Approved Courses
For students enrolled prior to 2024, participation in at least 7-9 data-science specific seminars (1 semester) to enrich their formal didactic training is required. These seminar series could be from different schools, Institutes, Initiatives, Centers, etc. Seminar attendance should be recorded on this log.
Click on the button below to view all courses approved for the Graduate Data Science Certificate. This list is sorted by course code. You may use temporary filters to view Foundation courses, Applications courses and Electives, and sort the list.
Approved Course listDon’t see a course you think would fit? Request approval for a course for your certificate.
Examples of Course Selection Pathways
Below are examples of possible curricular paths through the Graduate Certificate for Data Science program based on a student’s prior experience. This is intended to illustrate, not limit, the scope of candidates, or courses they can take to complete the program and obtain the certificate.
- Any field, no programming or statistics experience
- SI 506 Programming I (Applications)
- SI 507 Intermediate Programming (Applications)
- SI 544 Introduction to Statistics (Foundations)
- Any field, some self-taught programming (like the Python 3 series), no statistics experience
- SI 507 Intermediate Programming (Applications)
- SI 544 Introduction to Statistics (Foundations)
- SI 618 Data Manipulation & Analysis (Applications/Foundations)
- For students with some programming and undergraduate math experience, grouped by research interests:
- Earth/atmosphere and geosciences
- SPACE 423: Data Analysis and Visualization for Geoscientists (Foundations)
- BIOSTAT 696: Spatial Statistics (Applications/Foundations)
- ENVIRON 473: Statistical Modeling and Data Visualization in R (Applications)
- Health sciences
- LHS 610: Exploratory Data Analysis for Health (Foundations)
- BIOSTAT 521: Applied Biostatistics I (Foundations/Applications)
- EPID 633: Introduction to Mathematical Modeling (Applications)
- Biological sciences
- STATS 415: Data Mining and Statistical Learning (Foundations)
- BIOINF 597: Artificial Intelligence for Medicine and Biomedical Sciences (Applications)
- EECS 545: Machine Learning (Foundations/Applications)
- Education
- LHS 631: Learning Analytics: Foundations and Applications (Electives)
- SI 618: Data Manipulation & Analysis (Foundations)
- SI 630: Natural Language Processing: Algorithms and People (Applications)
- Humanities
- SI 630: Natural Language Processing: Algorithms and People (Foundations)
- SI 649: Information Visualization (Electives)
- SI 608: Networks: Theory and Application (Applications)
- Materials sciences & engineering
- EECS 545: Machine Learning (Foundations/Applications)
- CSE 549: Information Retrieval (Foundations/Applications)
- PHYSICS 514: Computational Physics (Electives)
- Earth/atmosphere and geosciences
BIDS-TP Fellows & Trainees
The University of Michigan T32 Biomedical Informatics and Data Science Training Program (BIDS-TP) trains data-savvy, computationally skilled, and highly motivated biomedical scholars through the development of an intellectually stimulating environment and implementation of an effective competency-based curriculum. To enhance their scientific, clinical, and translational abilities, all BIDS-TP students will be trained in collecting, managing, processing, interrogating, and analyzing large amounts of complex high-dimensional biomedical information with rigor and transparency.
Annually, the Program makes 2-year appointments to support 8 Fellows (fully funded by this T32 program) and up to 8 Trainees (independently funded). The BIDS-TP program represents a unique collaboration between the UM’s Department of Computational Medicine and Bioinformatics (DCMB) and the Michigan Institute for Data & AI in Society (MIDAS). This partnership will provide immersive synergistic activities, translational education, transdisciplinary research projects, co-mentoring, and career development for all BIDS-TP trainees. Feeder graduate programs with eligible pre-doctoral trainees include DCMB and MIDAS doctoral students from engineering, mathematics, statistics, public health, and information sciences.
Over 40 UM faculty members from 8 UM Schools provide breadth and depth of scholarly co-mentoring, career coaching, and student-specific curriculum development. The competency-based BIDS-TP curriculum requires all trainees to complete the add-on MIDAS-administered and Rackham Graduate School-accredited graduate data science certificate program and actively participate in BIDS-TP workshops, seminars, and short courses on health analytics, biomedical informatics, and computational data science. The Program emphasizes foundational understanding of complex experimental designs, computational inference, data-driven decision-making, and advanced health analytics.
All UM doctoral students enrolled in the Rackham Certificate Program are eligible to apply for BIDS-TP. Funded Fellowship slots require US citizenship/PR. Both Fellows and Trainees are fully, actively, and equally engaged in BIDS Program activities. Application procedure and other logistics are available on the BIDS-TP website.
MIDAS Certificate Assistant
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