- Introduction
- Most Affordable Programs
- Best Programs
- Program Details
- Admission Requirements
- No GRE
- Accreditations for Online Master’s in Data Science Degrees
- Where to Find Free Online Courses for Data Science Master’s Students
- How To Pay?
- Career Opportunities and Salaries
- Certifications and Licensing
- More Resources
- FAQs
Edited By Darryl S.
Review & Contribution By Brian Bliss
The rise of computers and digital businesses has revolutionized the world. However, to keep up with advancing technologies, businesses continually need skilled workers with backgrounds in data science. With an online master’s in data science, individuals set themselves up to enter a lucrative, fast-growing field. Computer and information research scientists, a common landing spot for those with a master’s in data science, make an annual median wage of $136,620, according to the Bureau of Labor Statistics (BLS)[29]. The BLS also projects a 23% growth rate for computer and information research scientists from 2022 to 2032, much faster than the average growth rate for all jobs.
Table Of Contents
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Southern New Hampshire University
PROGRAM: Best & Affordable Online Master’s in Data Analytics
Southern New Hampshire University is a private, nonprofit, accredited institution with more than 3,000 on-campus students and over 60,000 online students, making us one of the fastest-growing universities in the country. Founded in 1932, we’ve been relentlessly reinventing higher education ever since and have gained national recognition for our dedication to helping students transform their lives and the lives of those around them.
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20 Most Affordable Online Data Science Master’s Programs
Earning a graduate degree does not have to be expensive. Affordable online data science programs teach the same skills and methods as more expensive in-person programs, only at a lower cost to the learner. Considering these and other criteria following a unique methodology, the OMC team has compiled a list of top-notch affordable online master’s degree programs in data science:
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| College Name & Address | Tuition | Graduation Rate |
|---|---|---|
| #1 Middle Georgia State University 100 University Parkway, Macon, Georgia 31206 | $3,582 | 18% |
| #2 Southern Arkansas University 100 E. University, Magnolia, Arkansas 71753 | $5,040 | 41% |
| #3 Texas Tech University Broadway and University Avenue, Lubbock, Texas 79409 | $5,958 | 60% |
| #4 Cabrini University 610 King of Prussia Rd, Radnor, Pennsylvania 19087 | $5,985 | 57% |
| #5 Arizona State University 1475 N Scottsdale Rd, Scottsdale, Arizona 85257 | $6,384 | 48% |
| #6 University of Oklahoma,Norman 660 Parrington Oval, Norman, Oklahoma 73019 | $6,583 | 67% |
| #7 Texas A&M University, College Station JKW Administration Building, Suite 200, College Station, Texas 77843 | $6,677 | 82% |
| #8 The University of West Florida 11000 University Parkway, Pensacola, Florida 32514 | $7,088 | 43% |
| #9 Western Governors University 4001 South 700 East Suite 700, Salt Lake City, Utah 84107 | $7,500 | 29% |
| #10 Charleston Southern University 9200 University Blvd, Charleston, South Carolina 29406 | $7,500 | 42% |
| #11 University of Wisconsin, Green Bay 2420 Nicolet Dr, Green Bay, Wisconsin 54311 | $7,996 | 52% |
| #12 University of Illinois, Springfield One University Plaza, Springfield, Illinois 62703 | $8,270 | 51% |
| #13 University of Maryland Global Campus 3501 University Blvd East, Adelphi, Maryland 20783 | $8,640 | 15% |
| #14 University of Missouri, Columbia 105 Jesse Hall, Columbia, Missouri 65211 | $9,264 | 69% |
| #15 Indiana University, Bloomington 07 South Indiana Ave., Bloomington, Indiana 47405 | $9,501 | 78% |
| #16 University of Kansas Strong Hall, 1450 Jayhawk Blvd, Room 230, Lawrence, Kansas 66045 | $9,989 | 65% |
| #17 Notre Dame of Maryland University 4701 N Charles St, Baltimore, Maryland 21210 | $10,345 | 53% |
| #18 Colorado State University 102 Administration Building, Fort Collins, Colorado 80523 | $10,520 | 71% |
| #19 University of North Dakota 264 Centennial Drive, Stop 8193, Grand Forks, North Dakota 58202 | $10,534 | 55% |
| #20 Georgia Institute of Technology 225 North Ave, Atlanta, Georgia 30332 | $14,064 | 87% |
Source – Integrated Post Secondary Education Data System & University Data
*Tuition rates are for in-state and per year. Program specific rates may apply.
**NA – data not available
Top 20 Online Data Science Master’s Programs
The best online master’s in data science programs prepare graduates for successful careers, often offering some of the best outcomes in the industry. We rank the best online data science programs based on these outcomes and other factors, including tuition rates, curriculum, accreditation, and reputation.
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| College Name & Address | Tuition | Graduation Rate |
|---|---|---|
| #1 University of Virginia 1827 University Avenue, Charlottesville, Virginia 22903 | $16,578 | 94% |
| #2 University of Southern California University Park, Los Angeles, California 90089 | $46,272 | 92% |
| #3 University of California, Berkley 200 California Hall, Berkeley, California 94720 | $11,442 | 91% |
| #4 University of Michigan, Ann Arbor Business College Complex 632 Bogue St East Lansing, MI 48824 | $23,890 | 92% |
| #5 Brandeis University 415 South St, Waltham, Massachusetts 02454 | $51,940 | 88% |
| #6 Columbia University West 116 St and Broadway, New York, New York 10027 | $47,600 | 96% |
| #7 Northeastern University 360 Huntington Ave, Boston, Massachusetts 02115 | $24,793 | 88% |
| #8 Georgia Institute of Technology 25 North Ave, Atlanta, Georgia 30332 | $14,064 | 87% |
| #9 Carnegie Mellon University 5000 Forbes Avenue, Pittsburgh, Pennsylvania 15213 | $45,037 | 89% |
| #10 Stevens Institute of Technology Castle Point On Hudson, Hoboken, New Jersey 07030 | $36,680 | 87% |
| #11 Worcester Polytechnic Institute 100 Institute Road, Worcester, Massachusetts 01609 | $28,188 | 87% |
| #12 George Mason University 4400 University Dr, Fairfax, Virginia 22030 | $12,144 | 70% |
| #13 University of Maryland, College Park College Park, Maryland 20742 | $13,158 | 86% |
| #14 Texas Tech University Broadway and University Avenue, Lubbock, Texas 79409 | $5,958 | 60% |
| #15 Arizona State University 1475 N Scottsdale Rd, Scottsdale, Arizona 85257 | $6,384 | 48% |
| #16 University of Illinois Urbana, Champaign 601 E John Street, Champaign, Illinois 61820 | $14,997 | 84% |
| #17 Colorado State University 102 Administration Building, Fort Collins, Colorado 80523 | $10,520 | 71% |
| #18 DePaul University 1 E Jackson Blvd, Chicago, Illinois 60604 | $19,584 | 72% |
| #19 Clarkson University 8 Clarkson Ave, Potsdam, New York 13699 | $33,312 | 75% |
| #20 Rutgers University 249 University Avenue, Blumenthal Hall, Newark, New Jersey | $17,736 | 64% |
Source – Integrated Post Secondary Education Data System & University Data
*Tuition rates are for in-state and per year. Program specific rates may apply.
**NA – data not available
Understanding an Online Data Science Master’s Program
In an online master’s in data science program, students learn to communicate computer science concepts and information, create and manage new strategies, compile analytics at an advanced level, and lead teams to meet organizational goals. Most students have professional backgrounds in data science and want to advance their careers.
Curriculum for an Online Master of Data Science Program
While specific core and elective courses vary by program, many offer the following courses, sometimes with slightly different course titles and subject matter:
Database Systems and Data Preparation: This course introduces the fundamentals of database systems and data preparation, including relational database systems, relational modeling, and structured query language. Most programs require this course early on to introduce more complicated topics later.
Practical Machine Learning: Practical machine learning introduces machine learning techniques, resampling techniques, and various methods of grouping and analyzing data. Some programs include the use of open-source software, a common practice for data science.
Statistics for Data Science: A necessary course for data scientists, statistics for data science teaches various quantitative research methods for analyzing data. This course combines traditional statistics material with large data sets.
Computer Vision: As an elective course, computer vision teaches a specialized deep learning method through images, including creating digital representations of x-rays, sensor images, and hand-written documents.
Capstone Project: Many master’s in data science programs end with a capstone project. The capstone project usually groups students to teach leadership and communication skills while providing graduates real-world experience.
Apart from career advancement and increased pay, pursuing a master’s in data science equips students with the skills to make intelligent and informed decisions and analyze critical issues within the field. These skills become invaluable in one’s career or entrepreneurial endeavors. The program empowers professionals to build businesses and tackle various challenges, fostering growth. Upon completing a master’s in data science, students can expect to gain the following skills and learning outcomes:
- Apply analytical and critical thinking skills to resolve various issues in the field of data analytics.
- Employ effective communication methods to collaborate with diverse stakeholders in data science, conduct analyses, and develop models in the field.
- Demonstrate professional and ethical behavior while committing to continuous learning and improvement.
- Utilize theoretical knowledge to address real-world problems, collect and process data, and design optimal problem-solving and solution implementation methods.
- Showcase proficiency in programming skills, computational methods, principles of software systems, and key concepts of data science.
- Manage data to generate valuable predictions and gather analyzed data for making insightful and strategic decisions.
- Exhibit divergent thinking skills and a grasp of fundamental principles in data science.
- Integrate data science theories to extract meaningful information and identify new opportunities for organizations and individuals.
Types of Master’s Degrees Online Data Science Students Can Obtain
Many Universities in the United States provide various online master’s in data science degree programs, including the online Master of Arts (MA) in data science, the online Master of Science (MS) in data science, and the Master in Interdisciplinary Data Science (MIDS).
Master of Arts in Data Science
The Master of Arts in Data Science, or MA Data Science online, focuses on developing skills in data science for exploring, managing, analyzing, and visualizing large datasets through advanced technologies. Students engage in courses that integrate diverse academic disciplines such as mathematics, computer science, and statistics, enabling them to address complex challenges and acquire the ability to identify patterns and trends within datasets.
Master of Science in Data Science
The Master of Science in Data Science, also known as MS Data Science, encourages students to concentrate on advancing various research areas within the field. Students navigate a demanding and inventive curriculum by engaging in research endeavors, completing capstone projects, and collaborating with industry leaders. In essence, the MS degree adopts a more technical and scientific approach than an MA degree.
Master in Interdisciplinary Data Science
The Master in Interdisciplinary Data Science (MIDS) program integrates technical and computational training with domain-specific knowledge. Students develop critical thinking skills, communication abilities, collaboration expertise, leadership qualities, and teamwork proficiency to maximize their potential and contribute value to their respective fields. The program features an interdisciplinary syllabus comprising a well-balanced mix of core courses and electives, emphasizing practical, real-world experience in the field.
Common Specializations for an Online Master’s in Data Science
As a specialized field, many master’s in data science programs do not offer specializations. However, students can focus their education through elective courses, studying topics related to their desired role within data science.
| Area of Focus | Description | Careers This Concentration Prepares For |
|---|---|---|
| Big Data | Big Data, also called Big Data Systems, teaches students to design, implement, and interpret complex data sets and adjust systems based on analytics. | Data scientist, data architect, database administrator, data engineer, software development engineer |
| Big Data Analytics | Like Big Data, Big Data Analytics emphasizes analyzing existing data sets for valuable insights. This focus also emphasizes decision-making and leadership. | Data scientist, database manager, data analytics, data engineer, computer systems analyst |
| Data Analytics | A fast-growing field for all industries, a focus on data analytics teaches data science students to gather useful data through cutting-edge tools, compile the data, and then develop new business strategies based on analytics. | Data scientist, data analytics, operations analyst, database architect, database manager |
| Data Mining | Similar to data analytics, data mining works closely with large data sets. Data miners learn to use a combination of statistics and machine learning to discover patterns in large data sets and then advise future action based on the data. | Data scientist, data analyst, data engineer, database manager, business intelligence analyst |
| Machine Learning | A machine learning focus teaches students to model large data sets and process unstructured data sets for information, all with the assistance of artificial intelligence. | Machine learning engineer, business intelligence analyst, data scientist, database manager, computer system analyst |
| Predictive Analysis | Predictive analytics uses data sets to try and predict future trends. Students learn methods including machine learning, predictive modeling, and data mining. | Data analysis, data scientist, business operations specialist, database manager, chief data officer |
Online Master in Data Science Program Length
Most master’s in data science programs take 30-36 credits and 1-1.5 years to complete, though numerous factors influence program length. Factors include:
- Online vs. On-Campus: Online students have more flexibility than on-campus students and complete courses at their own pace. Some online students graduate faster than on-campus students.
- Part-time vs. Full-time: Part-time students take roughly 2-3 years to complete a master’s degree, though part-time students can continue working while studying.
- Transfer Credits: Students with certifications, significant work experience, or previous graduate school experience could earn transfer credits, immediately reducing the length and cost of the master’s degree.
Accelerated Data Science Programs
Accelerated master’s programs in Data Science provide an efficient pathway for students to complete their degree in a shorter duration. These programs are tailored to enable motivated and dedicated students to expedite their studies and graduate sooner. To expedite their program, students may undertake an increased course load, including summer or intensive courses, to expedite their program, thereby accelerating their progress. They might also be able to transfer credits from previous coursework or relevant professional experiences, reducing the overall time needed to earn the degree. It is crucial for students contemplating an accelerated program to thoroughly evaluate their preparedness and ability to manage an accelerated pace of study. Here are examples of colleges that offer accelerated online master’s programs in Data Science:
Online Data Science Master’s Admission Requirements
Admissions into master’s in data science programs are competitive, so applicants should do what they can to improve their applications, including going beyond these admission requirements. The typical admissions requirements for an online master’s in data science include:
- Bachelor’s Degree: Regardless of experience, all applicants must hold a bachelor’s degree from a regionally accredited institution. Most programs prefer candidates with a bachelor’s in computer science or a related field and a 3.0 GPA or higher.
- Experience: Many programs do not explicitly state experience requirements, though all master’s in data science degrees require students to demonstrate proficiency in programming languages. Students with 2-3 years of relevant professional experience might receive preference.
- GRE Scores: While not required for all master’s in data science programs, strong GRE scores boost applications. Students with lower GPA scores on transcripts should consider taking the GRE.
- Professional Resume: Applicants’ professional resumes include previous education, work experience, and other useful information. A strong resume demonstrates a background and interest in data science.
- Statement of Purpose: Competitive graduate programs only select applicants interested in data science. The statement of purpose is an applicant’s chance to prove why they’re a good candidate for the program.
No GRE Online Data Science Master’s Programs
The GRE (Graduate Record Examination) and GMAT (Graduate Management Admission Test) are commonly utilized standardized tests for admission to graduate programs. While many U.S. schools typically mandate these test scores, some online master’s programs in data science may not impose a GRE or GMAT requirement. The decision to waive the GRE/GMAT requirement acknowledges that standardized test scores may not always accurately reflect an applicant’s potential success in the program. Instead, universities may give weight to other factors such as academic background, research experience, statement of purpose, letters of recommendation, and personal interviews to evaluate applicants’ qualifications. Individuals interested in pursuing an online master’s in data science should contact the data science departments of their chosen universities to inquire about programs that do not necessitate GRE scores or explore options for obtaining a GRE waiver. Some institutions that provide online data science master’s no gre include:
Accreditations for Online Data Science Master’s Degrees
The accreditation obtained by institutions guarantees that their program aligns with the quality standards established by the engineering profession. This accreditation involves regular evaluations and is a testament to the school’s dedication to delivering high-quality programs. Programmatic accreditation for online master’s in data science programs can be granted by the Data Science Council of America 7. In cases where this specific accreditation is not present, students should seek college accreditation, typically conferred by six regional accrediting bodies, namely:
- New England Association of Schools and Colleges (NEASC)8
- Middle States Association of Colleges and Secondary Schools (MSA-CESS)9
- Higher Learning Commission (HLC)10
- Southern Association of Colleges and Schools Commission on Colleges (SACSCOC)11
- Northwest Commission on Colleges and Universities (NWCCU)12
- Western Association of Schools and Colleges (WASC) Senior College and University Commission (WSCUC)13
Where to Find Free Online Courses for Data Science Master’s Students
Graduate students continue to seek affordable college options, and it’s worth noting that some programs come at no cost. While fully accredited free master’s programs are not available, some options permit students to access lectures from previous sessions and take free courses from reputable institutions. While participants won’t receive a master’s diploma from these courses, the learning experience is on par with that of master’s students. All of these opportunities are available for free and entirely online. Explore the following courses:
| Course | Advanced Diploma in Data Science with R 14 |
| Provided by | Alison |
| Description | In this free course, students will explore crucial concepts and key factors in data science with R. They will uncover how data science supports businesses in making objective and influential decisions. Proficiency in applying real-world applications of data accumulated across various business sectors will be developed, enabling students to leverage this knowledge for clients or employers. The course provides hands-on experience in uncovering patterns from raw data and offers insights into the diverse career opportunities available in the field of data science. |
| Course | Data Science and Agile Systems for Product Management 15 |
| Provided by | Class Central |
| Description | In this course, students learn that modern systems must prioritize agility for competitive advantage. Once exclusive to tech companies, Agile, DevOps, and Data Science are now essential for all industries. Modern product management requires Lean and DevOps principles, emphasizing self-service, automation, and a robust Agile development process for noticeable improvements. In a DevOps environment, products are designed with modularity, open-set architectures, and flexible data management. The course covers paradigms, processes, and key technologies to make a data-driven product organization the optimal competitor in the market. |
| Course | Data Science-Working with Data 16 |
| Provided by | Alison |
| Description | In this course, students discover the process of acquiring the necessary information for a project and assessing the relevance of various data sets. The course examines Python and ‘R’ programming languages in Azure Machine Learning (Azure ML) and guides participants through the data and machine learning lifecycle. Integrating research methodology and programming is employed to impart knowledge in the field of data science. |
How to Pay for Online Data Science Master’s Programs
Tuition remains a hurdle for incoming students. Fortunately, master’s in data science students have many ways to reduce tuition costs beyond the FAFSA, such as:
A scholarship is a form of funding for students to apply for in terms of merit. It is provided based on one’s educational qualification and other merits like sports, music, etc., and need not be paid back.
Students can be given grants by organizations like educational institutions, non-profit institutions, and state and federal governments. Unlike scholarships, they can be awarded based on needs and not necessarily on merit.
Graduate Assistantships involve part-time roles within academic institutions, offering financial support, tuition waivers, and stipends. Graduate students contribute to research, teaching, or administrative tasks, gaining valuable experience while easing the financial burden of their education.
Internships
Fellowships, such as the Data Incubator Fellowship Program17, submerse students in multi-week programs and pay students for their work. Fellowships also help graduates form professional connections and gain experience.
Student Loans
The remaining degree costs can be paid down through financial aid. Financial aid includes scholarships, grants, and student loans. Contact schools and programs to learn more about specific financial aid opportunities available.
Read the Financial Aid Guide for more information on funding higher education.
Scholarships for Online Master’s in Data Science Students
One of the best ways to help finance education is through scholarships. Some scholarships are only available to master’s in data science students, and some require students to begin a program before applying, so keep checking for opportunities.
Great Minds in STEM Scholarship 18
The Great Minds in STEM (GMiS) Scholarship supports students pursuing health-related or STEM disciplines at accredited 2-year or 4-year colleges in the United States. This scholarship aims to empower and advance the next generation of leaders in science, technology, engineering, and mathematics.
Award/Amount: $500- $5000
Deadline: Varies
All students pursuing a career in data science or a relevant field may apply for this award. Applicants submit a themed essay and include their cover letter.
Award/Amount: $1,000
Deadline: Varies
ACM SIGHPC Computational and Data Science Fellowships 20
ACM SIGHPC has established the Computational and Data Science Fellowships, an extension of the program initiated with Intel (refer to below) to enhance diversity among students pursuing graduate degrees in data science and computational science. This program specifically targets women and students from underrepresented racial/ethnic backgrounds in the computing field, welcoming applicants from institutions globally.
Award/Amount: $15,000 up to 2 years
Deadline: April annually
Careers and Salary Outlook for Masters in Data Science Graduates
Students who graduate with an online master’s degree in data science can expect diverse career opportunities with varied titles and benefits. Although a degree does not ensure automatic job placement or a fixed salary, here are several common career paths that graduates might explore in the field, along with specific details about these professions:
| Occupation | Economists 21 |
| Median Annual Salary | $113.940 |
| Job Growth (up to 2032) | 6% (faster than average) |
| Job Description | Economists examine and gather data, assess economic issues, and analyze research trends related to resources, services, and goods. They operate autonomously or engage in collaboration with fellow statisticians and economists. |
| Occupation | Data Scientists 22 |
| Median Annual Salary | $103,500 |
| Job Growth (up to 2032) | 35% (much faster than average) |
| Job Description | Data scientists utilize statistical methods to interpret and analyze digital data, contributing to businesses’ decision-making processes. Employing various tools, they extract meaningful insights from data and apply algorithms and machine-learning techniques to categorize information. |
| Occupation | Computer and Information Research Scientists 23 |
| Median Annual Salary | $136,620 |
| Job Growth (up to 2032) | 23% (much faster than average) |
| Job Description | Computer and information research scientists employ inventive designs to leverage existing and emerging computing technologies, addressing intricate computing challenges. They pioneer the development of new computing languages, methodologies, and tools to enhance people’s interactions with computers. |
| Occupation | Data Science Manager 24 |
| Median Annual Salary | $155,245 |
| Job Growth (up to 2032) | No data Available |
| Job Description | Data Science Managers lead teams responsible for identifying trends, patterns, and anomalies within large datasets, extracting insights through thorough data analysis. They supervise interpreting results from diverse sources, employing techniques from simple data aggregation to sophisticated data mining. They direct the design and implementation of Big Data Solutions for the organization. |
Certifications and Licensing for Online Master’s Students in Data Science
Professional certifications provide students with qualifications showcasing their ability to deliver quality services and uphold high standards of professionalism. Such certifications enhance employment prospects, potentially leading to higher remuneration. They serve as evidence to employers and the industry that an individual is an expert in a specific area of data science. Online master’s data science students can pursue certifications from diverse professional organizations. Examples include:
Certification of Professional Achievement in Data Sciences 25
The Certification of Professional Achievement in Data Sciences is a non-degree initiative designed to cultivate proficiency in fundamental data science skills. Comprising four courses—Algorithms for Data Science, Probability and Statistics, Machine Learning for Data Science, and Exploratory Data Analysis and Visualization—the program aims to impart essential knowledge in the field.
Data Science Council of America Senior Data Scientist 26
This certification suits students seeking exposure to research and analytics and preparing for roles as data scientists in large institutions. The evaluation covers proficiency in spreadsheets, statistical analysis, relational database management systems (RDBMS), and databases.
IBM Data Science Professional Certificate 27
The IBM Data Science Professional Certificate is an entry-level certification showcasing proficiency in various data science areas, encompassing open-source tools, methodologies, Python, databases, SQL, data visualization, data analysis, and machine learning. To obtain the certificate, one must finish nine courses, typically taking around three months with a commitment of 12 hours per week. The certification process involves hands-on assignments and the creation of a portfolio featuring data science projects.
Data Scientist-Advanced Analytics 28
This certification evaluates students’ proficiency through advanced analytics, operationalization, and data visualization techniques. It covers the data analytics lifecycle, guiding students in conducting initial data analysis. Participants will gain insights into advanced analytics and comprehend the technology and tools employed in Big Data.
Additional Resources for Master’s Students in Data Science Degree
Before graduating or after earning a master’s degree in data science, students should take advantage of professional organizations. The following organizations provide members with networking opportunities, career development, and other useful resources:
INFORMS is a fast-growing international association for research and analytics professionals. Members can access professional development opportunities, industry tools, and an extensive professional network.
Association for Computing Machinery: The Association for Computing Machinery (ACM) connects industry leaders in data science working in all fields. ACM’s over 100,000 global professionals network helps data science graduates find new careers.
ASIS&T: ASIS&T combines information science and research, accepting members in fields from data science to content management. Student members receive career services and access to networking opportunities.
The Research Data Alliance connects European, United States, and Australian professionals to encourage the open sharing of data. Students can access valuable industry information through the Alliance’s website.
International Association for Social Science Information Service & Technology
Founded in 1974, IASSIST connects science professionals from all backgrounds to create an extensive community. Aside from access to IASSIST’s conference, members connect with one of the largest science-based online communities.
FAQs About Online Data Science Master’s Programs
Why should you do a master’s in data science degree online?
Pursuing an online master’s in data science offers flexibility, allowing you to balance work and study. It provides access to diverse resources and the latest industry tools. Online programs often accommodate various learning styles, fostering a dynamic and collaborative environment. This convenient format enhances accessibility and accommodates individual preferences and schedules.
How long is the master’s degree in data science?
What can you do with a master’s in data science?
Is an online master’s in data science worth it?
Is it necessary to have a bachelor’s degree in data science to pursue a master’s?
What is the difference between data science and data analytics?
Are online Master in Data Science programs as reputable as on-campus programs?
Citations:
University of California Berkeley
No GRE- University of California Berkeley
Columbia University Data Science Institute
Data Science Council of America
New England Association of Schools and Colleges (NEASC)
Middle States Association of Colleges and Secondary Schools (MSA-CESS)
Higher Learning Commission (HLC)
Southern Association of Colleges and Schools Commission on Colleges (SACSCOC)
Northwest Commission on Colleges and Universities (NWCCU)
Western Association of Schools and Colleges (WASC) Senior College and University Commission (WSCUC)
Alison- Advanced Diploma in Data Science with R
Class Central- Data Science and Agile Systems for Product Management
Alison- Data Science-Working with Data
Data Incubator Fellowship Program
Great Minds in STEM Scholarship
ACM SIGHPC Computational and Data Science Fellowships
U.S. Bureau of Labor Statistics: Occupational Outlook for Economists
U.S. Bureau of Labor Statistics: Occupational Outlook for Data Scientists
Salary.com- Data Science Manager
Certification of Professional Achievement in Data Sciences
Data Science Council of America Senior Data Scientist
IBM Data Science Professional Certificate
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