## BIODS 232: 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 consultation training for students. Data Studio is open to the Stanford community, and we expect it to have educational value for students and postdocs interested in biomedical data science. Most sessions are workshops that provide an extensive and in-depth consultation for a Medical School researcher based on research questions, data, statistical models, and other material prepared by the researcher with the aid of our facilitator. At the workshop, the researcher explains the project, goals, and needs. Experts in the area across campus will be invited and contribute to the brainstorming. After the workshop, the facilitator will follow up,helping with immediate action items and summary of the discussion. The last session of each month is devot
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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 consultation training for students. Data Studio is open to the Stanford community, and we expect it to have educational value for students and postdocs interested in biomedical data science. Most sessions are workshops that provide an extensive and in-depth consultation for a Medical School researcher based on research questions, data, statistical models, and other material prepared by the researcher with the aid of our facilitator. At the workshop, the researcher explains the project, goals, and needs. Experts in the area across campus will be invited and contribute to the brainstorming. After the workshop, the facilitator will follow up,helping with immediate action items and summary of the discussion. The last session of each month is devoted to drop-in consulting. DBDS faculty are available to provide assistance with your research questions. Skills required of practicing biomedical consultants, including exposed to biomedical and health science applications, identification of data science related questions, selection or development of appropriate statistical and analytic approaches to answer research needs. Students are required to attend the regular workshops and participate one to two consulting projects as team members under the supervision of faculty members or senior staff. Depending on the nature of the consulting service, the students may need to conduct numerical simulation, plan sample size, design study, and analyze client data. the formal written report needs to be completed at the end of consulting projects. May be repeated for credit. Prerequisites: course work in applied statistics, data analysis, and consent of instructor.

Terms: Aut, Win, Spr
| Units: 1-2
| Repeatable
2 times
(up to 4 units total)

Instructors:
Lu, Y. (PI)
;
Sabatti, C. (PI)
;
Tian, L. (PI)
;
Desai, M. (SI)
;
Efron, B. (SI)
;
Lavori, P. (SI)
;
Narasimhan, B. (SI)
;
Tamaresis, J. (SI)

## BIODS 248: Clinical Trial Design in the Age of Precision Medicine and Health (BIODS 248P, BIOMEDIN 248, STATS 248)

Overview of requirements, designs, and statistical foundations for traditional Phase I, II, and III clinical trials for medical product approval and Phase IV postmarketing studies for safety evaluation. As these methods cost too much and take too much time in the era of precision medicine and precision health, this course then introduces innovative designs that have been developed for affordable clinical trials, which can be completed within reasonable time constraints and which have been encouraged by regulatory agencies. Prerequisites: Working knowledge of statistics and R.

Terms: Spr
| Units: 3
| Repeatable
2 times
(up to 6 units total)

## BIODS 248P: Clinical Trial Design in the Age of Precision Medicine and Health (BIODS 248, BIOMEDIN 248, STATS 248)

Overview of requirements, designs, and statistical foundations for traditional Phase I, II, and III clinical trials for medical product approval and Phase IV postmarketing studies for safety evaluation. As these methods cost too much and take too much time in the era of precision medicine and precision health, this course then introduces innovative designs that have been developed for affordable clinical trials, which can be completed within reasonable time constraints and which have been encouraged by regulatory agencies. Prerequisites: Working knowledge of statistics and R.

Terms: Spr
| Units: 3
| Repeatable
2 times
(up to 6 units total)

## BIODS 260C: Workshop in Biostatistics (STATS 260C)

Applications of statistical techniques to current problems in medical science. 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 is required to write an acceptable one page summary of two of the workshops, with choices made by the student.

Terms: Spr
| Units: 1-2
| Repeatable
for credit

Instructors:
Palacios, J. (PI)
;
Zou, J. (PI)

## BIODS 299: Directed Reading and Research

For students wishing to receive credit for directed reading or research time. Prerequisite: consent of instructor.

Terms: Aut, Win, Spr, Sum
| Units: 1-18
| Repeatable
for credit

Instructors:
Bustamante, C. (PI)
;
Efron, B. (PI)
;
Hastie, T. (PI)
...
more instructors for BIODS 299 »

Instructors:
Bustamante, C. (PI)
;
Efron, B. (PI)
;
Hastie, T. (PI)
;
Lu, Y. (PI)
;
Olshen, R. (PI)
;
Palacios, J. (PI)
;
Plevritis, S. (PI)
;
Rivas, M. (PI)
;
Sabatti, C. (PI)
;
Salzman, J. (PI)
;
Tian, L. (PI)
;
Tibshirani, R. (PI)
;
Yeung, S. (PI)
;
Zou, J. (PI)

## BIODS 360: 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 higher education and to Stanford graduate programs in data science for individuals from backgrounds currently under-represented in those fields. During weekly class meetings, graduate student participants will learn strategies to create an inclusive environment, approaches to effective mentoring and coaching, and techniques to develop a personalized curriculum with the course staff and guest speakers. They will also be paired with current undergraduates from non-R1 schools with an interest in data science, recruited in partnership with faculty from those institutions. Participants will meet online weekly for one-on-one mentorship where you will expose your mentee to research in data science. During weekly online meetings, you will work with
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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 higher education and to Stanford graduate programs in data science for individuals from backgrounds currently under-represented in those fields. During weekly class meetings, graduate student participants will learn strategies to create an inclusive environment, approaches to effective mentoring and coaching, and techniques to develop a personalized curriculum with the course staff and guest speakers. They will also be paired with current undergraduates from non-R1 schools with an interest in data science, recruited in partnership with faculty from those institutions. Participants will meet online weekly for one-on-one mentorship where you will expose your mentee to research in data science. During weekly online meetings, you will work with your mentee on a range of activities, planned with assistance from course staff, including planning their course of studies, navigating internship opportunities and preparing applications; tutoring in some aspects of data science; and guidance in engaging in mini-research projects, depending on their interests.

Terms: Spr
| Units: 1
| Repeatable
2 times
(up to 2 units total)

## BIODS 399: Graduate Research on Biomedical Data Science

Students undertake investigations sponsored by individual faculty members. Prerequisite: consent of instructor.

Terms: Aut, Win, Spr, Sum
| Units: 1-18
| Repeatable
for credit

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