Genomic Data Analysis Online Graduate Certificate
Driving Careers with Specialized Training in Genomic Data Analysis
A 12-Credit 100% Online Graduate Program Steeped in Genetic Data Analysis Technique
Developed and taught by UConn’s Institute of Systems Genomics, the Genomic Data Analysis Online Graduate Certificate program provides an exceptional opportunity for students to gain specialized training in the analysis of high throughput genomic data, without committing to a multi-year full-time graduate degree. The 100% online graduate certificate can be completed in one year.
Meet the Growing Demand for Genomic Data Analysis Skills
As the field of genetics and genomics continues to grow rapidly, the demand for individuals with specialized skills and knowledge in genomics data analysis is on the rise. UConn’s Genomic Analysis Certificate is designed to equip students with the practical skills and theoretical knowledge needed to extract and communicate insight from large genetic datasets. The curriculum consists of four highly interactive and UConn faculty-led online courses introducing students to key concepts in genomics and bioinformatics. The courses further facilitate active learning opportunities, developing technical skills through real-time analysis of high throughput genetic data.
Learn Genomic Data Analysis and its Related Skill Sets
Upon completion of the program, students will have the skills to:
- Utilize best practice analysis methods for analyzing and interpreting genomic data.
- Make clinical diagnostic discoveries using genomic data analysis.
- Communicate analytical approaches and results to both scientific and non-scientific audiences.
Build Connections and Stand Out in the Genomic Analysis Field
UConn’s Genomic Analysis Certificate facilitates networking and engagement of students and professionals, ensuring that graduates are equipped with peer, faculty, and professional networks capable of providing the connections often pivotal in the career-growth of practitioners.
Noah Reid
Noah Reid is an assistant professor in the Department of Molecular and Cell Biology at the University of Connecticut. He received his PhD in Ecology and Evolutionary Biology from the Louisiana State University. His research interests include evolutionary genomics, bioinformatics, and computational biology. Dr. Reid has published numerous research articles in leading scientific journals, and is dedicated to mentoring and teaching students in the field of genomics. He is the Program Director and lead faculty member for UConn’s Genomics Data Analysis Online Graduate Certificate Program.
Jill Wegrzyn
Jill Wegrzyn is an Associate Professor in the Department of Plant Science and Landscape Architecture at the University of Connecticut. She received her Ph.D. in Information Systems and Technology at the University of California, San Diego. Dr. Wegrzyn's research focuses on understanding the genetic basis of complex traits in forest trees and developing genomic tools for their improvement. She has published numerous research articles in peer-reviewed journals and has received multiple grants to support her research. Further, Dr. Wegrzyn is actively involved in teaching and mentoring students in genomics and bioinformatics, and advises multiple graduate students and postdoctoral researchers. Her expertise in genomics data analysis and her passion for teaching make her a pivotal member of the faculty within the Genomics Data Analysis Online Graduate Certificate program.
Vijender Singh
Vijender Singh is an accomplished bioinformatician with extensive experience in genomics data analysis and currently sits as the Associate Director of UConn’s Computational Biology Core. He earned his PhD in ____ from the Indian Institute of Science and as a Bioinformatics Scientist, often works closely with private medical laboratories as a consultant. Dr. Singh has authored numerous publications in high-impact journals and has presented his research at many national and international conferences. His areas of expertise include genomics data analysis, statistical analysis, and algorithm development. As an instructor in UConn's Genomics Data Analysis Online Graduate Certificate program, Dr. Singh brings his knowledge and experience to help students develop the skills needed to excel in the rapidly growing field of genomics.
Program Costs
Students taking courses in the Genomic Analysis Online Graduate Certificate pay a comprehensive fee of $825 per credit or $2,475 for a 3-credit course. The cost of the 12-credit certificate program is $9,900.
Graduate students who are enrolled in a non-approved graduate certificate program (only) are not eligible to receive federal financial aid (Federal Stafford Loan and Graduate PLUS Loan funds).
Students enrolled in the Genomic Analysis Online Graduate Certificate program may wish to consider:
- UConn’s payment plan: http://bursar.uconn.edu/payment-plan-enrollment/.
- Alternative (Private) Loan financing: http://financialaid.uconn.edu/gradalt/.
- Checking with employers for tuition reimbursement opportunities.
Are you currently a UConn student in a master’s degree program?
- Graduate students who are seeking a graduate degree and are simultaneously enrolled in the Genomic Analysis Online Graduate Certificate program are eligible to apply for federal financial aid.
Information on the financial aid application process for Graduate Students is available here: http://financialaid.uconn.edu/graduate/
Courses
ISG 5301 - Basic Concepts in Genomic Data Analysis I (2-credit) (semester)
This course will cover fundamental concepts in genomics and the analysis of genomic data. Course content will provide an overview of the types of questions that can be addressed with genomic data, sequencing technologies used to collect those data, computational tools and infrastructure used to analyze them, the basics of bioinformatic workflows, and the interpretation and communication of high dimensional data through text and figures.
ISG 5302 - Basic Concepts in Genomic Data Analysis II (2-credit) (semester)
This course will cover in depth the concepts underlying several key genomic workflows, including assembly, annotation, variant detection and count-based functional genomic approaches. It will also cover retrieving and depositing data in several common public databases. It will introduce higher level computational tools used in version control and pipeline development, and the communication of results in public presentations.
ISG 5311 - Genomic Data Analysis in Practice I (4-credit) (semester)
This course will introduce students to key tools used in genomic data analysis in academic and industrial settings. Students will become familiar with the Linux operating system, learn to write scripts in the bash language, and learn how to interact with and operate a high performance computer cluster (HPC) through the job scheduler SLURM. Students will be introduced to the statistical computing language R and the tidyverse package for data manipulation. The course will also cover approaches for data and project management. The course will use RNA-seq as a model workflow to introduce tools and concepts.
ISG 5312 - Genomic in Data Analysis II (4-credit) (semester)
This course will introduce students to several key genomic data analysis workflows. It will build on skills developed in the previous semester by walking students through tools used to accomplish these workflows. It will also introduce higher level bioinformatics tools used to ensure reproducibility and re-usability of code, including version control and pipeline development tools. It will familiarize students with searching, accessing and depositing data in commonly used public databases. Students will develop skills in oral presentation of scientific results.
How to Apply & Begin Your Application
To apply for admission to the Genomic Data Analysis Online Graduate Certificate, complete the application process which begins at the link below. Applicants must have completed a Baccalaureate degree or higher from a regionally accredited college or university.
This program only accepts students within the fall semester.
The GRE, GMAT, and Residence Affidavit are not required.
Within the application, please select the following when applying:
- Levels of Study: Certificate
- Academic Areas: Health
- Program: Genomic Data Analysis Grad Cert
- Campus: Online
Applications are evaluated as soon as the student’s file is complete.
If you have any questions on how to use the online application system, please contact The UConn Graduate School at 860-486-3617.
International Students: This program is a part-time and online program. Pursuant to U.S. immigration regulations, the University of Connecticut may not sponsor F-1 and J-1 visas for the purpose of coming to the U.S. for enrollment in this program. International students may enroll in this program if they are currently in the U.S. in another visa status that permits foreign nationals to engage in school enrollment while meeting their primary visa objective, or if they complete the program from their home country.
Join An Infosession
Genomic Data Analysis Online Graduate Certificate Program Information Sessions
Attending an information session on UConn's Genomic Data Analysis Online Graduate Certificate program can provide valuable insight into the program and its curriculum.
There are currently no information sessions scheduled. However, please join our mailing list and we will be sure to drop you a note as soon as sessions become available.
Who can I talk to about UConn’s Genomic Data Analysis Online Graduate Certificate?
To discuss application, enrollment, program curriculum and content please reach out to me.
Noah Reid
Program Manager & Research Assistant Professor
Department of Molecular and Cell Biology
University of Connecticut
Email: noah.reid@uconn.edu
Phone: 860-486-6963
An Online Graduate Program from a Top-Ranked (R1) University
The University of Connecticut is ranked in the Top 25 Public Schools by US News & World Report and is accredited by the New England Association of Schools and Colleges.