The Online Graduate Certificate in Biomedical Informatics and Data Science (BIDS-CERT) is offered as a graduate level program ideally suited for working professionals and students interested in fields where biomedicine, precision medicine, health informatics, and data science intersect. Building on the core curriculum of UD’s Master’s and PhD bioinformatics data science degree programs, the Online Graduate Certificate will allow students to gain core competency in data science for real-world applications ranging from genomics to pharmaceutical, health informatics, and biomedical research. No previous programming or database experience is required but a familiarity with molecular biology and statistics is recommended.
- Earn credentials from a highly reputable bioinformatics data science program to advance your career
- Earn graduate level college credits that can be applied towards a Master’s or PhD degree program
- Gain core competency for rapidly growing bioinformatics data science job opportunities in fields from genomics, pharmaceuticals and health care to big data analytics
- Gain knowledge and experience in bioinformatics data science methods and analysis for improving understanding of biomedical systems and applications
- Learn cutting-edge state-of-the-art course contents from nationally and internationally renowned researchers and practitioners in the field
- Learn in an interactive, experiential and multidisciplinary team environment that incorporates online instructions with hands-on exercises and term projects
Requirements (Browse Courses)
The course curriculum consists of four graduate level courses that can be taken in any order. Each course will be offered annually during either Fall or Spring semester. Two courses will be offered each semester so that the Certificate program can be completed in as little as one year.
Biomedical Informatics Core (6 credits)
- BINF644 Bioinformatics (3 Credits): Principles of molecular sequence analysis and genome annotation with practical guides to bioinformatics resources, databases and tools
- BINF694 Systems Biology (3 Credits): Bioinformatics interpretation and biological network analysis of omics data from next-generation sequencing (genomics, transcriptomics) and other high-throughput technologies
- BINF690 Programming for Bioinformatics (3 Credits): Principles and techniques of computer programming using Python language framed within the context of bioinformatics
- BINF640 Databases for Bioinformatics (3 Credits): Principles and techniques of bioinformatics database development cycle from data modeling to relational database management and web hosting
Data Science Core (6 credits)
- BINF667-010 Applied Machine Learning (3 Credits): Basic concepts of machine learning principles and paradigms, and knowledge of machine learning pragmatics that are involved in a complete learning process from formulating a problem to choosing the appropriate techniques/tools to evaluating the results.
- BINF667-011 Data Science with Online Competitions (1 Credit): Introduce students to online data science competitions on Kaggle. Students will participate in various online competitions on Kaggle and get hands-on experience with applied machine learning.
- BINF667-012 Big Data Analytics in Biomedicine and Health (3 Credits): Introduce unsupervised and supervised methods for large-scale biomedical data analysis as well as healthcare analytics from model selection and risk stratification to disease progression and causal inference.
- Discounted tuition rate.