Biomedical Engineering and Data Science

Earn two Master's degrees in two years.

First Year

Fall Semester - 15 Credit Hours

  • BMEN 5210 - Biomedical Engineering
  • BMEN 5315 - Computational Methods in Biomedical Engineering
  • BMEN 5940 - Biomedical Engineering Seminar
  • INFO 5501 - Fundamentals of Data Analytics
  • INFO 5502 - Principles and Techniques for Data Science

Spring Semester

  • BMEN Courses – 9 Credit Hours
  • INFO 5505 - Applied Machine Learning for Data Scientists

Summer Semester

  • MSDS Guided Electives – 6 Credit Hours

Second Year

Fall Semester

Thesis Option

  • BMEN Elective
  • BMEN Thesis
  • MSDS Guided Electives – 6 Credit Hours

Non-thesis Option

  • BMEN Course
  • MSDS Guided Elective
  • MSDS General Elective
BMEN Courses
  • BMEN 5005 – Neuroengineering
  • BMEN 5007 – Research Methods in Biomedical Engineering
  • BMEN 5280 – AI for Wearables and Healthcare
  • BMEN 5310 – Clinical Instrumentation
  • BMEN 5311 – Rehabilitation Engineering
  • BMEN 5312 – Advanced Signal Processing in Biomedical Engineering
  • BMEN 5313 – Bioengineering of Cellular Systems
  • BMEN 5314 – Advanced Tissue Engineering and Regenerative medicine
  • BMEN 5316 – Biopolymers and Flexible Bio-electronics
  • BMEN 5317 – Advanced Biotechnology
  • BMEN 5318 – Biomedical Implants
  • BMEN 5319 – Cardiovascular Fluid Dynamics
  • BMEN 5320 – Advanced Biomechanics
  • BMEN 5321 – Biomaterials Compatibility
  • BMEN 5322 – Medical Imaging
  • BMEN 5323 – Advanced Biomedical Optics
  • BMEN 5324 – Biomedical MEMS
  • BMEN 5325 – Bio-nanotechnology
  • BMEN 5326 – Biomolecular Engineering
  • BMEN 5700 – Statistical Genetics
  • BMEN 5800 – Topics in Biomedical Engineering
  • BMEN 5810 – Topics in Biomedical Engineering
  • BMEN 5890 – Directed Study in Biomedical Engineering
  • BMEN 5900 – Special Problems in Biomedical Engineering
  • BMEN 5910 – Special Problems in Biomedical Engineering
  • BMEN 5920 – Cooperative Education in Biomedical Engineering
BMEN Electives
  • 5000 or 6000 level courses from any of BMEN, EENG, MEEN, MTSE, CSCE, or BIOL
  • 5000 level or above MGMT/LSCM/MKTG courses from the College of Business
  • 5000 level or above HLSV courses from the College of Health and Public Service
  • 5000 level or above MUPH courses in Performance Arts Health from the College of Music
  • 6000 level or above ASLP courses in Audiology from the College of Health and Public Service
Data Science Guided Electives 
  • CSCE 5213 - Modeling and Simulation
  • CSCE 5218 - Deep Learning
  • CSCE 5300 - Introduction to Big Data and Data Science
  • DSCI 5240 - Data Mining and Machine Learning for Business
  • CSCE 5380 - Data Mining
  • DSCI 5330 - Enterprise Applications of Business Intelligence
  • DSCI 5340 - Predictive Analytics and Business Forecasting
  • INFO 5040 - Information Behavior
  • INFO 5206 - Information Retrieval Design
  • INFO 5307 - Knowledge Management Tools and Technologies
  • INFO 5503 - Knowledge Management Processes and Practices
  • INFO 5810 - Data Analysis and Knowledge Discovery
  • ADTA 5230 - Data Analytics II
  • DSCI 5360 - Data Visualization for Analytics
  • INFO 5709 - Data Visualization and Communication
  • LING 5410 - Computational Linguistics I
  • LING 5412 - NLP in Linguistics
  • LING 5415 - Computational Linguistics II
Data Science General Electives
  • CSCE 5200 - Information Retrieval and Web Search
  • CSCE 5214 - Software Development for Artificial Intelligence
  • CSCE 5216 - Pattern Recognition
  • INFO 5091 - Data Science Internship
  • INFO 5200 - Information Organization
  • INFO 5205 - Information Indexing, Abstracting and Retrieval
  • INFO 5223 - Metadata for Information Organization and Retrieval I
  • INFO 5224 - Metadata for Information Organization and Retrieval II
  • INFO 5305 - Systems Analysis and Design
  • INFO 5365 - Health Sciences Information Management
  • INFO 5637 - Medical Informatics
  • INFO 5707 - Data Modeling for Information Professionals
  • INFO 5731 - Computational Methods for Information Systems
  • INFO 5735 - Usability and User Experience Metrics
  • INFO 5737 - Information and Cyber-Security
  • INFO 5745 - Information Architecture
  • INFO 5770 - Introduction to Health Data Analytics
  • INFO 6050 - Health Research Methodology
  • LTEC 5300 - Learning and Cognition
  • LTEC 5320 - Contemporary Issues in Workforce Learning and Performance
  • LING 5405 - Python Programming for Text

Application

Applying to the MS (BMEN)-MS (DS) option:

  1. Apply to the MS in Biomedical Engineering as directed by the College of Engineering. You will need to pay a $75.00 application fee.
  2. Complete a 2nd ApplyTexas application, selecting Master of Science in Data Science as your chosen degree. When you apply through ApplyTexas, select “pay by check.” Do not remit an application fee for this second application. You will also not need to submit transcripts for this second application, as we will already have them on file. But, after you have received access to the MyUNT portal (it takes 2 to 3 days to get access to MyUNT portal after you submit ApplyTexas application), you will need to submit all other required documents, as mentioned at: https://informationscience.unt.edu/admission-ms-data-science. 
  3. Please email at BMEN-DS-Admit@ad.unt.edu your ApplyTexas application numbers of BOTH your Engineering application and your MS in Data Science application. We will waive the 2nd application fee (and you will not submit payment). In summary, you will only pay one application fee for both applications.

Please note that it is a cohort-based very intensive program with a heavy workload and high commitment expectations. The admission process for this option is very competitive.

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