Online Master’s Program: Data Science in Biomedicine

The Master of Science in Data Science in Biomedicine combines foundational training in all areas of data science including machine learning, statistics, data mining, algorithms and analytics with understanding of application areas including genomics, medical imaging, and analysis of electronic health records as well as other types of medical data (waveforms, mobile health data, etc.).  Graduates of the program will have the necessary skills and background to develop new data science methodologies and apply them to a wide range of biomedical data sources.  

The instructors are UCLA faculty whose research programs span both data sciences and medicine, are actively engaged in biomedical research, and have many years of experience in teaching interdisciplinary courses.

Graduates of the program will develop critical skills that will enhance their careers, including:

  • Deep technical knowledge in data science, with a strong basis in the fundamentals 

  • Deep technical knowledge of the biomedical data

  • Knowledge of the current active research areas of data science in biomedicine in the healthcare industry

  • Understand the potential of biomedical data analysis to improve patient care

  • Understanding of ethical considerations in biomedical research such as implicit bias and inclusion 

  • Ability to communicate the results of research effectively

We expect that the majority of the students will be employed full time in the biotech/pharma industry, especially genomics companies and digital health companies, and that many of them will receive tuition benefits from their employer.  The ideal candidate has a strong quantitative and computational background either from their undergraduate degrees (such as a Computer Science major) or will have developed these skills through their work experience or non-degree study.  They will be early in their careers and/or will be seeking data science training to support their career advancement. 

Curriculum:

Students will complete 36 quarters units or 9 courses at the graduate level.  Students will typically take one course per quarter.  The program includes a culminating capstone project which will deepen and integrate the students' knowledge acquired throughout the program. 

Data Science in Biomedicine courses include:

  • DSB 200 Foundations of Data Science 

  • DSB 205 Machine Learning Applications in Biomedicine 

  • DSB 206 Advanced Machine Learning Applications in Biomedicine 

  • DSB 207 Data Science for Medical Imaging 

  • DSB 218 Applied Data Science in Genomics and Biomedicine 

  • DSB 219 Data Science Algorithms in Biomedicine 

  • DSB 220 Data Science in Biomedicine Supervised Project

 

While all courses are online, a few of the courses will also be offered in-person for those who want one or two quarters in residence at UCLA.

For more information, including tuition, admissions process and deadlines, and course description, please access the DSB Program Webpage.