mathematics

Data science students should expect to spend time in mathematics courses. Math is an integral part of data science. For students who don’t like math, keep in mind that plenty of resources are available at little to no cost, including extra study materials and tutors. 

Coding and Programming

Coding is a major part of data science as well, and students should expect some level of code training during an associate degree program in the field. In most cases, coding languages such as Python and R will be the primary focus.

Statistics

Statistics play a significant role in data science and will be a focus of the data science math curriculum. The level of statistical training varies between schools, but students should expect to spend a good portion of their time on the subject. 

Specialty Courses

Depending on your specific course of study, specialty programs are likely to find their way into your schedule. These include wildly interesting subjects such as an introduction to machine learning and artificial intelligence.

Electives

Students will choose various electives to balance out their associate’s degree training. These include courses such as foreign languages, programming, and more. Students generally spend the least amount of time in elective courses.

Data science is a broad field with numerous subject requirements. Chief among these are courses in programming, analytics, and statistics. Individual course requirements vary between schools, but the general theme remains the same. Data science is a highly technical field with universal core education requirements. Here are the most common courses in a data science associate’s degree program:

Basic Computer Programming (Programming I)

Basic programming training is essential for most data science careers. Community colleges offer basic programming courses, which often cover languages such as R and Python.

Introduction to Analytics (Analytics I)

Data analytics is a key part of data science, and students will have an opportunity to learn the craft in an introductory analytics course. This course is often a core degree requirement.

Introduction to Databases (Databases I)

Databases are the bread-and-butter of many data science jobs. Community colleges offer introductory database courses early in the program, and these courses are always required.

Data Structures for Analytics

After learning basic analytical skills, students move on to data structures for analytics. This course expands on Analytics I and helps students understand algorithms.

Applied Predictive Modeling

Predictive modeling is essential to data science, and most college programs cover it. In this course, students learn about data mining and how to predict trends from historical data. 

Analytical Methods

Analytical methods courses emphasize the importance of analytics in the data science field. This class expands on the subjects covered in Analytics I and similar 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 Associate’s Degree in Data Science

Thanks to the evolution of technology, it’s now possible to earn an associate’s degree entirely online. A decade ago, it was much more difficult to get an online education. Today, an online degree program is a serious consideration for many students.

Online courses are polished and high-quality, often featuring the same curriculum as in-person courses. For many students, online programs make it possible to earn an associate’s degree conveniently.

The two types of online degree programs are synchronous and asynchronous. Synchronous instruction happens in real-time and requires scheduled attendance. Asynchronous instruction is either self-paced or flexible and doesn’t require set class times.

Flexible Degrees

Students often choose online degree programs due to their flexibility. People with family or work obligations benefit most from the ability to study at home or on the go.

Transfer Opportunities

Online associate’s degrees are often transferable, just like in-person programs. Students can transfer credits to in-person or online university programs.

Cost Effective Education

Sometimes, online degree programs are less expensive than traditional courses. Regardless, every online student saves on fuel or public transportation costs.

Multiple Programs

Remote students have the flexibility to attend multiple education programs. Many students also attend coding bootcamps or earn certifications while studying. 

High-Quality Education

Online degree programs and in-person courses often utilize the same curriculum and course materials, ensuring all students receive a high-quality education. 

Learn and Work

Many students have bills to pay, and online degrees make it easier than ever to manage. Students can work full-time or part-time and attend flexible online courses.

Data Science Education Pathways

Data science has numerous education pathways, including associate’s degrees. Due to the complexity of the field, associate’s degrees in data science aren’t that common. Instead, students interested in a data science career often opt for an AS in statistics or a similar field, then transfer to a university to complete their education. Other students opt for career-specific training in a coding bootcamp, which offers the fastest route into a data science career. Here are the most common data science education options:

Bachelor’s Degree

A bachelor’s degree is often a minimum requirement for data science jobs, though some companies prefer experience over education. Students earn a bachelor’s degree from four-year universities, and many spend two of those years in a community college to save money.

  • Program Length: 4 Years
  • Average Cost: $20,000 / Year

Master’s Degree

A master’s degree in data science is the next level of education above a bachelor’s degree. This advanced title opens the door to senior data science positions and higher salaries. A master’s degree takes 1.5 to 2 years to complete at a university’s graduate school.

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

Advanced Degrees

Additional degrees are available in graduate school, including a PhD (or doctorate) in a data science field. This degree earns a student the title of ‘Dr.’ and represents one of the highest levels of expertise available in the field.

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

Coding Bootcamp

Coding bootcamps are career training programs designed to help beginners learn data science and get a job. These short-term and intensive schools appeared about a decade ago, and account for an increasing share of job placements in the field.

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

Data Science Degree Options

Data science is more of a career field than a specific degree option. Due to the complex and varied nature of the subject, few schools offer dedicated ‘data science’ degrees. Instead, colleges and universities offer countless related degrees that students specialize in. These include data-related paths and computer science courses. Here are the most common degrees chosen by data science students.

Computer Science Degree

Computer science is the go-to technology degree for thousands of professionals, including data scientists. A degree in computer science is an excellent way to build the foundational skills for a data science career. 

Data Administration Degree

Data administration covers the essentials of a data science job. This popular and high-paying career path offers a data-centric curriculum with emphasis on databases. Students often combine data administration with a minor in computer programming.

Software Engineering Degree

A software engineering degree is an ideal substitute for a data science program. Software engineers learn key programming and software engineering skills, which allow them to integrate into a data science career with relative ease.

Business Analytics Degree

A business analytics degree is a popular choice for data analysts. This program opens the door to high-paying jobs at major companies. Business analysts focus on the statistical and modeling aspects of data science, which gives them an advantage in the field.

Data Science Professional Organizations

Professional organizations are one of the tech industry’s best-kept secrets. These groups offer enormous advantages to anyone who becomes a member. Students and professionals alike will have access to networking opportunities, community resources, and vital tools that collectively increase the productivity and prosperity of the field. Here are some of the most well-known data science and data analytics professional organizations:

The Institute for Operations Resources and Management Sciences (INFORMS) is one of the top professional organizations for data-related professionals. The organization hosts annual meetings, business analytics conferences, and resources for data scientists.

The Association for Information Science and Technology (AIST) is a well-known professional organization that caters to data scientists, data analysts, and other information-based careers. The organization offers networking opportunities, jobs, conferences, and legal information.

The International Institute for Analytics (IIA) is a multinational organization for data analysts and other analytical professionals. The institute offers networking opportunities, leadership training, conferences, membership perks, and advisory services.

The Association for Information Systems (not to be confused with the Association for Information Science and Technology) is a professional organization for data scientists that offers career support, webinars, and networking opportunities.

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