Certificate in Data Science

The rise of data science has driven advances in technology across almost all areas of our life, including health. Modern computational tools give us the ability to manage, process, and analyze data on previously unthinkable scales. Recent advances in statistics and machine learning allow us to glean new insights for these data. These new advances demand an innovative approach to training public health practitioners of the future. Trainees should be equipped with a skill set that allows them to address challenges raised by modern approaches to data collection and analysis. Trainees must also be equipped with an understanding of the challenges, limitations, and ethical implications of these novel approaches. Students in the Data Science Certificate program at RSPH will be trained to meet the needs of a rapidly advancing health research field. Pursuing data science training within a top public health school will allow students to see how modern data science can be used towards advancing the public good, rather than increasing corporate profits.

This certificate will be available for MPH & MSPH degree candidates in all departments of the Rollins School of Public Health. There are no pre-requisite courses for the Certificate.

The certificate in data science has five specific competencies that students who complete the certificate are expected to master.

  1. Use open-source software to analyze data.
  2. Apply modern software tools to construct reproducible data science workflows.
  3. Identify settings where machine learning can be used to inform public health and clinical decision making and apply common machine learning frameworks to data.
  4. Develop data science products that increase accessibility and interpretability of analytic findings.
  5. Communicate effectively with public health stakeholders.

This certificate program has 4 required courses (R programming, data science toolkit, machine learning, and a current topics course) which is 8-9 credit hours plus 3-4 hours of elective credits. Students must additionally ensure that their APE and ILEs can be related to data science, as described below. In extenuating circumstances, students may replace the APE and/or ILE requirement with additional elective courses in lieu of these requirements.

Programming:

Course Title Credits Semester Prerequisites

BIOS 544

Introduction to R Programming for Non-BIOS Students

2

 Fall/Spring None
BIOS 545 R Programming for BIOS Students 2 Spring None

 

 Data Science Toolkit:

Course Title Credits Semester Prerequisites

DATA 550

Data Science Toolkit

2

 Fall BIOS 544/545 (concurrent enrollment OK)

 

Machine Learning (Choose One):

Course Title Credits Semester Prerequisites
BIOS 534

Machine Learning

3

 Fall/Spring BIOS 585 + Multivariate Calculus + Linear Algebra
DATA 534 Applied Machine Learning in Public Health 2 Fall/Spring BIOS 500 + (BIOS 544 or BIOS 545)

 

Current Topics:

Course Title Credits Semester Prerequisites

DATA 555

Current Topics in Data Science

2

 Spring None

 

All certificate students should enroll in DATA 555 in the spring semester of their second year. This course will facilitate the integration of the development of an approved data science product into the students’ existing ILE requirements.

All students should make a good faith effort to complete a data science component as a part of their ILE and enroll in DATA 555. However, if extenuating circumstances preclude a student from identifying an appropriate data science component for their ILE, then an additional 4 credit hours of electives may be completed in lieu of DATA 555.

Applied Practice Experience (APE)

To satisfy the certificate APE requirement, either:
      1) A data science-related APE should be completed; or
      2) 3 additional credit hours from the list of electives above should be completed

Integrated Learning Experience (ILE)

We will offer a 2 credit Current Topics in Data Science (DATA 555) that students will complete in the spring semester of the second year. This course must be taken in addition to each degree program’s specific ILE requirements. If a project cannot be identified then the student must complete an additional 4 credit hours of electives from the list of acceptable elective courses.

Each fall semester students will declare their interest in the certificate by submitting a formal Declaration of Intent. The Declaration will ask students to answer specific questions to gauge the student’s interest and desire to complete the Data Science Certificate.

Data Science Certificate Administrators

David Benkeser, PhD
Associate Professor, Department of Biostatistics and Bioinformatics  
Director, Data Science Certificate
RSPH
GCR, Room 322
benkeser@emory.edu

Angela Guinyard
Assistant Director of Academic Programs in Biostatistics
Coordinator, Data Science Certificate
RSPH
GCR, R00 270
Office: (404)712-9643
angela.guinyard@emory.edu