phd in data science waterloo

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7 Best Universities in Canada to Study Ph.D. in Data Science

A Ph.D. degree is the highest academic qualification anyone can earn. And with Harvard Business Review declaring data scientist to be the sexiest job of the 21 st century, a Ph.D. in Data Science should probably be called the sexiest university degree of the century.

Universities in Canada, like the ones in other highly advanced countries, are offering such degrees in abundance. Here, we have listed the seven best Canadian universities that offer a Ph.D. degree in Data Science.

Top Schools Offering Ph.D. in Data Science Programs in Canada

1. university of british columbia.

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Beginning its journey over a hundred years ago, the University of British Columbia (UBC) offers higher education to nearly 65,000 students, including over 17,000 international students.

It has two main campuses sited in Vancouver and Okanagan of the province of British Columbia. It is recognized as one of the top 40 universities in the world and top three universities in Canada by a number of major university rankings.

Nobel laureates like economist Robert Mundell and physicist Bertram Brockhouse are a couple of notable alumni.

UBC’s Department of Computer Science administers a Ph.D. in Computer Science program. Its research areas include a number of concepts relevant to Data Science like Data Integration, Text Mining, Web Databases, and Optimization.

It is an on-campus program that is only available in a full-time format. It takes place at the Vancouver campus and can be completed within three to five years.

2. HEC Montréal

HEC Montréal is actually not a university; rather, it is a graduate school of the Université de Montréal. Founded in 1907, the business school currently has over 14,000 students.

All of its classes take place in its two buildings in Montreal, Quebec: the Côte-Sainte-Catherine building and the Decelles building.

Despite being a French-language institution, it also offers programs that have English as the medium of instruction.

Louis R. Chênevert, the former CEO of United Technologies Corporation and president of Pratt & Whitney, graduated from this institution.

HEC Montréal offers a Ph.D. in Administration – Data Science program in collaboration with three other universities: McGill University , Concordia University , and Université du Québec à Montréal (UQAM). The partnership provides students with access to resources from all four Montreal-based institutions.

The English-language program requires 90 credits to be completed in full-time study mode. The duration of the program is typically four to five years.

3. University of Waterloo

Next on our list of universities in Canada with a Ph.D. in Data Science is the University of Waterloo . Founded in 1957, the University of Waterloo (UWaterloo) has a student population north of 40,000.

Around 20 percent of all undergraduate students and 40 percent of all graduate students have come from outside Canada. According to U.S. News and World Report Best Global Universities 2019, the university located in Waterloo is Canada’s best for Computer Science and second-best for Engineering.

It is the alma mater of Rasmus Lerdorf, the programmer who authored the first two versions of the PHP scripting language.

UWaterloo’s Ph.D. in Computer Science includes research areas like Databases, Information Retrieval, and Machine Learning that are relevant to the field of Data Science.

Students may take on this on-campus program in either full-time or part-time study mode. Admission takes place thrice a year at the start of the academic terms Fall, Winter, and Spring.

4. University of Alberta

The University of Alberta is a top-tier Canadian research university based primarily in Edmonton, the capital of Alberta. It was established in 1908, the same year that UBC came into being. The total student enrolment stands at over 40,000.

Nobel-winning physicist Richard E. Taylor and former Canadian prime minister Joe Clark graduated from this university.

Alberta’s Department of Computing Science runs a Ph.D. in Computing Science that has a wide range of research areas. A few of them, including Database Systems and Machine Learning, are related to the field of Data Science.

There’s also a Ph.D. in Statistical Machine Learning offered by the department in collaboration with the Department of Mathematical and Statistical Sciences. These are full-time programs that are ideally completed within five years.

5. Dalhousie University

Founded over two hundred years ago, Dalhousie University (Dal) is one of the oldest universities in the Great White North. Its student population is around 19,000, which includes nearly 4,000 international students representing over 115 nationalities.

Each of its three campuses is located in Halifax, the capital of Nova Scotia. The university is the alma mater of Nobel-winning astrophysicist Arthur B. McDonald, Canadian PMs R.B. Bennett, and Brian Mulroney, as well as former Xerox Corporation CEO and chairman Charles Peter McColough.

Dal offers a Ph.D. in Computer Science which allows students to specialize and develop deep expertise in Data Analytics. The Faculty of Computer Science’s Big Data Analytics & Machine Learning research cluster, which is based in the Institute for Big Data Analytics, helps students to conduct independent and original research. The Ph.D. program takes around three to four years to complete.

6. University of New Brunswick

The University of New Brunswick (UNB) started off in 1785 as Canada’s first English-language university. It has two campuses: one situated in New Brunswick’s capital Fredericton, and the other in the port city of Saint John in the same province. The university has more than 10,000 students hailing from over 100 countries. It was recognized as the country’s most entrepreneurial university in 2014 by Startup Canada.

UNB’s Faculty of Computer Science offers a Ph.D. in Computer Science one of the many research areas is Data Management, Analytics, and Mining. The program can be completed in three years. While it is ideally a full-time program, students could be permitted to take on the program on a part-time basis under certain conditions.

7. Ryerson University

Beginning its journey in 1948 as a postsecondary institute with merely 250 students, Ryerson University has grown into a full-fledged university with over 45,000 students.

It is located in Toronto, Ontario, and is the province’s most applied-to university relative to available accommodation.

Four Seasons Hotels and Resorts founder and chairman Isadore Sharp and former Maple Leaf Sports & Entertainment president and COO Tom Anselmi are a couple of its notable alumni.

Ryerson’s Faculty of Science administers a Ph.D. in Computer Science which provides students with the option of specializing in Data Science and related subjects like Machine Learning and Data Mining. The nominal duration of the thesis-based program is three years. The format for this program is full-time.

FAQS About Studying Ph.D. in Data Science

Which university in canada is best for a ph.d. in data science.

When it comes to Canada, the University of British Columbia would probably be your best pick for getting a Ph.D. in data science. Requiring nearly 5-6 years of your time, this professional degree program will challenge its students to analyze data from a wide range of domains while allowing each student to solve real-world problems created by partnered businesses.

How Long Does It Take to Earn a Ph.D. in Data Science?

If you want to graduate with a Ph.D. in data science, the time required ranges from 4 years to 9 years, depending on the person. To go down this track, you would probably apply for a Doctor of Philosophy in Computer Science and take the track of data analysis, which is a major part of data science.

If you just want to complete a Master’s degree in data science, you only need to spend 10 months of your time in this accelerated professional degree program. Analyzing data from a real-world environment, the experience that you would get from these types of programs would be second to none!

We hope that this article on universities in Canada with Ph.D. in Data Science was helpful. Make sure to also check out our  Data Science Programs for International Students  for some of the currently open data science courses around the world!

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Waterloo Apple PhD Fellowship in Data Science and Machine Learning

Note: this fellowship is no longer accepting applications. this page is for reference only..

The funding will establish a Fellowship Fund to support PhD candidates in Data Science and Machine Learning at the University of Waterloo. Fellowships will be offered starting in 2022.

An Apple PhD Fellow will receive $37,500/year for two years. Up to two fellowships will be awarded each year for two years starting in 2022.

Eligibility & Selection Criteria

• Students must be in the 2 nd or 3 rd year of their PhD program in the School of Computer Science at the University of Waterloo.
• Students must remain registered full-time and be in good standing in their PhD program for the duration of the Fellowship.
• Proposed research must be in the areas of Data Science or Machine Learning.
• Students can receive this award in addition to other internal or external scholarships (e.g., OGS, NSERC, etc.)
• Students already supported by a comparable industry award at the time of selection are not eligible.
• Applications are evaluated on the basis of students' academic achievements, leadership contributions and potential, and the strength of their research proposal.
• Research proposals are evaluated for innovative concepts that are relevant to Apple’s research areas, as well as their potential impact to the field.
• Interested students must submit an application package to the Director of Graduate Studies by March 31
• UW transcript
• a research propoal
• The completed package should be sent to the Director of Graduate Studies at [email protected]

Reference Letters

• 2 references must submit support letters for the student directly to the Director of Graduate Studies at [email protected] . One of the references must be the student’s primary thesis supervisor.

Recipients will be selected in April by the School Director in consultation with the Sponsor.

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The University of Waterloo acknowledges that much of our work takes place on the traditional territory of the Neutral, Anishinaabeg and Haudenosaunee peoples. Our main campus is situated on the Haldimand Tract, the land granted to the Six Nations that includes six miles on each side of the Grand River. Our active work toward reconciliation takes place across our campuses through research, learning, teaching, and community building, and is co-ordinated within the Office of Indigenous Relations .

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Data Analytics for Behavioural Insights

As advances in technology and the widespread availability of data rapidly progress, you can leverage data insights like never before. To help inform decisions, you need effective tools and techniques to analyze data, answer important questions about your communities, and inform policy development and decision-making.

This three-course certificate program extends beyond basic methods of coding and analysis, enabling you to interpret data findings from complex statistical analysis and directly apply them to decision-making and policy development. It is specifically designed for individuals who have a limited background in statistics and are interested in acquiring skills that will enable them to analyze data, extract insights, and apply them to decision-making. As part of this program, you will also discover how to understand and interpret data through a comprehensive introduction to statistics, regression analysis, Python, and R, and through unique case studies based on Canadian public data.

Establish the foundational knowledge you need to use complex data to tell stories about your funding, your policies, and your programs, and to deliver results for your organization.

NOTE:   Each course is offered individually , or as part of the three-course Data Analytics for Behavioural Insights certificate program. You will receive a certificate for each individual course you successfully complete, and then a certificate upon successful completion of the entire program.

Basics of Modern Statistics and Analysis

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Python and Public Data

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Behavioural Insights, Modelling, and Predictive Analytics

Some prior knowledge of R and statistics is recommended before taking this course.

Get a sample of what you'll learn in week two of   Python and Public Data !

Receive a certificate from the University of Waterloo

Upon successful completion of all three courses, you will receive a professional education program certificate from the University of Waterloo.

• Policymakers:  Do you develop policies for any public service sector (e.g., health care or municipalities)? Understand how modern data analytics techniques can better inform your decisions.
• Public servants, non-profit and community leaders:  Are you working in public service or leading a business improvement area, non-profit, or public office? Gain behavioural insights that can be used to inform your work, improve your community, and increase your chances of success when competing for funding.
• Public service organizations:   Do you primarily serve the public sector or the general public? Elevate your understanding about your customers and partners and learn to make more informed decisions that better serve public interest.
• Draw behavioural insights to tell effective stories that support decision-making.
• Draw conclusions that have the power to impact your decision-making and policy development.
• Analyze data with the statistical methods used by social scientists.
• Use basic methods of coding to conduct increasingly sophisticated statistical analysis with R and Python.

Access case studies based on Canadian public data

Review unique case studies, based on publicly available Canadian data, and conduct analysis that can be used to draw behavioural insights. Use your learning to analyze data sets for your own organization and inform decision-making and policy development.

Anindya Sen, PhD

Director, master of public service (mps) professor, department of economics.

Anindya Sen is the lead author of the Data Analytics for Behavioural Insights Program. Sen is professor of economics, director of the Master of Public Service (MPS) program, and acting associate dean of co-operative education and planning at the University of Waterloo. He is also the director of Computational Data Analytics for the Social Sciences and Humanities (CDASH). Prior to joining the University of Waterloo, Sen was an economist at the Competition Bureau of Canada.

His research focuses on the economics of public policy, with an emphasis on estimating the statistical effects of government intervention and imperfectly competitive market structures. He has published research on the effects of government policies on COVID-19 cases, the relationship between market concentration and gasoline prices, the impacts of higher cigarette taxes on smoking, the effects of higher minimum wages on employment and poverty, and the consequences of incentive programs on electricity usage. These papers have been published in peer reviewed journals such as the Canadian Journal of Economics, Journal of Law and Economics, Journal of Health Economics, Journal of Regulatory Economics, International Review of Law and Economics, Labour Economics, and Canadian Public Policy. His work has been extensively covered by the Globe and Mail, the Financial Post, CBC, and the Toronto Star.

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Study In Canada > Colleges In Canada > UWaterloo > Programs > M.S[Data Science and Artificial Intelligence]

Master of Science [M.S] [Data Science and Artificial Intelligence] From University of Waterloo

Master of Science [M.S] (Data Science and Artificial Intelligence)

Stem course.

This course focuses on Science, Technology, Engineering, or Mathematics subjects, offering a deep dive into these fields to enhance your knowledge and skills in STEM disciplines.

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₽2,762,247 /Yr

• University of Waterloo master of data science and artificial intelligence is offered as a 16 months program
• Master of Data Science and Artificial Intelligence Waterloo program is offered on a full-time basis
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• Master of Data Science and Artificial Intelligence Waterloo is a coursework program with a co-op (only for full-time students) option
• Master of Data Science and Artificial Intelligence Waterloo program provides strong core training so that graduates can adapt easily to changes and new challenges from industry

Click here to know more about Master of Data Science and Artificial Intelligence Waterloo

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The total expenses including tuition and living expenses is around $73,720. 

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Data Science Certificate Course

as anyone taking this course and could provide some feedback? It is a 4 course data science certificate.

https://pd.uwaterloo.ca/DataScienceCertificateDetails.aspx#1

It also requires some basic knowledge of Python, how easy it is to learn on my own?

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Build a strong foundation with the best data science courses to boost your career. You will get a top-notch learning experience with these Popular Data Science Certificate Programs. These programs are in collaboration with world-class universities.

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Get to Know Our Data Science Courses

Introduction to data science courses, top rated data science courses, universities offering data science courses, data science course eligibility, data science course subjects, what is the best data science course for freshers and early career professionals in 2024, ut austin's data science courses offered in partnership with great learning, mit data science courses offered in partnership with great learning, data science course career support.

Data Science uses computer techniques and mathematical methods to make sense of large amounts of data. Data Science courses teach to collect, process, analyze, and interpret data to make better decisions. Data Science skills are in high demand across industries and can help you make a real impact.

With these courses, learners will develop technical skills and soft skills, like problem-solving and critical thinking, essential in any business role. With the insights gained from these courses, businesses can make more informed decisions, leading to improved efficiency and profitability.

The data science courses cover the basics of Statistical Analysis and Machine Learning along with advanced Data Visualization, Data Analytics, and Data Mining. Data science courses are offered by Great Learning in collaboration with the world's leading universities and institutions.

Best Data Science Courses Online for 2024

PGP - Data Science and Business Analytics

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If you’re looking to learn Data Science from the world’s top-ranked universities, you’ve come to the right place. The courses are offered by:  

Massachusetts Institute of Technology  - Institute for Data, Systems, and Society (MIT IDSS)

The University of Texas at Austin (UT Austin) McCombs School of Business

Northwestern University School of Professional Studies

Deakin University

Great Lakes Executive Learning

National University of Singapore Business School

PES University

Walsh College

Eller College of Management

FOM University

With multiple options available, you’re sure to find a course that meets your requirements.

Below are the  eligibility requirements  for a range of data science courses:  

*Please visit the respective program page for detailed information on the eligibility criteria.

Before enrolling, it is usually advised to thoroughly understand the course syllabus, enabling you to determine whether the course equips you with the required skills. The subjects involved in Data Science are as follows:  

For a fresher in 2024, there are several top-notch data science courses offered by Great Learning. They are listed below:  

Data Analytics Course for Beginners  - The University of Texas, Austin (For Non- Indian learners)

PGP in Data Science (Online)  - Great Lakes Executive Learning (For Indian Learners Only)

PGP in Data Science (Bootcamp)  - Great Lakes Executive Learning (For Indian Learners Only)

UT Austin's Data Science Courses Offered in Partnership with Great Learning.

In collaboration with Great Learning, the University of Texas at Austin offers a range of comprehensive online data science certificate courses. These programs are designed for professionals and are tailored to accelerate your professional growth. Depending on the program format, these programs provide a data science certificate online and offline. 

These programs are designed to be flexible and accessible, offering mentored online learning experiences that cater to mid-career professionals. They provide a blend of theoretical knowledge and practical skills, preparing you for the evolving demands of the tech industry.

MIT Data Science Courses Offered in Partnership with Great Learning.

Massachusetts Institute of Technology (MIT), in partnership with Great Learning, offers a variety of in-depth online postgraduate certificate programs specifically designed for professionals seeking to enhance their careers. These programs emphasize key areas in data science and technology, ensuring participants are well-equipped for the dynamic demands of the industry. 

These MIT programs, facilitated through Great Learning, are structured to offer flexibility and convenience, making them ideal for mid-career professionals. The courses blend theoretical insights with practical applications, preparing participants for the rapidly evolving landscape of the data science and technology sectors.

Great Learning offers data science courses with placement opportunities* and career support. You can get access to career fairs, job boards, 1:1 mock interviews with industry experts, career prep sessions, networking sessions, hackathons & live projects that help you land your dream job.

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Data Science Course Placements

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Things You Want To Know About Data Science Courses

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Data Science Course Frequently Asked Questions

What is a data science course.

The Data Science course is a fine blend of mathematics, statistical foundations and tools, and business acumen, all of which assist in extracting from raw data the hidden patterns or insights that can significantly aid in formulating important business decisions. Proving prevalent in academics, Business analytics courses are now an amalgamate of Data Science.

The major components of the course also include scientific computing, data structures and algorithms, data visualization and data analysis, and machine learning tools and techniques to escalate business performance.  The course could be around six to twelve months, designed to give candidates a solid foundation in the discipline. In addition to educational materials, our Data Science certificate courses contain virtual laboratories, interactive quizzes and assignments, case studies, industrial projects, and capstone projects, which will accelerate your learning path.

What are the prerequisites to start a career in Data Science?

Considering this soaring demand in Data Science and Data Analytics, if you want to learn Data Science online, some Data Science prerequisites are as follows:

Mathematical Skills: One must be good at mathematical concepts, such as linear algebra, matrices, calculus, gradients, etc. is considered as one of the major prerequisites for taking up Data Analytics courses.

Programming Skills: Having a concise knowledge of programming, such as Python, C, C++, SQL, Java, etc., would help you gain complete knowledge and understanding throughout the Data Science online course. 

Data Processing: As Data Science is all about dealing with data, an individual must be familiar with data mining, data modeling, data processing, etc., which makes it easy for you to pursue Data Science online training.

Statistical Analysis: Being good with statistical analysis would be a great asset to learn Data Science. Data Science aims to extract valuable insights from a vast collection of data. Experience working with analytical tools such as Hadoop, R, SAS, and many more, will serve you in efficiently performing the statistical analytics of the given data.

Data Visualization Skills: Knowing the data visualization tools such as Matplottlib, Tableau, and many more would benefit you in comprehending the complex outcomes and letting the audience understand the metrics.

Is doing Data Science Course worth it?

Yes, it is entirely worth it to learn Data Science and choose it as your career. Check out the following factors: 

High Demand: Data Science has seen significant growth in various industries. The demand for Data Science jobs is expected to rise steadily in the coming years. According to the U.S. Bureau of Labor Statistics, 11.5 million Data Science jobs might be created by 2026.

Lack of Data Scientists: As Data Science is high in demand, there is a lack of Data Scientists. Several companies are vastly searching for Data Scientists and Analysts. 

Sky-high Pay Scale: A Data Scientist’s average pay scale ranges from USD 15,000 to USD 125,000 (approx.) worldwide.

Adds Value to Business: Data Science has seen significant growth in various industries, such as IT services, healthcare and e-commerce industries, banking sectors, consultancy services, etc

Are there any Data Science courses for working professionals?

Yes, there are Data Science courses designed for working professionals, like senior managers, business leaders, entrepreneurs, etc. They include:

MIT Data Science and Machine Learning - Making Data-Driven Decisions using Data Science and Machine Learning

MS in Data Science - Northwestern University

Data Science and Business Analytics Course - UT Austin

Data Science and Business Analytics Classroom Course - Great Lakes

PG in Data Science Online - Great Lakes

PGP in Data Science - Great Lakes (Bootcamp)

Applied Data Science - MIT (International Program)

Data Analytics Essentials - UT Austin (International Program)

Master of Data Science (Global) - Deakin University

M.Tech in Data Science and Machine Learning - PES University

What is a data scientist's job?

A data scientist's job is to collect, clean, and analyze data to find trends and insights. They use their skills in statistics, programming, and machine learning to build models and algorithms to optimize decision-making. Data scientists also communicate their findings to others through reports and presentations. Data scientists work in multiple industries, including healthcare, finance, technology, and retail. They utilize their skills to solve business problems and help organizations make more informed decisions.

Data scientists typically have a background in computer science, statistics, and mathematics. A data scientist's job is to make sense of data. They use their skills in statistics, computer science, and mathematics to clean, organize, and analyze data. Data scientists also develop algorithms to help make decisions based on data.

What are the career options in data science?

Choosing a job opportunity in data science gives you a lot of career options:

Data Scientist: Responsible for analyzing and interpreting complex data to help inform business decisions.

Data Analyst: Focuses on processing and performing statistical analyses on large datasets.

Machine Learning Engineer: Specializes in designing and implementing machine learning techniques, models and systems.

Data Engineer: Focuses on the preparation of 'big data' for analytical or operational uses.

Business Intelligence (BI) Analyst: Uses data to help organizations make better business decisions.

Data Science Manager/Lead: Ensures meeting organizational goals with various data science teams and projects.

Research Scientist: Engages in data-driven research, often in academic, government, or corporate settings.

Statistician: Applies statistical methods to collect, analyze, and interpret data to solve real-world problems in business, engineering, healthcare, or other fields

Which certificate is best for data science?

There are a variety of data science certificate courses available, each with its own benefits. The best certification for data science depends on your individual goals and needs. If you are looking to strengthen your career or change jobs, a certification from a reputable institution can give you the edge you need. 

The data science certificate course from the University of Texas at Austin McCombs School of Business is an excellent choice for aspirants. World-renowned professionals from UT Austin and Great Learning have designed the curriculum. This certificate program equips you with the relevant knowledge and skills to pursue data science or managerial careers with the best analytics firms or move the analytics roles within your existing organization.

What is the syllabus of data science?

When it comes to learning data science, the common question that usually comes to mind is: what is the syllabus of data science? While there is no one-size-fits-all answer to this question, there are certainly some core topics and skills that all data scientists should know.

In general, the syllabus of data science covers three key areas: statistics, machine learning, and data mining. Each of these areas is essential for any data scientist, as they provide the foundation for understanding and manipulating data. 

A standard syllabus for data science includes:

Statistics and Mathematics

Programming using Python or R

Database Management using SQL

Exploratory Data Analysis

Machine Learning and Artificial Intelligence

Time Series Forecasting

Data Mining

Business Analytics

Data Visualization using Tableau or Power BI

No matter your experience in data science, if you want to be a data scientist, it is critical to have a strong foundation in these core areas. With this foundation, you will be able to tackle any data science challenge that comes your way.

What is the salary of a data scientist fresher across the world?

With the increase in the demand for data scientists across the globe, salaries are also skyrocketing. Data scientists are making generous pay from top-notch companies. Since there is a lack of data science professionals in the field, even freshers are earning excellent salaries.

The following are a few salaries of a data scientist fresher from different countries:

Data scientist salary in the United States : USD 101K per annum

Data scientist salary in the United Kingdom : £55K per annum

Data scientist salary in India : ₹10.5 Lakh per annum

Data scientist salary in Germany : €55K per annum

Data scientist salary in Australia : AU$121K per annum

Is data science a good career option?

Data science is an excellent career choice for those with strong analytical and problem-solving skills. The field is projected to proliferate in the coming years, and data scientists are in high demand. 

Data science is a versatile field, and data scientists can work in a variety of industries, including healthcare, finance, government, and tech. Salaries for data scientists are also very competitive and among the highest salaries offered in any profession. 

The demand for data scientists is increasing as businesses become more reliant on data to make data-driven business decisions. Data science is a relatively new subject, and there is a lot of opportunity for growth and advancement.

Which is the best institute for Data Science training?

There is no one-size-fits-all answer to this question, as the best institute for Data Science training will vary depending on your specific needs and goals. Nevertheless, some factors to consider when choosing a Data Science training institute include the institute's reputation, curriculum, and instructors. It is also vital to ensure that the institute you choose offers an accredited Data Science program that will help you become a certified data scientist.

Here is a list of a few top-notch institutes for Data Science training:

Massachusetts Institute of Technology - Institute for Data, Systems, and Society (MIT IDSS)

Shiv Nadar University, Delhi NCR

How do I get certified in Data Science?

After you successfully pass all the assignments, exams, or projects, your course will be completed. Then, you will receive a Data Science professional or degree certificate from respective institutes or universities. 

Should I go for a data science certification or degree?

Deciding between a data science certification course and a data science degree course depends on your qualifications, career goals, and the time and resources you can commit. A degree in data science typically offers an in-depth skill set, and it's well-suited for those who are early in their career. The ones who are looking to gain a strong foundation in data science can also consider a data science online degree.

On the other hand, data science professional certificates are more focused and flexible. It allows learners to specialize in specific areas of data science. They are ideal for professionals seeking to update their skills or pivot to a data science career without committing to a full-time degree program.

What is the demand for data science jobs in 2024?

The demand for data science jobs is extremely high, and data is considered the new oil in today's digital economy. Companies across industries are seeking professionals who can interpret and analyze this data to provide business insights. Therefore, the demand for data science skills, including machine learning, predictive analytics, and data visualization, is rising significantly.

What are the benefits of a data science boot camp?

A data science boot camp offers several benefits, such as:

Providing a fast-paced, intensive learning environment that helps you gain data science skills in a relatively short period

Focusing on practical, hands-on learning with real-world projects

Providing mentorship from industry experts and career support, helping you transition into a data science role more smoothly

What is the future scope for data scientists?

The future scope for data scientists is promising. With the advent of AI and machine learning, companies in various sectors, such as healthcare, finance, retail, and e-commerce, are increasingly leveraging data to make informed business decisions, resulting in a growing demand for data scientists. 

As per the U.S. Bureau of Labor Statistics, the future for data scientists is highly promising, with a 35% growth in employment from 2022 to 2032, which is higher than all the other occupations.

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Best Online Master’s in Data Science Programs for 2024

Exponential growth in data has translated into a demand for data scientists that outpaces how fast universities can train them. But what are the best options if you’re looking to break into data science and don’t have time for in-person classes? To answer that question, Fortune built our second ranking of online data science graduate programs. This ranking was last updated January 2023.

Berkeley’s Data Science Master’s

Johns Hopkins Engineering for Professionals Online MSE in Data Science

1. University of Southern California

• ACCEPTANCE RATE
• AVERAGE NUMBER OF YEARS OF WORK EXPERIENCE
• COST PER CREDIT
• GRE REQUIRED

2. University of California—Berkeley

3. Bay Path University

Learn Applied Data Science from UNC-Chapel Hill

4. New Jersey Institute of Technology

5. Clemson University

6. Illinois Institute of Technology

7. Oklahoma State University

8. Texas Tech University

Maryville University Master of Science in Data Science | Online

9. University of Missouri—Columbia

10. University of California–Los Angeles

11. DePaul University

12. University of California–Riverside

13. Worcester Polytechnic Institute

Syracuse University MS in Applied Data Science Online

14. Lewis University

15. University of Illinois at Urbana—Champaign

16. CUNY School of Professional Studies

17. University of Michigan–Dearborn

18. Regis University

19. Rice University

20. Eastern University

21. Syracuse University

22. Stevens Institute of Technology

23. pace university.

What is a master’s in data science and what will you learn in an online program?

Pursuing a master’s degree in the fast-growing field of data science can help you to advance your career in a wide variety of tech-related roles. Expect to learn a broad set of skills, including how to use computer programming languages and about applied statistics, database systems, and machine learning. The skills and concepts you learn in a master’s degree program will prepare you for a career in data science to help organizations make strategic decisions based on the data they collect. There’s no significant difference between online and on-campus data science programs—schools typically offer the same courses that are taught by the same professors, regardless of the format. 

General curriculum and skills taught

You can expect a comprehensive curriculum in an online master’s degree program in data science that draws on both statistical and computational methods. Programs will emphasize the real-world application of these knowledge and skills, while offering a multidisciplinary approach to the field that also draws on statistics, computer science, and law. Data science is about more than numbers, however; you will also learn “soft skills” about how to effectively communicate the lessons learned and collaborate with others to learn how to best utilize information in an ethical way . Core coursework at many data science programs covers the following topics:

• Machine learning
• Data mining
• Data visualization
• Cloud computing
• Research design
• Information ethics
• Statistical analysis
• Data engineering

Project-based learning

Beyond the core and advanced-level coursework that are common among all data science programs, some schools also offer mandatory or optional project-based learning opportunities. These projects focus on the real-world application of the skills learned in the program, and can be an opportunity for students to display the skills learned during a program to potential employers. The master’s degree programs at both the University of California-Berkeley and Bay Path University , for example, both include a culminating capstone project that draws upon the skills learned throughout the course of the program. Such projects may extend the length of a master’s degree program, however. 

Specializations and concentrations

While the core coursework required for completing a master’s degree in data science is intentionally comprehensive, many programs offer specializations or concentrations so students can carve out a niche within this field. The University of Illinois at Urbana-Champaign offers advanced coursework in cloud computing and scientific visualization, while Texas Tech University has advanced coursework in multivariate analysis and project management. Concentration options may include:

• Business analytics
• Artificial intelligence

Admissions information

While admissions requirements can vary by school, graduate degree programs require the following of aspiring data scientists :

• Successful completion of a bachelor’s degree, as demonstrated by an official transcript from a college or university
• If you don’t have an undergraduate degree in a data-related field (like computer science), you may need to demonstrate that you have sufficient work and educational experience in fundamental concepts on your résumé
• You may also use your personal statement or essay to highlight your unique characteristics and goal for the program
• Letters of recommendation from supervisors, professors or alumni of the program
• Many top-ranked data science programs no longer require you to submit GMAT or GRE scores, though you may need to if you don’t meet minimum undergraduate GPA requirements
• Some master’s degree programs in data science, like the University of Illinois Urbana-Champaign, may require applicants to complete a data proficiency exam

GMAT, GRE & GPA

A majority of online master’s degree programs in data science have waived GRE or GMAT score requirements and, in fact, only two schools on Fortune’s ranking still require applicants to submit scores as part of that application process. That said, you may submit this information particularly if you want to provide additional supporting information that’s helpful in the admissions process. Moreover, GPA requirements also vary by school and may be waived with sufficient work experience.

Which factors drive acceptance?

While admissions officers strive to take a holistic approach when evaluating candidates, they will be particularly interested in your educational background and work experience in a data-related field. Applicants to some data science programs, like the University of Wisconsin-Madison and the University of Connecticut , must show they’ve completed particular quantitative college-level coursework, while other programs like Syracuse University place a greater emphasis on the personal essay and what applicants emphasize they’re looking for in the program, why they chose it, and what their goals are.

The online master’s in data science experience: What is it like to study online?

Online learning has been growing in popularity in recent years, and students considering a master’s degree program in data science can often choose between an in-person or online option within the same school. Data science programs may offer a mix of both synchronous and asynchronous learning, meaning courses that either need to be attended live at a particular time or at the student’s convenience, and could include some limited in-person elements.

For the most part, students can expect to participate in class discussions via video conferencing or using other technology. And because of the online format, many students who pursue a master’s degree in data science are working while attending school with a goal of either switching careers or advancing their current career in data science.

How to choose the best online master’s degree program in data science for you: Factors to consider beyond rankings

Fortune’s ranking of online master’s degree programs in data science is a good starting place when comparing various programs. We emphasize selectivity (schools with top-notch faculty that attract some of the brightest students) and demand (based on the size of the student body), since the people you meet in graduate school could be transformative to your future career.

That said, prospective students should also consider how a particular program will help you achieve your goals and advance in the field of data science. Other factors that may be important include cost, a school’s prestige, its curriculum, and the years of work experience schools may require of applicants.

Start times, schedule, and program length

As data science programs have grown in popularity, schools have beefed up the number of start dates they offer. The University of Illinois and UC Berkeley, the No. 1 and No. 2 ranked programs, both offer three start dates throughout the year. Students may have some flexibility in choosing their schedule and how long it takes to complete the program of their choice, though two years is common.

As indicated, some data science programs include project-based learning opportunities that focus on the real-world application of skills taught in the program. Because these projects can be useful to show potential employers, career switchers may want to consider prioritizing schools with project-based learning opportunities—even if they could extend the program’s length.

Concentrations

As you think about your career goals post-graduation, you should also consider the concentrations offered by various data science programs. By carving out a specialty within data science, that may make you a more attractive job candidate for some employers—and it could increase your earning potential. People with the title of “data scientist” can earn up to $170,000, while manager-level professionals in the field could fetch salaries of as much as $250,000. 

The cost of a data science program is undoubtedly a factor to consider when applying to school—and tuition varies widely. Students may be able to pay one-year tuition of about $20,000 (or less) at schools like the University of Illinois Urbana-Champaign, Loyola University Maryland, the University of Missouri-Columbia, and CUNY School of Professional Studies. That said, the cost of tuition exceeds $50,000 at UC Berkeley, Syracuse University, and the University of Denver.

Network and access to alumni

The more students a data science program has, the larger its alumni network. This is important to consider during your selection process, not only because your cohort can be a defining characteristic of your grad school experience even if you’re attending classes online. What’s more, the network and a school’s ability to connect you with alumni may help you when looking for jobs—and particularly if you’re not already working in the field.

Years of work experience

Because many data science programs are seeking out applicants who already have relevant work experience, it may be useful to see how your experience compares. What’s more, the amount of work experience will inherently influence how advanced your fellow students are in their careers. Worcester Polytechnic Institute reports that students have an average of 8 years of work experience, while roughly half of the master’s degree students in New York University’s program enroll straight out of undergrad.

Careers for master’s in data science graduates

There’s a hot job market for data scientists thanks to robust demand—and that means many graduates of master’s degree programs are fielding multiple, six-digit salary offers. Big tech companies are a likely career path for many data scientists. A survey of more than 11,000 data scientists found that the companies with the largest teams of data scientists are Microsoft, Facebook, and IBM. And Apple, for example, pays as much as $182,000 for data scientists.

Financing and scholarships

If your goal of obtaining a master’s degree in data science is to advance within your current company, then your employer may help pay for the cost of the program. New York University grants tuition scholarships to some master’s degree students, while UC Berkeley offers several fellowships of varying amounts. 

You may also want to seek out a growing number of scholarship or fellowship opportunities from private organizations. Some examples that are available to master’s degree students include:

• The Association of Computing Machinery (ACM) awards computational and data science fellowships to diverse candidates with a $15,000 annual stipend. 
• Acxiom awards $5,000 scholarships to U.S.-based students from diverse backgrounds who are enrolled full-time in various programs that include data science.
• Although it doesn’t specify the amount, the American Statistical Association (ASA) offers a pride scholarship to students enrolled in a data science graduate program and identify as LGBTQ+ or an ally.

Finally, current members of the military or veterans may want to consider covering the cost of your data science program with Post-9/11 GI Bill benefits or the Yellow Ribbon Program , which can cover any tuition and fees not covered by those benefits.

Frequently Asked Questions

While still relatively new, data science is a field that incorporates preparing and analyzing data to draw conclusions. Data scientists design and build new processes for data modeling by using algorithms, prototypes, predictive models, and custom analysis. People should pursue data science if they’re interested in asking questions and creating algorithms and statistical models to estimate the unknown. 

All of the data in the world is projected to grow to a staggering 181 zettabytes by 2025. And this growth has translated into high demand for data scientists—even outpacing the speed with which colleges and universities can train them. Data scientist ranks No. 3 among the 50 best occupations in the U.S., according to Glassdoor’s list of the best jobs for 2022 , and was beat out only by the roles of enterprise architect and full stack engineer.

Some people may choose to follow a step-by-step guide to become a data scientist. First, you may want to pursue an undergraduate degree that focuses on technical skills like programming or statistics. Then, you should identify an area of specialization and hone this specialization by enrolling in a master’s degree program in data science. Finally, you should showcase your data science experience when applying for jobs.

In addition to high demand, people with a master’s degree in data science can expect to enter a rapidly-growing field with solid salary prospects. Through 2026, the U.S. Bureau of Labor Statistics (BLS) projects data science jobs will grow by 28% per year . Even before graduation, some data science students in master’s degree programs are fielding offers of $125,000 and up .

As with any career, pay prospects can vary by company and role. Data scientists made a median salary of $164,500 in 2020, according to a 2021 survey of engineering professionals by the Institute of Electrical and Electronics Engineers (IEEE).

The median base salary for data scientists is $120,000, according to figures from Glassdoor, though the likely range for positions goes as high as $294,000. Some tech companies are even paying in excess of $300,000 for senior-level data scientist roles.

The sky’s the limit for job opportunities for data scientists, including careers in tech, entertainment, pharmaceuticals, telecom, sports, consulting, or even as a company executive who understands data. What’s more, new job titles are likely to be created, particularly related to ethical concerns with sensitive data and as companies look for new ways to utilize their massive data sets and emerging technologies such as cloud computing, A.I., and machine learning.

In 2012, Harvard Business Review called the role of a data scientist “ the sexiest job of the 21st century .” Ten years later, data science remains a good career field for many people thanks to the wide range of jobs available now and in the future, along with robust demand and six-figure salary prospects.

The class of 2022 from master’s degree programs in data science were fielding job offers, with competitive salaries, months ahead of graduation. Demand for data scientists is growing faster than colleges and universities can train them. Even so, job applicants should still expect a rigorous interview process that often entails showcasing examples of work or a commitment to staying up-to-date in a rapidly changing industry.