It is time for a data science program that situates you to solve some of the most pressing problems of the day.
Technology has the power to revolutionize our world. However, it is up to us to decide whether those changes will help or harm our society. We know firsthand how technology has discriminated against historically disenfranchised groups through the misuse of facial recognition software and predictive policing algorithms, for example.
And with increased reliance on data to address social problems, we need a new class of data scientists to understand the existing systems, work on redressing them before more data bias gets perpetuated, all the while creating new knowledge in the process. Howard University’s new MS in Applied Data Science is here to fill that gap. This degree connects the Howard ethos of justice, and excellence in truth and service, with the technical finesse and data science backing needed to understand and work towards technical advances that are equitably shared among all segments of society.
The Howard University MS in Applied Data Science will prepare students for successful careers in a burgeoning and prospering field. With a unique emphasis on Social Justice and the growing importance of understanding data across academic disciplines, this three-semester long program provides students with traditional data science opportunities while also offering specializations in the areas of Minority Health & Health Disparities, Environmental Justice, and Economic Empowerment.
Each and all these fields of study will equip students from traditional and non-traditional STEM backgrounds alike to enter diverse industries with solid expertise across data science disciplines with equity at the forefront of their work. The only question that remains is, will you be among them?
W.E.B. Du Bois, The Philadelphia Negro, 1898
Nevertheless here are social problems before us demanding careful study, questions awaiting satisfactory answers. We must study, we must investigate, we must attempt to solve ; and the utmost that the world can demand is, not lack of human interest and moral conviction, but rather the heart-quality of fairness, and an earnest desire for the truth despite its possible unpleasantness.
Stand Out and Stand Up
With collaborations across 5 schools and colleges, representing over 50 areas of study, students will experience an interdisciplinary program.
Students will prioritize the use of data science to investigate questions pertinent to historically marginalized communities in an innovative manner.
Situated in the nation’s capital, the program allows students to gain insight into the analysis, interpretation, and application of data to real world problems with key decision makers.
The Center of Applied Data Science and Analytics at Howard University
The Center of Applied Data Science and Analytics at Howard University (CASDA) coordinates and facilitates interdisciplinary data science research and instruction in the primarily in the following areas:
• Economic empowerment
• Minority health & health disparities
• Social justice
• Environmental justice
To address these issues, CADSA provides the HU investigator community the resources needed to develop data-driven understandings of the current state of each of these research areas. Additionally, CADSA will develop proper insight into research trend directions and how the HU research effort can position itself to both benefit from and influence the developing trend directions. In summary, the CADSA is an HU institutional tool of inquiry that produces new information that can then be used to address important human problems. As a result, the research philosophy of the CADSA will be to inquire, to inform, and to intervene.
Students have the flexibility to pursue the Master of Science in Data Science and Analytics degree on a part- or full-time schedule. Part-time students enroll in one or two courses each semester and take their courses in the evenings. Full-time students take three courses per semester.
Students earn the Master of Science in Data Science and Analytics by successfully completing thirty credit courses and a final internship/capstone project.
The only way to stop data from exacerbating historical disparities for marginalized communities is by producing data scientists who consider the importance of social consciousness and tackling sensitive issues of difference head-on.
Howard University’s new online M.S. in Applied Data Science and Analytics connects the Howard ethos of social justice and excellence in truth and service with the technical data science skills needed to understand and work toward equity among all segments of society. We challenge students to engage in issues concerning minority health & health disparities, environmental justice, and economic empowerment.
Howard's data science students have the opportunity to conduct original research, interact with our community, government and industry partners through an internship or practicum, produce a capstone project, and engage with world-class faculty.
Howard's data science students have the opportunity to conduct original research, interact with underrepresented communities, government and industry partners through an internship or practicum course, produce a capstone project, and engage with world-class faculty.
The courses prescribed by this program include:
Pre-Capstone (0 credits)
Introduction to Data Science (3 credits)
Computational Social Justice (3 credits)
Statistically Measuring and Modeling Social Justice (3 credit)
Engineering and Managing Data-driven Change (3 credits)
Data Storytelling & Visualization (3 credits)
Applied Data Science for Social Impact (3 credits)
Applied Machine Learning, Bias and Ethics (3 credits)
Elective Course (3 credits)
Elective Course (3 credits)
Practicum/Internship (2 credit)
Capstone (1 credit)
Student will also receive career mentorship, opportunities to work on social impact projects and join communities of social justice organizations and institutions working for change.
Howard's MS Online Applied Data Science and Analytics enrolls individuals who show potential to become change agents in the field of data science.
Transcripts from all previously attended institutions
Personal statement and application essay
Three letters of recommendation
No GRE score is required to apply.
❱ Fall entry (deadline for priority admission): January 15, 2023
❱ Fall entry (final deadline for admission): April 15, 2023