Most Affordable Masters Program in Data Science

College Of Natural Applied Science » Division of Mathematics and Computer Science » Master of Science in Data Science.

The University of Guam M.S. in Data Science program is a comprehensive and cohort-based study requiring 30 credit hours. Delivered in a face-to-face format, the curriculum places a strong emphasis on the practical applications of statistical methodology, computational science, and diverse domains. It includes a range of topics, including statistical modeling, machine learning, optimization, data management, analysis of large datasets, and data acquisition.

Throughout the program, students will explore reproducible data analysis, collaborative problem-solving, and honing visualization and communication skills. Also, the curriculum addresses ethical and security issues intrinsic to data science. Students will have developed expertise in applying data science techniques to solve real-world problems across various domains.

Master of Science in Data Science program objectives are:.

To establish the first regional graduate program in Data Science that provides affordable education options to local students. The program will offer lower resident tuition rates and access to financial aid and support programs compared to similar off-island programs. Additionally, the program will leverage existing UOG grants such as U54, EPSCOR, and NASA to support students.

To equip students with the necessary skills to work as data analysts in both academic and industry settings. Graduates can contribute to existing research initiatives at UOG, further enhancing research capabilities at the university.

Students completing the Master of Science in Data Science Program at UOG will be able to:.

Design and execute statistical experiments and hypothesis tests to extract meaningful insights from data.

Analyze and interpret complex statistical data using advanced statistical methodologies and tools.

Develop and implement predictive models and machine learning algorithms to make data-driven decisions.

Applicants must have the following minimum qualifications, to be eligible to program:.

Earned baccalaureate degree in mathematics, computer science, biology, chemistry, statistics, psychology, or public health from an accredited college or university.

The bridge course will cover calculus, linear algebra and statistics topics necessary for data science courses. The Bridge Course will take place during the UOG summer Session C, preceding the program start.

Represent data as vectors and matrices and identify their properties using concepts of singularity, rank, and linear independence.

Understand the properties of commonly used probability distributions in machine learning and data science.

All Data Science classes take place on campus in a face-to-face format, with the exception of MA-500 and MA-505, which are eight-week online courses. All required math courses will be held at 4 p.m. Elective courses may take place in the morning or other times of day.

M.S. in Data Science Degree Requirements (30 credit hours).

MA-541 REGRESSION MODELS AND APPLICATIONS (4 credit hours).

MA-551 INTRODUCTION TO PROBABILITY THEORY (3 credit hours).

MA-552 INTRODUCTION TO MATHEMATICAL STATISTICS (3 credit hours).

MA-571 STATISTICAL RESEARCH AND CONSULTING (1-3 credit hours).

MA-581 MACHINE LEARNING FOR DATA SCIENCE (3 credit hours).

The master program offers flexibility by not requiring a thesis. Instead, students can pursue alternative capstone projects or practical experiences aligned with their interests and goals.

The Department of Mathematics & Statistics at the University of Nevada, Reno (UNR) offers a Master of Science and Ph.D. program in Statistics and Data Science. The department provides qualified students with teaching assistantships, research assistantships, and department and university-wide scholarships. Students accepted into the program with teaching assistantships are awarded a stipend, tuition waiver, and subsidized medical plan.

The M.S. Program in Statistics and Data Science is meticulously designed to offer comprehensive training in the contemporary methods and fundamental concepts of Statistics, both in theory and application. This program creates an avenue for individuals to focus on interdisciplinary collaborative research, fostering an environment where students can harness their skills effectively.

By emphasizing research and computational proficiency, the program equips its students with the tools necessary to excel in a wide range of career opportunities. Graduates are well-prepared to pursue careers in academia, government, and the business world, ensuring they remain competitive and adaptive in today's dynamic professional landscape.

Students pursuing the M.S. Program in Statistics and Data Science program have two options to choose from in order to complete their degree:

• The Master’s Thesis Degree Plan (Thesis Plan): This path requires the completion of a minimum of 30 credits consisting of acceptable graduate courses.
• The Comprehensive Exam Plan (Non-Thesis Plan): In this track, students are required to complete a minimum of 32 credits comprising acceptable graduate courses.

It's essential to note that any transfer credits applied to the M.S. program must adhere to a time limitation of 6 years. For example, if a student completed a course five years before their admission to the program, they must finish their degree within one year for that specific course to be considered valid toward their degree requirements. However, students who have already earned a master's degree will be exempt from the 8-year time limitation if they are pursuing a doctoral degree.

The Ph.D. program in Statistics and Data Science is meticulously crafted to offer comprehensive training in the latest statistical methods and data science concepts, with a primary focus on extracting valuable insights from data. Within this program, there is a significant emphasis on fostering interdisciplinary collaborative research.

One of the program's core objectives is to equip students with the essential research and computational skills necessary to excel in their academic, government, and business endeavors. By providing a robust foundation in modern statistics, it aims to empower students to compete effectively and thrive in a variety of professional environments.

Montana State's interdisciplinary Data Science program is designed to provide candidates with a broad range of skills and knowledge. It draws on courses in Computer Science, Mathematics, and Statistics, allowing students to explore diverse topics such as machine learning, algorithms, data mining, and artificial intelligence.

As part of this cross-disciplinary exposure, Data Science students at MSU have access to various laboratories and opportunities, including:

• The Software Lab
• The Applied Algorithms Laboratory
• The Computational Ecology Group
• The Numerical Intelligent Systems Laboratory
• Statistical Consulting and Research Services

Through their education at MSU, Master of Data Science students not only gain technical expertise but also develop essential skills in data analysis, contextualization, and communication. These skills empower them to actively contribute to the field of data science through activities like technical writing, data visualization, presentations, and the creation of active software solutions.

To complete the program, students must earn a total of 30 credits, which are distributed among ten 3-credit courses. Each student is obligated to enroll in one core course from every discipline offered and, as a minimum, select two courses from each of the following categories: computer science, mathematics, and statistics.

The unique features of the Master of Science in Data Science program are:

• Interdisciplinary Flexibility: The Data Science program offers students the flexibility to build their curriculum based on their professional interests. It has core foundations in computer science, mathematics, and statistics, providing a strong base for students to choose courses that align with their career goals.
• WICHE Partnered Program: The program is part of a partnership with WICHE (Western Interstate Commission for Higher Education), benefiting students from 15 western states. Residents of these states can access the program at significantly reduced tuition rates compared to standard non-resident tuition, making it more accessible to a wider range of students.
• Start-Up Prowess: Montana, where the program is located, has a strong entrepreneurial environment. It ranks #4 in Startup Activity among smaller states according to the Kauffman Index of Entrepreneurship. Additionally, Bozeman, a city in Montana, is ranked #3 in Main Street Entrepreneurship, indicating a supportive ecosystem for startups and entrepreneurship-related activities. This suggests that students in the program may have opportunities to engage with the local startup community and gain real-world experience in entrepreneurship.

The Department of Electrical Engineering and Computer Science (EECS) at Florida Atlantic University offers a concentration in Data Science and Engineering (DSE). The Master of Science with Major in Data Science and Analytics (MSDSA) is designed to equip students with the necessary skill sets for analyzing data, whether it's small, fast, big, massive, or complex. Graduates of this program will emerge with valuable hands-on experience and proficiency in data analytics. They will be well-prepared to pursue a range of exciting career opportunities, including roles such as Data Engineer, Data Analytics Scientist, Software Engineer, Machine Learning Engineer, Market Analyst, and more.

The Master of Science program with a major in Data Science and Analytics, specifically the Data Science and Engineering (DSE) concentration, provides students with two distinct pathways: a thesis option and a non-thesis option, both of which necessitate a minimum of 30 credits. To successfully complete this program, students are required to meet all graduate requirements set forth by the University.

• Complete a total of 30 credits, consisting of 6 credits for an orally defended written thesis and 24 credits of approved coursework.
• Ensure that at least one-half of the credits are taken at the 6000 level or above.
• Maintain a minimum GPA of 3.0 on a 4.0 scale.
• Attain a grade of "C" or better in all courses within the degree program.

It is important to note that any transfer credits applied towards fulfilling the requirements of a master's degree in Data Science and Analytics, DSE concentration, must gain approval from the department, the College, and the University. These transfer credits should align with equivalent requirements and performance expectations for the degree program. Generally, no more than 6 credits of coursework (which have not been previously applied to a degree) may be accepted from another educational institution.

The Master of Science in Computer and Information Science (MCIS) program at Southern Arkansas University is renowned for its exceptional offerings, including a specialized Data Science Option. In the realm of computer science graduate programs in the United States, it stands out as both highly appealing and remarkably affordable. This program has earned its place as one of the largest programs available, offering students a comprehensive array of courses that can be pursued both online and in traditional classroom settings.

At its core, the 30-credits MCIS program is meticulously designed to provide students with a well-rounded education that encompasses both theoretical foundations and hands-on practical training. One distinctive feature of this program is its commitment to staying abreast of the ever-evolving landscape of computer science. Regular updates ensure that students are exposed to the latest advancements and trends within the field.

The Data Science Option within the MCIS program is particularly noteworthy. It places a specific emphasis on critical subjects such as data analytics, decision theories, and the management of big data. To excel in this specialization, students are expected to have a foundational knowledge of programming and statistics, laying a solid groundwork for their future endeavors.

Graduates of this esteemed program are equipped with a diverse skill set that opens doors to a multitude of career opportunities. They may find themselves pursuing roles as data analysts, data scientists, decision analysts, or even machine learning engineers, to name just a few possibilities. The strength of the program lies not only in its curriculum but also in its dedicated faculty members, who bring significant industry experience and impressive qualifications to the classroom, enriching the learning experience.

Furthermore, Southern Arkansas University's commitment to academic excellence is reflected in its accreditation by the Higher Learning Commission (HLC). With a focus on quality education, affordability, and the practical skills demanded by the industry, the MCIS program at Southern Arkansas University is undeniably a top choice for those aspiring to advance their careers in the dynamic field of computer science.

Interests and goals. Students receive training in foundational courses in probability and statistics and can then choose from a variety of electives including data mining and data visualization. Students can opt for a thesis or a non-thesis option. Graduates of the program are equipped with the techniques and knowledge needed for careers in government and industry, as well as for the pursuit of further graduate studies.

Gain real world experience by providing consulting services through the Data Analytics Lab.

Teaching assistantships are available for full-time graduate students.

Post-graduation, Zaira now works as an Investment Data Analyst for Thornburg Investment Management.

In an increasingly data-driven world, being able to translate information into meaningful insights that can be used by organizations is a valuable skill. Our graduates are prepared for the pursuit of doctoral degrees as well as careers in business, health and the military, to name a few.

The innovative program in Data Science features a Masters degree and an undergraduate Big Data Analytics Certificate. Both provide students with a background in the foundations of data science and the practical application of data science methods. Candidates for the Masters degree should have coursework equivalent to an undergraduate mathematics minor and at least one course in computer programming.

From data analyst roles to research positions at academic institutions, our graduates emerge prepared to tackle the challenges of our data-rich world.

Immerse yourself in the dynamic world of data science. Gain a deeper understanding of theoretical principles alongside practical applications, preparing you for a range of opportunities in both industry and academia.

Dive into essential mathematical concepts, laying the groundwork for understanding complex data structures and algorithms.

Explore statistical methods for data analysis, enabling you to draw meaningful insights from diverse datasets.

US DOL Bureau of Labor Statistics, Occupational Outlook Handbook, 2023.

You may also qualify for in-state tuition rates and tuition remission for up to two classes.

View a list of current graduate teaching and research assistants.

Internship experience provides the foundation employers are often looking for. Although not required for your degree, internships are an important part of your education experience. These are just a few of the companies that partner with Student Career Preparedness and offer opportunities for A M-Commerce mathematics students.

Designed for working professionals, our master program in mathematics offers a flexible way to earn your degree. We also offer some online and face-to-face courses at the Mesquite Metroplex Center and our main campus location.

Tuition and fees for graduate students taking nine credit hours are $3,669 for Texas residents and $7,341 for non-residents.

After you application, the Graduate School will send a confirmation email within two business days to the personal email account you used for ApplyTexas.

After you application, you may be granted provisional status, which means you can enroll in one semester of courses. You will not be eligible for financial aid until you submit all of your documents and are accepted into the program.

DeRene SuttonGraduate Student Services Coordinator: College of Education and Human Services, College of Science and Engineering, College of Agricultural Sciences and Natural Resources, College of Innovation and Design.

We recommend that you request transcripts for all of your academic work.

All international transcripts must be evaluated and the evaluation submitted to the Graduate School.

Describe your preparation for graduate work and your academic interests and goals in no than 500 words.

Submit a resume or curriculum vitae (CV) which includes your academic and professional history and achievements.

Apply for scholarships and graduate assistantships once you are admitted.

Once registration opens and you are eligible to enroll, your graduate enrollment specialist is here to help you complete registration.

Applicants must have a completed admissions file by May 10 for fall consideration.

You do not need to submit test scores if you have completed (all years) of a bachelor or higher degree from a regionally accredited university in the United States.

Yes, a limited number of graduate assistantships are available to competitive students.

Educational mathematics is designed for secondary and middle school teachers, and qualifies them teaching dual credit courses and at community colleges.

Once you are qualified for comprehensive exams, please let the department head know the courses that you want for the comprehensive exams.

Courses need to be at the graduate level, in mathematics or can be used for a concentration in our program, and offered at a regional credited institution. A 595 course cannot be transferred from another university.

After the research project is chosen, you will work on the project. One summer term is not enough to complete a Math 595 project. There are two options: either get an incomplete grade so that you can have time to finish it in summer II you work on the project in Summer I without registration of Math 595, then you sign up Math 595 in Summer II and complete Math 595 in Summer II. If you want to graduate in August, you need to defend it on or before the first Friday in August.

You may take Math 597 a few times as long as it has a different course title.

The Master of Science (MS) degree in Data Science offers individuals rigorous training in data science methods. Its primary aim is to equip aspiring students with innovative data science techniques to address complex societal challenges and enhance the well-being of humankind. This program provides students with a solid foundation and expertise in quantitative methods, machine learning tools, and data management skills, enabling them to effectively visualize, summarize, and analyze large and intricate datasets.

The program is designed to cultivate broadly applicable analytical skills in data science. Students can personalize their experience by choosing elective courses in areas such as genomics, cybersecurity, or other graduate-level subjects that align with their interests. Additionally, the program offers flexibility in terms of duration, allowing students to complete it within a single calendar year (three semesters), two years, or on a part-time basis.

The MS Data Science program curriculum encompasses:

• A total of 36 credit hours
• Didactic coursework: 21 hours of core coursework; 9 - 10 hours of elective coursework.
• A Capstone Project (5-6 hours)

Mathematics Behind the Data Science (MBDS) Summer Bridge Program.

Mathematics Behind the Science (MBS) Summer Bridge Program.

FOR SUMMER 2023, MBDS WILL BE A RESIDENTIAL PROGRAM WITH STUDENTS LIVING AND TAKING CLASSES ON CAMPUS.

The Mathematics Behind the Data Science (MBDS) summer bridge program is designed to enhance the mathematics preparedness of college-bound students who are interested in pursuing careers in science, data science, mathematics, engineering, technology, or medicine. Specifically, it will prepare students to enter the introductory calculus course and provide a foundation for success in that important course.

Mathematics Behind the Data Science is a STEM (Science, Technology, Engineering, Mathematics) college preparation program that serves students who are entering 12th grade, have completed grade 12 and will enter university as freshmen in the fall, or students already attending UVI who have successfully completed MAT 024. It is intended to serve as a bridge between high school curriculum and expectations at university.

The courses are designed to show students some of the ways that mathematics and data science are used in scientific contexts and to enhance the preparedness of college-bound students who are interested in pursuing STEM careers. The courses will provide a foundation for success in STEM courses in the freshman year. Mathematics is required for majors in both Mathematics and Applied Mathematics (Dual Degree Engineering Program) it is also required for Bachelors degrees in Biology, Marine Biology, Chemistry, Computer Science, and the Associates degree in Physics.

Mathematics Behind the Data Science is a residential program. St. Thomas, St. John and St. Croix students may reside in the dorms on the St. Thomas campus.

To strengthen the mathematical proficiency of entering students, better preparing them for success in college level mathematics courses.

A unique mathematics program exploring the mathematical concepts that underpin the concepts of calculus. Significant connections will be made to biology, chemistry, physics and the environment.

A course in data sciences and computation that will focus on introductory computer science skills and data science applications and concepts with applications to the sciences in order to prepare students for a college STEM curriculum and today environment where computation is used in Biology, Chemistry, Engineering, and other related STEM disciplines.

A Success in STEM course to give students information that will help them to transition to college life, including seminars related to use of library, information technology, student services, and scholarship programs to support student success at UVI.

Genuine interest in pursuing a program of study in science, mathematics, engineering, technology, or medicine .

US Citizenship or permanent residency. International students should inquire funding availability.

The Mathematics Behind the Data Science Application is available online on this link.