Convergence Education and Its Goals

Convergence education through experimental learning is critical in training future data scientists.

Goal 1. New Graduate Curriculum

We developed a new graduate curriculum based on transdisciplinary courses and research projects and using extensive convergence activities. The new program has been developed for both Master and PhD students from various departments and colleges including Computer Science, Computer Engineering, Electrical Engineering, Nursing, Science, and Medicine. The Master program takes18 months to complete, while PhD program 3 to 4 years, which is typical timing for these programs. The program includes normalization courses, boot-camps, in-depth elective courses, testbeds, and professional workshops. The desired result of this goal is to produce graduates with technical depth and transdisciplinary understanding of data science technologies and applications.

Goal 2. Transdisciplinary Research Projects

Students in the NRT program will be involved in interdisciplinary research projects. Testbeds are developed in our newly created AI-DA laboratory. Research projects are formulated jointly with industry partners who are members of our NSF I/UCRC CAKE, so students work on real life problems. The desired result of this goal is to advance data science and technologies and address societal grand challenges in this area.

Goal 3. Initiate New Activities to Aggressively Recruit and Retain Women and Other Underrepresented Groups

We developed new activities to recruit students for the NRT program with focus on woman and underrepresented groups. Very recently the U.S. Department of Education, Office of Post Secondary Education informed us that FAU is designated as an eligible institution under Titles III and V. This means that FAU is a Developing Hispanic-Serving Institution (HSI) and is eligible for Promoting Postbaccalaureate Opportunities for Hispanic Americans (PPOHA).