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Masters of Science in Data Analytics

Masters of Data Analytics

Master of Science

Graduate (Masters)

On Campus (In-Person)

Downtown Location

 

Contact Us

University of Houston-Downtown
One Main Street,
Houston, TX 77002

 
713-223-7972
msda@uhd.edu

Angel Griffin
Assistant Director of Graduate Studies
Ermelinda DeLaViña
Associate Dean & Director of MSDA

 

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CST Graduate Advising Contact Information


Phone: 713-223-7972
Email: msda@uhd.edu

 



Imagine a project involving numerous, linked Excel spreadsheets with over 1,000,000 rows of data with a dozen columns of attributes. Google processes over one million gigabytes of data daily. Tens of billions of financial shares are traded every day. Every week, astronomers collect over 100,000 terabytes of data from the heavens. Health professionals enter over terabyte of data monthly in the USA. This is big data.

The University of Houston–Downtown offers an evening and weekend Master of Science in Data Analytics. Weekday classes start at 5:30 PM! This is a master's program that will allow motivated, ambitious students from various academic backgrounds to learn the statistical and computation tools to assemble, structure, and analyze large data sets; learn to manage large projects involving big data; and effectively communicate findings, visually, orally, and in writing.


Program Description:

The Master of Science in Data Analytics (MSDA) is a theory and application-based program that will provide students with a broad education in advanced statistics, digital data acquisition, digital data management, data analysis, and data presentation.

The MS in Data Analytics is designed to meet the increasing need for highly skilled data analysts who can analyze the growing amount of data confronting in a variety of disciplines, and transform it into usable information for use in decision-making. The program is a university-wide collaboration that delivers rigorous training in statistical analysis and computational techniques and provides mastery of data analysis tied to interdisciplinary applications. Students in the program study 27 hours of foundation courses with topics in regression analysis, multivariate analysis, experimental design, nonparametric analysis, statistical modeling, simulation, mathematical theory for data analysis, and statistical computing. Students also take 6 hours of interdisciplinary application courses in business management, science, criminal justice, education, communication, and social sciences. In the final semester, students will have the opportunity to engage in research or real-world applications with faculty members at UHD and other collaborators of UHD faculty and/or internships with partnering businesses, industry, and government agencies.

 

 

Program Learning Outcomes:

Students who complete the program will be able to:

  • Organize, manipulate, and summarize data in various formats.
  • Convert a data analytic problem and related information into a proper mathematical representation and select appropriate methodologies for analysis based on attributes of the available data sets.
  • Implement security measures and ethical practices for the collection and storage of data.
  • Transfer (and transform) data from different platforms into usable contexts.
  • Communicate and summarize results of data analysis in written, oral and visual form.
  • Select the appropriate methods and tools for data analysis in specific organizational contexts.

 

MSDA Degree Requirements:

The Master of Science in Data Analytics requires a minimum of 35 semester credit hours that include a choice of a capstone or internship experience.

Required Courses (30 hours)
STAT 5301 Statistical Foundations for Data Analytics
CS 5301 Programming Foundations for Data Analytics
STAT 5307 Time Series Analysis
STAT 5310 Applied Regression Analysis
STAT 5311 Multivariate Analysis and Nonparametric Statistics
TCOM 5340 Project Management
CS 5310 Data Mining
CS 5318 Database Management Systems
CS 6301 Information Visualization
STAT 6382 or CS/STAT 6380/6399 Capstone in last semester

 

Elective Courses (2 courses)
CJ 6321 Quantitative Analysis and Criminal Justice
CS 6302 Predictive Analytics
CS 6303 Big Data Analytics
MATH 5302 Mathematical Statistics
*MBA 6211 Managerial Decision Making
*MBA 6325 Decision Modeling
*MBA 6362 Financial Forecasting
SOC 6320 Survey Research Methods
STAT 5309 Design and Analysis of Experiments
STAT 6312 Biostatistics

 

*MBA Graduate tuition will apply.

For course descriptions please see the

Graduation is dependent upon satisfactory completion of all coursework with a minimum graduate grade point average of 3.0 and completion of a capstone course, internship course or approved directed study. Satisfactory completion of graduate courses includes completing all coursework with a grade of "B" or better.

Minimum Grade Point Average to remain in the MSDA program

No more than two grades below a "B" in any graduate level courses will be accepted toward the MS in Data Analytics degree. At most two grades of "C" will be allowed and then only if the cumulative GPA is 3.0 or higher. Upon receipt of the third grade below a "B" in any three required graduate courses, or if the GPA drops below 3.0, the student will be academically dismissed from the program once all appeals processes are exhausted. If a student wishes to appeal their admissions decision, all written appeals must be directed to the Director of the Graduate program by emailing msda@uhd.edu. For example, if a student feels that there was an error in any documentation received.

Transfer of Graduate Credits

A maximum of two approved courses may be transferred from another accredited university. A minimum grade of "B" is required for the course to transfer. All petitions for transfer credit must be submitted to the UHD Graduate Admissions Committee at the time of application for the committee's approval.


Application Deadlines

Woman looking at analytics. 

Spring 2025 US residents January 6 and International October 1

Summer 2025 US residents May 1 and International April 1

Fall 2025 US residents July 15 and International May 1

APPLY NOW

Admission Requirements:

Admission requirements for the MS in Data Analytics are designed to identify applicants who have the ability, interest, and qualities necessary to complete the program. Admission is competitive and selective. Applicants must demonstrate that they possess the abilities, interests, and qualities necessary to successfully complete the program. The application opens on September 5

Applicants seeking admission will provide the following application materials for review by the Graduate Curriculum Committee. Please submit all documents to the Graduate Admissions office at gradadmissions@uhd.edu

  • A completed SLATE application (Click on Apply Now below).
  • Submit (1,000 words or less) a personal statement that addresses why you want to pursue a master's in data analytics.
  • Bachelor's degree conferred by a regionally accredited institution.
  • Official University transcript(s) from which the applicant earned a Bachelor's degree and an advanced degree (if applicable) indicating:
    • the last 60 semester credit hours of coursework and evidence of Bachelor's degree awarded and the GPA. as admission to the degree program is competitive, candidates with a cumulative GPA of 3.0 or higher will be preferred.
    • Students with an international transcript must submit their transcripts to UHD already evaluated for U.S. equivalency. Here is a list of approved agencies.
  • Graduate Record Exam Scores. However, there are two GRE waiver options available:
    • The GRE Waiver form can be requested for applicants with a GPA above 3.0 in their last 60 hours of college coursework. The last 60 hours GPA must be counted with all attempted course grades including repeats and not just the highest grades.
    • Complete CS 5301 (Programming in Foundations of Data Analytics) and STAT 5301 (Statistical Foundations for Data Analytics) with grades of B or better by applying as a Graduate Certificate in Foundations of Data Analytics student. 
  • Resume documenting any work experience that emphasizes personal and professional accomplishments.
  • Two references from individuals well-acquainted with your work and who are able to address your academic potential, for example, work supervisors and professors. Recommenders may either write a letter or complete the MSDA Application Reference Form.
  • Test of English as a Foreign Language (TOEFL) score, if you are a graduate of a university where English is not the primary language of instruction (preferred TOEFL scores are: an Internet-based score of 81, a paper-based score of 553 or an IELTS score of 6.5 or higher). As a waiver to these English Proficiency Exams, the College of Sciences & Technology Graduate Studies office will accept as proof of English proficiency, full-time employment history of at least 3 years in a country where English is the primary language spoken, such as the US, UK, Canada, etc. Please submit an English Proficiency Waiver Form as part of your application documents to the Graduate Admissions office.
Admission Process:
The Graduate Advisory Committee will evaluate applications using a matrix based on GPA, GRE score, relevant coursework or experience, recommendations, and other written materials in the applicant's file. The Graduate Advisory Committee will use the results of this evaluation to determine if an applicant is admitted. The Graduate Coordinator will notify students, in writing, of the committee's decision. If an applicant wishes to appeal their admissions decision, can do so here: CST Graduate Admissions Appeal Form.
 

* Please view all of the application requirements on the UHD Admissions website before submitting your application.


Information Session

You are cordially invited to an information session for the Master of Science in Data Analytics program at the University of Houston-Downtown. A master's degree from the University of Houston-Downtown can be the edge you need to launch your career to new heights.

During the information session, you will have the chance to learn about admissions requirements and financial aid options, and discuss schedules and curriculum.

Information Session Date: 

2/5/2025
06:00 - 7:30 PM
RSVP

3/4/2025
06:00  - 7:30 PM
RSVP

3/6/2025
10:00-11:30 AM
RSVP

4/1/2025
6:00-7:30 PM
RSVP

5/6/2025
6:00-7:30 PM
RSVP


Resources for Prospective Students


Resources for Current Students

The College of Sciences and Technology, Graduate Studies currently offers a Master of Science in Data Analytics. We provide academic advising to current graduate students in the program. If you need assistance with personalizing your graduation plan to ensure you graduate within a timely manner, please schedule an appointment. All students have access to their degree evaluation at MyUHD and we are more than happy to assist you with any advising questions or concerns. Please see office hours below.

Contact for Office

Hours: 8:00 A.M. - 5:00 P.M.
Phone Number: 713-223-7972
Email: msda@uhd.edu


Questions About Graduate Admissions

Graduate Admissions Office
713-221-8093
713-221-2718 (fax)
gradadmissions@uhd.edu

For any other information about the MS in Data Analytics, contact the Assistant Director of Graduate Studies, Angel Griffin at msda@uhd.edu.


Accreditation

The University of Houston-Downtown is accredited by the Southern Association of Colleges and Schools Commission on Colleges to award baccalaureate and master's degrees and certificate programs. Contact the Commission on Colleges at 1866 Southern Lane, Decatur Georgia 30033-4097 or call 404-679-4500 for questions about the accreditation of the University of Houston-Downtown.

MSDA By the Numbers




Start of the Program

Fall 2015 EST


114

# of Students
at the start of Fall 2023


328

Alumni
to date in MSDA



20

Average Class Size
Small class sizes give our students a more supportive environment.


75%

of Students
are part time


25%

of Students
are full time

 

*Numbers indicate the number of students reported to the Texas Higher Education Coordinating Board. Data is obtained from Fact Sheets and Fact Books at UHD Institutional Research.



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