Department: Biomedical Data Science

Code Name Description
BIODS201 Biomedical Informatics Student Seminar Participants report on recent articles from the Biomedical Informatics literature or their research projects. Goals are to teach critical reading of scientific papers and presentation skills. Summer Quarter consists of critical review of relevant lit...
BIODS202 BIOMEDICAL DATA SCIENCE This course introduces the data modalities and methods valuable to ask and answer probing and novel questions that advance biomedicine. You will get exposure to a variety of current data types from imaging and omics to patient-centric and digital he...
BIODS205 Bioinformatics for Stem Cell and Cancer Biology For graduate and medical students. High-throughput technologies and data science are essential tools in modern stem cell biology and cancer research. Students will gain practical exposure to bioinformatics concepts and techniques required to address...
BIODS210 Configuration of the US Healthcare System and the Application of Big Data/Analytics Almost no country anywhere in the world can afford their healthcare. Starbucks spends more money on healthcare than their coffee. General Motors spends more money on healthcare than steel for their cars. The macro economic effects of healthcare costs...
BIODS215 Topics in Biomedical Data Science: Large-scale inference The recent explosion of data generated in the fields of biology and medicine has led to many analytical challenges and opportunities for understanding human health. This graduate-level course focuses on methodology for large-scale inference from biom...
BIODS217 Analytics Accelerator This is a multidisciplinary graduate level course designed to give students hands-on experience working in teams through real-world project-based research and experiential classroom activities. Students work in dynamic teams with the support of cours...
BIODS217A Analytics Accelerator Seminar CME 217A introduces students to potential computational mathematics research projects at Stanford and with outside organizations. This seminar series is an introduction to winter quarter CME 217B, a multidisciplinary graduate level course designed to...
BIODS220 Artificial Intelligence in Healthcare Healthcare is one of the most exciting application domains of artificial intelligence, with transformative potential in areas ranging from medical image analysis to electronic health records-based prediction and precision medicine. This course will i...
BIODS221 Machine Learning Approaches for Data Fusion in Biomedicine Vast amounts of biomedical data are now routinely available for patients, raging from genomic data, to radiographic images and electronic health records. AI and machine learning are increasingly used to enable pattern discover to link such data for i...
BIODS227 Current Topics in Machine Learning for Neuroimaging The discovery of biological markers in medical applications is a fast-growing field. For this purpose, different experimental and neuroscientific procedures are incorporated to detect biological signatures and improve diagnosis or treatment of comple...
BIODS232 Consulting Workshop on Biomedical Data Science The Data Studio is a collaboration between Spectrum (The Stanford Center for Clinical and Translational research and Education) and the Department of Biomedical Data Science (DBDS). The educational goal of this workshop is to provide data science con...
BIODS235 Best practices for developing data science software for clinical and healthcare applications Best practices for developing data science software for clinical and healthcare applications is a new seminar aimed to provide an overview of the strategies, processes, and regulatory hurdles to develop software implementing new algorithms or analyti...
BIODS237 Deep Learning in Genomics and Biomedicine Recent breakthroughs in high-throughput genomic and biomedical data are transforming biological sciences into "big data" disciplines. In parallel, progress in deep neural networks are revolutionizing fields such as image recognition, natural language...
BIODS239 Introduction to Analysis of RNA Sequence Data Introduction to analysis of RNA-sequencing data including theory and applications. Topics discussed will include computer scientific approaches to sequencing alignment such as dynamic programming, and statistical techniques that are that are used in...
BIODS240 Race, Data Algorithms, and Health This course studies the interplay between race, data and algorithms in healthcare. The particular viewpoint we want to take is to understand the role of data, data analysis and algorithms in supporting equitable delivery of health care to members of...
BIODS248-B Causal Inference in Clinical Trials and Observational Study This course offers an overview of statistical foundations for causal inference and introduces new analytic methods for causal inference in both randomized controlled trials and observational study. The covered topics include outcome regression, prope...
BIODS249 Causal Inference in Clinical Trials and Observational Study (II) This course offers an overview of statistical foundations for causal inference. This course introduces new analytic methods for causal inference in observational study including propensity score, doubly robust estimation, instrumental variables, marg...
BIODS249P Causal Inference in Clinical Trials and Observational Study (II) This course offers an overview of statistical foundations for causal inference. This course introduces new analytic methods for causal inference in observational study including propensity score, doubly robust estimation, instrumental variables, marg...
BIODS253 Software Engineering For Scientists The importance of software to science has grown tremendously over the past 20 years. Proper use of standardized Software Engineering techniques, such as cloud computing, testing, virtualization, testing, and source control, is often necessary for hig...
BIODS260A Workshop in Biostatistics Applications of data science techniques to current problems in biology, medicine and healthcare. To receive credit for one or two units, a student must attend every workshop. To receive two units, in addition to attending every workshop, the student...
BIODS260B Workshop in Biostatistics Applications of data science techniques to current problems in biology, medicine and healthcare. To receive credit for one or two units, a student must attend every workshop. To receive two units, in addition to attending every workshop, the student...
BIODS260C Workshop in Biostatistics Applications of data science techniques to current problems in biology, medicine and healthcare. To receive credit for one or two units, a student must attend every workshop. To receive two units, in addition to attending every workshop, the student...
BIODS299 Directed Reading and Research For students wishing to receive credit for directed reading or research time. Prerequisite: consent of instructor.
BIODS352 Topics in Computing for Data Science A seminar-style course with lectures on a range of computational topics important for modern data-intensive science, jointly supported by the Statistics department and Stanford Data Science, and suitable for advanced undergraduate/graduate students e...
BIODS360 Inclusive Mentorship in Data Science This course has the following broad goals: (1) To ensure that Stanford graduate students in data science are intentionally trained to effectively mentor people who may be different from them. (2) To sustainably develop pathways to increase access to...
BIODS388 Stakeholder Competencies for Artificial Intelligence in Healthcare Advancements of machine learning and AI into all areas of medicine are now a reality and they hold the potential to transform healthcare and open up a world of incredible promise for everyone. But we will never realize the potential for these technol...
BIODS399 Graduate Research on Biomedical Data Science Students undertake investigations sponsored by individual faculty members. Prerequisite: consent of instructor.
BIODS472 Data science and AI for COVID-19 This project class investigates and models COVID-19 using tools from data science and machine learning. We will introduce the relevant background for the biology and epidemiology of the COVID-19 virus. Then we will critically examine current models t...
BIODS48N Riding the Data Wave Imagine collecting a bit of your saliva and sending it in to one of the personalized genomics company: for very little money you will get back information about hundreds of thousands of variable sites in your genome. Records of exposure to a variety...