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What are the Best Schools for Data Science in 2023?

Whether or not data scientist can still be considered the sexiest job of the 21st century, when considering the enduring relevance of data science, the numbers don’t lie. As corporations and other organizations continue to harness data to drive growth and performance, there has never been more demand for the bachelor’s degrees, master’s degrees, and university-offered professional certificates that can provide the key skills needed to succeed as a data scientist.

According to data provided by the National Center for Education Statistics, in fact, the 200,000 degrees and certificates awarded in computer science and mathematics in the US in 2021 represent over 100% growth from just a decade prior.


This growth should come as no surprise: the US Bureau of Labor Statistics (BLS) estimates the median data scientist in the US earns just over $100,000 annually, more than 2x the annual median wages for the country as a whole. In reality, mid- and late-career data scientists at high performing companies can earn much more. And it’s not like the opportunities are limited. The BLS forecasts 36% growth in data scientist headcount by 2031, over 7x the growth rate projected for the US labor market as a whole over the same time period.

Of course, a booming job market doesn’t mean there isn’t any competition for these roles. On the contrary: for each opening hiring managers and recruiters receive reams of resumes from candidates eager to play a central role in tomorrow’s data economy. As a result, aspiring data scientists interested in investing in their futures are keen to find and enroll in the best schools for data science. But again, easier said than done: not only are there a vast number of schools out there purporting to offer the best data science education, but it’s not exactly clear what is even meant by best. After all, no two students are the same, so while Columbia University might be the best school for one student, Carnegie Mellon University or University of Texas — Austin might be better for another.

With this in mind, we set out in this article to map how you can identify for yourself what your best schools for data science might be. After breaking down exactly how a data science bachelor’s degree, master’s degree, or professional certificate can launch you onto your data science career path, we’ll present some of our favorite programs and lay out some factors to take into consideration as you research programs.

Data science career path: what’s the role of education?

Data science is a highly interdisciplinary field, combining computer science, applied mathematics, machine learning, and research science to develop new ways to extract actionable insights from the big data sets produced by corporations, human activity, and the environment every day. This interdisciplinarity means there are a variety of entry points into data science, both in terms of an individual’s educational background and their career stage. As you’ll see, the different educational options offered by colleges and universities aren’t just about giving students progressively more advanced training, but about providing opportunities for students who have already progressed along other paths to pivot and leverage their existing skills to transition into data science.

Data science bachelor’s degrees

Up until recently, students interested in leveraging a bachelor’s degree to pursue a career in data science would major in an adjacent field like computer science, advanced statistics, business, or even information technology, perhaps complementing their course of study with a relevant minor. For many, this remains a viable path, especially because it allows the student to retain optionality should they not wish to continue in data science.

Increasingly, however, many universities and colleges are offering specific data science majors and concentrations. These programs generally furnish students with a baseline understanding of the following areas:

  • Fundamental and applied mathematics: calculus, statistics, probability, linear algebra

  • Computer science: Excel, SQL, Python and R programming languages, software engineering, operating systems and systems programming, database systems

  • Machine learning: machine learning algorithms, predictive analytics, deep learning

  • Data management: data engineering, data mining, data visualization

  • Social sciences and humanities, according to individual interest and distribution requirements

In addition to this coursework, many programs either recommend or require students to complete an internship or capstone project in order to gain experience applying what they’ve learned in a real-world setting.

In the US, bachelor’s degrees are generally a four-year commitment, with an average cost of attendance of $102,828 for students paying in-state tuition at a state school and $218,004 for students at a private university. Upon graduating, students who are viable candidates for entry-level data analyst, data scientist, business analyst, and data engineer positions. To move up in the field of data science, however, there is a good chance that a college graduate will eventually need to earn a master’s degree, which we’ll turn to now.

If you’re interested in learning more about data science bachelor’s opportunities, be sure to check out the programs listed at the end of this article.

Data science master’s degrees

According to one recent study, over two-thirds of data scientists hold a master’s degree or higher. While not all data scientists will hold their master’s degree in data science specifically, a data science master’s is growing in popularity as the field matures, junior data scientists look to advance their careers, and professionals from different backgrounds look to transition into data science.

While many universities frequently offer full-time in-person master’s programs, online data science master’s degrees are increasingly offering students looking to advance or transition their careers the flexibility to continue working and avoid relocating while doing so.

As would be expected, the curriculum for a data science master’s resembles that of a data science bachelor’s but is more condensed, advanced, and generally omits distributional requirements such as courses in the social sciences and the humanities. Master’s students in a data science program can expect to take courses in:

  • Computer science: advanced data science algorithms, machine learning and deep learning, software engineering

  • Statistics and linear algebra:  advanced data analysis, statistical modeling R or Python, and other applied mathematics

  • Data science principles: research design, data management (data collection, data mining, data cleansing, database management, etc.), data science ethics

  • Industry-specific electives such as Big Data in Finance, Sports Performance Analytics, Marketing Analytics, etc.

As with bachelor’s programs, most data science master’s students are expected to complete an internship and a capstone project. According to Education Data Initiative, the current average cost of a master’s of science degree in the US is $59,720.  As we explain in our article on master’s in data science salaries, students with aptitude for mathematics, computer science, and information technology have a high likelihood of seeing a high return on their up-front investment in the degree by working in one of the following high-paying capacities:

If you’re interested in learning more about master’s in data science opportunities, check out our full guides on in-person and online programs.

Data science professional certificates

In addition to traditional two- and four-year degrees, many universities and colleges offer both professional education and executive education certificate programs in data science. Professional education (sometimes “continuing education”) programs, usually offered online, can take the form of a bootcamp — a condensed but comprehensive course of study that provides career services aimed at placing graduates in entry-level positions — or a shorter certificate program. In both cases, the goal is to provide training in specific data science skills. University professional education programs are good options for aspiring data scientists who don’t wish to spend the time and money on a traditional degree but would still like to benefit from the education and name-recognition a college or university can provide.

Executive education programs, on the other hand, are designed to help managers, executives, and other leadership gain fluency in data science concepts and terminology and better understand how to implement data solutions at their companies, including particular use-cases for their industries and how to effectively hire and lead teams of data scientists. These kinds of programs can be completed online or in one or several short residencies.

The best schools for data science

Now that we’ve covered what colleges and universities have on offer, it’s time to dive into what goes into being one of the “best” schools for data science.

What does it mean to be the best?

With such astronomical salaries on offer, it only makes sense that future data scientists would try to put their best foot forward by seeking out the best colleges and universities for their data science degree or professional program. Just a quick Google search will show you a number of sites working to fill this need by ranking data science schools to ease research and decision-making.

While these rankings might very well help the process along, however, to merely rank programs collapses some important nuance: identifying the “best” programs presumes that just one kind of student is seeking data science education. In reality, each prospective student has their own background, priorities, realities, and needs — so what’s best for one might not be best for all.

 Our approach

In light of this fact, our approach to collecting the best schools for data science is slightly different than the norm: we certainly aim to feature stellar programs, but we also strive to prioritize accessibility. Accordingly, we’ve sought to feature a broad swath of programs, all of which are stellar but differ in the following ways:

  • Reputation

  • Size

  • Geographic location

  • Modality

  • Focus (e.g. machine learning, data science for social good, industry emphases, etc.)


So while you’ll find many of the big names you would expect to find on such a list, you’ll also find some great options that, while perhaps not usually top-of-mind, nevertheless provide quality data science instruction online or at a fraction of the price.

Our list of the best schools for data science


The University of Texas – Austin

Austin, Texas

Boasting an award-winning faculty and a comprehensive collection of degree and certificate options, the University of Texas – Austin’s Department of Statistics and Data Sciences emphasizes scientific discovery and the power of data to yield world-changing insights. 

Data science faculty

  • 33 tenure-track or professional-track faculty

Data science programs

  • BS in Statistics and Data Science

  • Undergraduate Certificate in Applied Statistical Modeling

  • Undergraduate Certificate in Scientific Computation and Data Sciences

  • Online MS in Data Science

  • Concurrent MS in Statistics

  • PhD in Statistics

  • Graduate Portfolio in Applied Statistical Modeling

  • Graduate Portfolio in Scientific Computation

  • Postdoctoral Fellowship Program

  • Online Certificate in Data Science & Business Analytics (offered by McCombs School of Business)

Available modalities

  • Online (MS in Data Science, Online Certificate in Data Science & Business Analytics)

  • In-person

Undergraduate tuition: 11,406 (in-state); 40,504 (out-of-state)

Graduate tuition: 14,802 (in-state); 28,028 (out-of-state)

Undergraduate acceptance rate: 32%

washington seal

The University of Washington

Seattle, Washington

Administered by the eScience Institute in collaboration with the Center for Statistics and the Social Sciences, the University of Washington’s data science programs embrace the wide-reaching potential for data science to enhance human discovery and improve our world. Evidence of this is the extreme flexibility offered undergraduates and graduates to add a data science concentration to their course of study.

Data science faculty

  • 153 affiliated faculty

Data science programs

  • Undergraduate Data Science Major

  • Undergraduate Data Science Concentration for following major programs:

    • Applied & Computational Mathematical Sciences

    • Atmospheric Sciences

    • Bioengineering

    • Computer Science & Engineering

    • Geography

    • Human Centered Design & Engineering

    • Information School

    • Statistics

  • Masters in Data Science

  • Graduate Data Science Concentration in one of 16 programs

Available modalities

  • In-person

  • Part-time (MS in data science)

Undergraduate tuition: $12,242 (in-state); $40,740 (out-of-state)

Graduate tuition: $20,535 (in-state); $35,781 (out-of-state)

Undergraduate acceptance rate: 56%

MIT seal

Massachusetts Institute of Technology

Cambridge, Massachusetts

Massachusetts Institute of Technology and the MIT Statistics + Data Science Center not for the traditional data science degrees they offer, but for the innovative options to study data science alongside another course of study or alongside your career. Through a data science minor, a bootcamp, and a Micromasters program, MIT offers students realistic and flexible ways to transform their futures.

Data science faculty

  • 23 core faculty members

  • 24 affiliate faculty members

Data science programs

Available modalities

  • In-person

  • Online

  • Part-time (MicroMasters and bootcamp)

Undergraduate tuition: $57,590

Graduate tuition: No cost (fully funded)

Undergraduate acceptance rate: 3.96%

uc berkeley school mark

The University of California – Berkeley

Berkeley, California

Just minutes from San Francisco, Cal Berkeley offers a wide selection of data science paths for students of all backgrounds through their Division of Computing, Data Science and Society and their School of Information. Through the former, Berkeley emphasizes applications of data, machine learning, and artificial intelligence for a wide variety of industries as well as the social and environmental sectors. In this, the division is supported by the Berkeley D-Lab, a research lab supporting R&D and data acquisition for projects in the social sciences and humanities, and the Berkeley Institute for Data Science, which aims to facilitate collaboration between experts from a variety of fields.

Data science faculty

  • 77 faculty and research affiliates

Data science programs

Available modalities

  • In-person

  • Online (online MS in data science)

  • Part-time (online MS in data science)

Undergraduate tuition: $15,444 (in-state); $48,018 (out-of-state)

Graduate tuition: $75,060 (online MS total)

Undergraduate acceptance rate: 16%

northwestern seal

Northwestern University

Evanston, Illinois

Nestled on the shores of Lake Michigan, Northwestern’s Department of Statistics and Data Science emphasizes the application of data science for the betterment of public policy, law, medicine and life sciences, and the social sciences. As the department is small, students have the opportunity to work closely with faculty members.

Data science faculty

  • 19 faculty, 3 affiliated faculty

Data science programs

Available modalities

  • In-person

  • Online (online MS in Data Science)

  • Part-time (online MS in Data Science)

What are the important considerations when choosing a program?

Above, we’ve listed some great data science programs to get you started with your research — but how do you know which is right for you? Here are some things to keep in mind:

Admissions requirements & prerequisites

  • Do you meet the requirements and prerequisites (GPA, standardized test scores, experience, academic background) listed on the program website? 

Program profile

  • Does the program’s profile align with the path you see for yourself? Will you be taking courses that you’ll be interested in and that will launch you into your future?

Industry relationships

  • Does the program have links to an industry or company you are interested in that you’ll be able to leverage for future internship or job opportunities?

Location and learning modality

  • Is a school’s location feasible for you? And cost-effective?

  • Are there online options you can take advantage of to keep costs down and continue working while you study?

Student outcomes

  • Does the student have a history of churning out successful data scientists, as evidenced by data they provide or LinkedIn research?


  • Does a program offer reasonable value for money when taking into account student outcomes, quality of curriculum, and a school’s reputation? 

  • Are you able to afford tuition or will you be able to quickly repay any loans you take out? 

  • Are you reasonably sure that you’ll see significant return on investment in the near- or mid-term?

  • Are there scholarships or grants available that can help defray the cost of education?

How else can we help?

Choosing a data science program is a big decision, and it’s easy to get overwhelmed. To make the process easier, we’ve put together top-notch information specific to data science master’s programs, online-only data science master’s programs, data science scholarships, and data science certificates.

If you’d like to learn more about what it’s like to work as a data scientist before you dive into researching schools, you can also check out our articles on the typical data science career path and how to land your first data science job.