LibGuides: Data-related Educational Opportunities at OHSU: Courses

Courses

BMI 509/609: Practicum - Biomedical Informatics
A practical hands-on experience in an operational biomedical informatics setting at OHSU, a local health software vendor, or a hospital/health system.

Contact(s): Unknown
Location: Unknown
Intended audience: Students
Experience Level: N/A
Restrictions on attendance: Prerequisites: 50X Form, Consent of Internship Coordinator.
Internal or external resource: Internal
Facilitated or Self-Guided: Both
Regularity or occurrence: TBD
Duration: N/A
Keywords: Medical Informatics, software
Cost/Fees: OHSU Tuition & Fees

BMI 510/610: Introduction to Biomedical and Health Informatics
An introduction to the fundamental principles of biomedical informatics, the field concerned with the acquisition, storage, and use of information in health and biomedicine. The course begins with a basic introduction to health and biomedicine as well as computing concepts. It then surveys aspects of electronic health records, decision support systems, standards, security and confidentiality, evidence-based medicine, information retrieval, bioinformatics, public health informatics, imaging informatics, nursing informatics and consumer health informatics.

Contact(s): William Hersh, M.D.
Location: Online
Intended audience: Students
Experience Level: Beginner
Restrictions on attendance: None
Internal or external resource: Internal
Facilitated or Self-Guided: Facilitated
Regularity or occurrence: Last Winter 2022; Fall, Winter, Spring, Summer
Duration: 01/03/2022 to 03/18/2022
Keywords: Electronic Health Records, Consumer Health Informatics, Computational Biology, Nursing Informatics, Public Health Informatics, Information Storage and Retrieval
Cost/Fees: OHSU Tuition & Fees

HIP 512A Biostatistics with STATA
Consists of a series of tutorials showing trainees how to analyze data using the statistical software program STATA. Trainees can work through individual tutorials on their own and at their own pace. They can attend office hours, held weekly, for help on completing the assignment.

Contact(s): Jennifer Lucas, Ph.D., M.P.H
Location: Unknown
Intended audience: Trainees
Experience Level: N/A
Restrictions on attendance: Prerequisitse: Must have completed HIP 511, 512 or have otherwise received permission. Contact the HIP program.
Internal or external resource: Internal
Facilitated or Self-Guided: Self-Guided
Regularity or occurrence: Any term
Duration: N/A
Keywords: Biostatistics, Software
Cost/Fees: OHSU Tuition & Fees

HIP 517 Scientific Writing and Data Presentation
Success in clinical research rests on the researcher’s ability to communicate the findings of research clearly and effectively. The purpose of this course is to provide insight into the peer-reviewed journal process in clinical medicine and surgery. The trainee also gains an understanding of the elements of clinical science writing that are expected in peer-reviewed publications. The topics covered include elements of the clinical science paper; writing the paper from concept to manuscript; defining the peer-reviewed literature; finding appropriate and best journals for submission; elements of peer review including how to review and how to respond to reviewers’ comments. This module also explores the art of oral presentation of scientific data.

Contact(s): Patricia Carney, Ph.D. and Rachel Dresbeck, Ph.D.
Location: Unknown
Intended audience: Unknown
Experience Level: N/A
Restrictions on attendance: None
Internal or external resource: Internal
Facilitated or Self-Guided: N/A
Regularity or occurrence: Winter term
Duration: 6 weeks
Keywords: Clinical Medicine, Writing, Communication
Cost/Fees: OHSU Tuition & Fees

HIP 520 Medical Informatics
Course topics include fundamentals of medical computing, electronic medical records, data interchange and terminology standards, information retrieval from databases, security and confidentiality, and bioinformatics. The course consists of on-line lectures with assignments that include hands-one use of electronic medical records, decision support applications, and information retrieval systems; reading assignments; and threaded on-line discussions.

Contact(s): William Hersh, M.D.
Location: Online
Intended audience: Unknown
Experience Level: N/A
Restrictions on attendance: N/A
Internal or external resource: Internal
Facilitated or Self-Guided: Unknown
Regularity or occurrence: Summer term
Duration: 7 sessions
Keywords: Medical Informatics, Computational Biology, Information Systems, Electronic Health Records
Cost/Fees: OHSU Tuition & Fees

BMI 524/624: Analytics for Healthcare
This course is a broad overview of how analytics is used in healthcare settings. We attempt to cover the process, infrastructure needs, tools, skills, organization, people and governance to effectively perform this work in a healthcare organization. We do not focus on particular quantitative methodologies and therefore our course should be considered 'non-technical'. Instead we provide a broad overview of the field with exposure to several common tools and software packages.

Contact(s): Abhijit Pandit, M.B.A. & Tracy Edinger, N.D.
Location: Online
Intended audience: CI-major students
Experience Level: Beginner
Restrictions on attendance: No
Internal or external resource: Internal
Facilitated or Self-Guided: Facilitated
Regularity or occurrence: Spring 2021
Duration: 03/29/2021 to 06/18/2021
Keywords: Data Mining, Data Science, Software
Cost/Fees: OHSU Tuition & Fees

BMI 525/625: Principles and Practice of Data Visualization
This course will give students a foundation in the principles of data visualization, particularly as applied to scientific and technical data, as well as provide students with hands-on experience using modern software tools for developing visualizations. Lecture topics will include an overview of visual perception, color theory and practice, different types of graphs and their purposes, visualizations for specialized forms of data including time-series and geospatial data sets, strategies for working with multidimensional data, etc.

Contact(s): Steven Bedrick, Ph.D.
Location: Online
Intended audience: Students
Experience Level: Beginner
Restrictions on attendance: Prerequisites: Ready for R
Internal or external resource: Internal
Facilitated or Self-Guided: Facilitated
Regularity or occurrence: Spring 2021
Duration: 03/29/2021 to 06/18/2021
Keywords: Data Visualization, Visual Perception, Computer Graphics, Software
Cost/Fees: OHSU Tuition & Fees

BMI 527/627: Applied Data Science and Machine Learning
This course is an overview of the application of data science, machine learning, and artificial intelligence in health care settings. Students will be introduced to a wide range of machine learning topics, including identifying health care issues that can be addressed with machine learning solutions, machine learning model development and data source identification, machine learning model implementation, critical appraisal of machine learning literature, and ethical considerations for the application of machine learning and artificial intelligence in health care. Students will also identify an issue in health and develop their own machine learning model to address this issue.

Contact(s): Steven Chamberlin, N.D. and William Hersh, M.D.
Location: Online
Intended audience: Students
Experience Level: N/A
Restrictions on attendance: Prerequisite: BMI 540 or instructor's permission
Internal or external resource: Internal
Facilitated or Self-Guided: Facilitated
Regularity or occurrence: Spring 2021
Duration: 03/29/2021 to 06/18/2021
Keywords: Artificial Intelligence, Data Science, Information Storage and Retrieval, Machine Learning
Cost/Fees: OHSU Tuition & Fees

HIP 528 Applied Biostatistics I
Didactic learning paired with experience in use of statistical software. This course, expanding on topics explored in the HIP 511/512/513 course series, will focus on multivariable methods widely used in clinical research: linear regression, logistic regression, survival analysis, and repeated measures analysis.

Contact(s): Barbara BrumBach, Ph.D.
Location: Unknown
Intended audience: Unknown
Experience Level: N/A
Restrictions on attendance: Prerequisites: HIP 511, 512, 513 and HIP 512A Biostatistics Tutorial in Stata
Internal or external resource: Internal
Facilitated or Self-Guided: Facilitated
Regularity or occurrence: Winter term/Class sessions held for three hours each, one day a week.
Duration: 11 weeks
Keywords: Biostatistics, Software, Logistic Models, Linear Models
Cost/Fees: OHSU Tuition & Fees

BMI 531/631: Probability and Statistical Inference
This course will introduce fundamental concepts underlying statistical data visualization, analysis, inference and statistical decision making. The topics include presentation and description of data, basic concepts of probability, Bayes theorem, discrete and continuous probability distributions, estimation, sampling distributions, classical tests of hypotheses on means, variances and proportions, maximum likelihood estimation, Bayesian inference and estimation, linear models, examples of nonlinear models and introduction to simple experimental designs. One of the key notions underlying this course is the role of mathematical modeling in science and engineering with a particular focus on the need for understanding of variability and uncertainty. Examples are chosen from a wide range of bioinformatics and computational biology topics.

Contact(s): Steven Chamberlin, N.D., M.S.
Location: Unknown
Intended audience: Students
Experience Level: N/A
Restrictions on attendance: The most important prerequisite for this course is familiarity with multivariate calculus, and some linear algebra and matrix operations. Some homework will also require a computer and familiarity with R. It is recommended to take a class in R, such as R Bootcamp or Ready for R offered from the Department of Medical Informatics and Clinical Epidemiology.
Internal or external resource: Internal
Facilitated or Self-Guided: Facilitated
Regularity or occurrence: Fall 2021
Duration: 09/27/2021 to 12/17/2021
Keywords: Data Visualization, Computational Biology, Statistical Models
Cost/Fees: OHSU Tuition & Fees

BMI 533/633: Data Harmonization and Standards for Translational Research
The goal of this course is to provide an overview of the data types and data standards needed to effectively integrate both clinical and biological data in the context of current translational research. The five main focus areas will be 1) data structures and ontologies, 2) EHR standards, data types and usage, 3) reference genome annotation formats and standards, 4) integration of genotype and phenotype data, and 5) clinical trials data standards.

Contact(s): Melissa Haendel, Ph.D., Ted Laderas, Ph.D., Christina Zheng, Ph.D.
Location: TBD
Intended audience: Students
Experience Level: N/A
Restrictions on attendance: Prerequisite: BMI 569/669
Internal or external resource: Internal
Facilitated or Self-Guided: Facilitated
Regularity or occurrence: Unknown
Duration: Unknown
Keywords: Biostatistics, Data Science
Cost/Fees: OHSU Tuition & Fees

BMI 535/635: Management and Processing of Large Scale Data
The goal of this course is to provide an introduction to the data management and data processing applications available for large scale data. Utilizing samples from the 1000 Genomes Project, this course will provide hands-on experience managing and processing large scale data. Topics covered include SQL, NoSQL, distributed file systems and parallel computing.

Contact(s): Michael Mooney, Ph.D and Ted Laderas, Ph.D
Location: On Campus
Intended audience: Students
Experience Level: N/A
Restrictions on attendance: Prerequisites: BMI 565/665, BMI 550/650, familiarity with Linux
Internal or external resource: Internal
Facilitated or Self-Guided: Facilitated
Regularity or occurrence: Winter 2022
Duration: 01/03/2022 to 03/18/2022
Keywords: Big Data, Data Management, Software, Computational Biology
Cost/Fees: OHSU Tuition & Fees

BMI 544/644: Databases
An in-depth look at databases and database management systems. Topics covered will include data modeling, hierarchical and relational databases, query languages (SQL), database optimization, and OLAP and data warehousing

Contact(s): Michael Lieberman, M.D.
Location: Online
Intended audience: Admitted Biomedical Informatics students
Experience Level: N/A
Restrictions on attendance: No prerequisite, but prior completion of BMI 540 suggested.
Internal or external resource: Internal
Facilitated or Self-Guided: Facilitated
Regularity or occurrence: Winter
Duration: N/A
Keywords: Data Warehousing, Database Management Systems, Programming Languages, Factual Databases
Cost/Fees: OHSU Tuition & Fees

BMI 550/650: Bioinformatics and Computational Biology I: Algorithms
The course will be a problem-driven examination of the algorithmic issues in computational biology. The course will provide students with the computational fundamentals underlying the techniques covered. Students will be expected to learn basic algorithm principles, basic mathematical and statistical proofs, and molecular biology. The emphasis is on algorithm development and application to biological problems, particularly those from functional genomics studies.

Contact(s): James Jacobs, M.D.
Location: Undecided
Intended audience: Students
Experience Level: N/A
Restrictions on attendance: Introductory programming course required or instructor's permission.
Internal or external resource: Internal
Facilitated or Self-Guided: Facilitated
Regularity or occurrence: Fall 2021
Duration: 09/27/2021 to 12/17/2021
Keywords: Bioinformatics, Computational Biology, Genomics, Algorithms
Cost/Fees: OHSU Tuition & Fees

BMI 551/651: Bioinformatics and Computational Biology II: Statistical Methods
This course will be a problem-driven examination of the quantitative issues in computational biology. The course will provide students with the statistical fundamentals underlying the techniques covered. Topics will include applications involving MCMC Models, Maximum Likelihood, Random Walks, Hidden Markov Models, Estimating Genealogical Relationships and Networks.
Location: On Campus

Contact(s): James Jacobs, M.D.
Location: On Campus
Intended audience: Students
Experience Level: N/A
Restrictions on attendance: Non-BMI students require instructor's permission
Internal or external resource: Internal
Facilitated or Self-Guided: Facilitated
Regularity or occurrence: Winter 2022
Duration: 01/03/2022 to 03/18/2022
Keywords: Bioinformatics, Computational Biology
Cost/Fees: OHSU Tuition & Fees

BMI 560/660: Design and Evaluation in Health Informatics
This course provides an overview of the concepts, vocabularies, and strategies needed to design and evaluate projects in biomedical informatics, including a breadth of methodologies drawn from qualitative research, quantitative research, and software engineering.

Contact(s): Vishnu Mohan, M.D., M.B.I., FACP, FAMIA
Location: Unknown
Intended audience: Recommended for students in their first year of the program with DMICE.
Experience Level: N/A
Restrictions on attendance: Prerequisites: BSTA 525 (formerly PHPM 524) or BSTA 511/611, and working knowledge of Excel or consent of instructor.
Internal or external resource: Internal
Facilitated or Self-Guided: Facilitated
Regularity or occurrence: Winter 2021
Duration: 01/04/2021 to 03/19/2021
Keywords: Medical Informatics, Software, Qualitative Research
Cost/Fees: OHSU Tuition & Fees

BMI 565/665: Bioinformatics Programming and Scripting
The purpose of this course is to equip research scientists with computational skills necessary to create and automate tools to analyze biological data. The course is divided into four sub-topics: python programming, scripting in unix, biopython library, bioinformatics workflows. In addition, students will learn to access public repositories to perform basic bioinformatics tasks such as annotating gene products, sequence searching, and functional queries.

Contact(s): Michael Mooney, Ph.D.
Location: On Campus
Intended audience: Students
Experience Level: N/A
Restrictions on attendance: Prerequisites: This course is designed to be a first year requirement for students in the Bioinformatics and Computational Biology graduate program in Biomedical Informatics. Open to other students with consent of instructor. Background must include an introductory programming class including concepts such as variables, loops, I/O, methods, and algorithms.
Internal or external resource: Internal
Facilitated or Self-Guided: Facilitated
Regularity or occurrence: Fall 2021
Duration: 09/27/2021 to 12/17/2021
Keywords: Computational Biology, Software
Cost/Fees: OHSU Tuition & Fees

BMI 569/669: Data Analytics
Data Analytics is an applied hybrid course that introduces the concepts of the data analytics life cycle through the implementation of a quality metric. Through this implementation, we explore the role of analysts and analytics in healthcare organizations.

Contact(s): Lauren Ludwig; ludwigl@ohsu.edu
Location: Hybrid
Intended audience: Students
Experience Level: N/A
Restrictions on attendance: Prerequisites: (BMI 540 or 565) and (BSTA 525 or BSTA 511 or MATH 530). Experience with R (or other scripted statistical language), SQL, and spreadsheets a positive. Students must bring a laptop to class.
Internal or external resource: Internal
Facilitated or Self-Guided: Facilitated
Regularity or occurrence: TBD
Duration: N/A
Keywords: Data Science, Data Mining, Statistical Data Analysis
Cost/Fees: OHSU Tuition & Fees

CS 527/627: Data Science Programming
Familiarization with UNIX/LINUX environment, learn how to version control files with git, write programs in python, perform numeric tasks using numpy and scipy, analyze data using pandas, apply machine learning algorithms using scikit-learn, visualize data using matplotlib and pyqtgraph, use QT/pyside to build graphical user interfaces, and finally we will address performance issues via compilation/profiling/parallelization tools.

Contact(s): Alexander Kain (Instructor): kaina@ohsu.edu
Location: Online
Intended audience: Students
Experience Level: Beginner
Restrictions on attendance: N/A
Internal or external resource: Internal
Facilitated or Self-Guided: Facilitated
Regularity or occurrence: Last happened Spring 2020
Duration: Unknown
Keywords: Algorithms, Data Science, Machine Learning, Software
Cost/Fees: OHSU Tuition & Fees

CS 631 Data Visualization
The purpose of this course is to equip research scientists with computational skills necessary to create and automate tools to analyze biological data. The course is divided into four sub-topics: python programming, scripting in unix, biopython library, bioinformatics workflows. In addition, students will learn to access public repositories to perform basic bioinformatics tasks such as annotating gene products, sequence searching, and functional queries.

Contact(s): Steven Bedrick (Instructor)
Location: Online
Intended audience: Students
Experience Level: Beginner
Restrictions on attendance: Prerequisites: This course is designed to be a first year requirement for students in the Bioinformatics and Computational Biology graduate program in Biomedical Informatics. Open to other students with consent of instructor. Background must include an introductory programming class including concepts such as variables, loops, I/O, methods, and algorithms.
Internal or external resource: Internal
Facilitated or Self-Guided: Facilitated
Regularity or occurrence: Last happened Spring 2020
Duration: Unknown
Keywords: Data visualization, Visual Perception, Computer Graphics
Cost/Fees: OHSU Tuition & Fees

CS 635 Information Retrieval
Information retrieval methodologies and applications; covers the various computational and methodological aspects of search, both over textual data as well as multimedia data.

Contact(s): Steven Bedrick (Instructor)
Location: Unknown
Intended audience: Students
Experience Level: Beginner
Restrictions on attendance: N/A
Internal or external resource: Internal
Facilitated or Self-Guided: Facilitated
Regularity or occurrence: Last happened Spring 2021
Duration: Unknown
Keywords: Data Collection, Data Science, Information Storage and Retrieval, Multimedia
Cost/Fees: OHSU Tuition & Fees

HIP 529 Applied Biostatistics II
This course explores some advanced biostatistics topics that are widely used in health sciences research, including categorical data modeling procedures, methods for missing data, meta-analysis and others.

Contact(s): hip@ohsu.edu
Location: Unknown
Intended audience: Students
Experience Level: N/A
Restrictions on attendance: Prerequisites: HIP 511, 512, 513, HIP 512A: Biostatistics Tutorial and HIP 528
Internal or external resource: Internal
Facilitated or Self-Guided: Facilitated
Regularity or occurrence: Spring Term/Class sessions held for three hours each, one day a week
Duration: 11 weeks
Keywords: Biostatistics
Cost/Fees: OHSU Tuition & Fees

CS/EE 679 Problem Solving with Large Clusters
Solving computational problems involving data sets like analysis of high-throughput genomic or proteomic data,data analytics over very large data sets, large-scale social network analysis, training machine learning models on "web scale" data sets, etc.

Contact(s): Steve Bedrick (Instructor)
Location: Unknown
Intended audience: Unknown
Experience Level: Advanced
Restrictions on attendance: Prerequisites: A graduate level course on machine learning or probability and statistics. Students should be comfortable coding in at least one programming language, and familiar with the UNIX command-line environment.
Internal or external resource: Internal
Facilitated or Self-Guided: Facilitated
Regularity or occurrence: Last happened Winter 2018
Duration: Unknown
Keywords: Data Science, Proteomics, Social Network Analysis, Machine Learning, Computational Biology
Cost/Fees: OHSU Tuition & Fees

Data Science for Clinical and Translational Research
This course provides an introduction to principles of clinical research informatics, including use of data sources such as clinical information systems, data management, collection and storage of clinical data, database design, and data security. This includes exercises in working with data to answer clinical questions. Course objectives include developing skills and comfort skills and comfort to construct and implement a data collection, management, and secure storage plan for clinical data; and developing the facility with clinical data to wrangle data to answer questions and test hypotheses.

Contact(s): Cynthia Morris, Ph.D., M.P.H. (Course Director)
Location: Unknown
Intended audience: Clinicians
Experience Level: Unknown
Restrictions on attendance: Unknown
Internal or external resource: Internal
Facilitated or Self-Guided: Facilitated
Regularity or occurrence: Fall term
Duration: 7 weeks
Keywords: Computer Security, Data Management, Information Systems, Informatics
Cost/Fees: OHSU Tuition & Fees

UNI 504: Qualitative Methods for Health Professionals
Students will work in interprofessional teams to plan for and engage in basic data collection and analysis, with a focus on study design, sampling and selection, budgeting for qualitative tasks, data management, coding, content analysis and reporting.

Contact(s): Lisa Marriott, Ph.D.
Location: Unknown
Intended audience: Students
Experience Level: Beginner
Restrictions on attendance: N/A
Internal or external resource: Internal
Facilitated or Self-Guided: Facilitated
Regularity or occurrence: Winter and Spring terms
Duration: Unknown
Keywords: Data Analysis, Data Collection, Data Management, Qualitative Research
Cost/Fees: OHSU Tuition & Fees