Transition into principal investigators and generators of data science-based knowledge. Develop practical skills necessary to conduct high quality data science research, advance development into producers and critical consumers of research, and further development into professional data scientists broadly defined. Research based career topics covered: time management, research products, types of research positions, and grant writing.

Content for this course includes the purposes and nature of theory in educational administration and the application of organization theory to education. Theories of leadership, organizations, decision-making, communication, climate, conflict, change process, and motivation are included.

This course examines and promotes prospective administrators, intrapersonal understanding, interpersonal ability, and potential for effectiveness as leaders. Theory and practice relative to the staffing of schools for effective realization of educational goals and objectives will be explored. Current challenges influencing the optimization of human capital in schools will be studied and students will apply the concepts to their own settings.

This course is designed to prepare individuals for positions of education leadership by exposing them to hands-on administrators. Students will be engaged in a significant number of administrative activities at the elementary, middle, and high schools levels as well as at central office and at community out-reach sites. Students will be mentored on site by licensed school administrators during their 320-hour internship.

This course provides students with the necessary blend of theory, best practice, and authentic problems of practice in leadership. The course provides a bridge between their thought in other courses and the practicalities involved as they prepare for the administrative leadership selection process and their first leadership assignment. Students learn how to use personal assessment tools and feedback to construct Individual Development Plans.

Research Ethics/Responsible Conduct of Research fulfills both the National Science Foundation and National Institutes of Health Responsible Conduct of Research (RCR) Mandate. The course is case-based and practical. The goal is to have course participants grapple with complex research integrity concerns, especially through cases, and to take away important points from each session as well as where to turn for more information.

This is the required course for the graduate Certificate in Digital Humanities. It entails participation in colloquia, sixty hours of experience participating in a research project uniting computation and humanities, and a portfolio.

Where do our educational practices come from? This seminar invites graduate students to explore theories and philosophies of education in order to guide their own professional development and practices as educators. We will examine topics such as psychological and social development, human rights, social justice, and civic engagement in order to determine what it means to be effective educators in 21st century institutions of higher education.

Students will learn algorithms and applications of computational methods for analysis of experimental data from genome, epigenome, and transcriptome sequencing experiments. The course will cover various biological data types (whole genome sequencing, ChIP-seq, ATAC-seq, RNA-seq, and DNA methylation profiling/bisulfite sequencing), algorithms, statistical and computational methods, and application areas in genomics and systems biology. 

This course will cover fundamental topics in statistical genetics with a focus on concepts and methods critical to a concrete understanding of the application of statistical genetics to public health genomics. Major topics covered in this course include modes of genetic inheritance, heritability analysis, linkage and association mapping, integrative analysis leveraging molecular 'omics' data, and genetic risk prediction modeling.