Courses taught by Guanglan Zhang

The goal of this course is to provide students with the mathematical and practical background required in the field of data analytics. Starting with an introduction to probability and statistics, the R tool is introduced for statistical computing and graphics. Different types of data are investigated along with data summarization techniques and plotting. Data populations using discrete, continuous, and multivariate distributions are explored. Errors during measurements and computations are analyzed in the course. Confidence intervals and hypothesis testing topics are also examined. The concepts covered in the course are demonstrated using R. Laboratory Course.

This course provides an overview of the statistical tools most commonly used to process, analyze, and visualize data. Topics include simple linear regression, multiple regression, logistic regression, analysis of variance, and survival analysis. These topics are explored using the statistical package R, with a focus on understanding how to use and interpret output from this software as well as how to visualize results. In each topic area, the methodology, including underlying assumptions and the mechanics of how it all works along with appropriate interpretation of the results, are discussed. Concepts are presented in context of real world examples.

This course presents the fundamental principles, concepts, and technological elements that make up the building blocks of Health Informatics. It introduces fundamental characteristics of data, information, and knowledge in the domain, the common algorithms for health applications, and IT components in representative clinical processes. It also introduces the conceptual framework for handling the collection, storage and the optimal use of biomedical data. It covers basic principles of knowledge management systems in biomedicine, various aspects of Health Information Technology standards, and IT aspects of clinical process modeling. There is also a term project to access students' ability to understand and implement simple Health Informatics solutions.

This course presents the details of health care data and information, health care information systems (HCIS), and the management of information technology (IT) challenges. The first part of the course introduces data, information, regulations, laws, and standards related to health care. The second part covers the history of HCISs, the technologies behind them, the details of HCIS acquisition, development, implementation and support, and HCIS standards and security issues. The last part starts with an introduction to the roles, responsibilities, and functions of the IT staff and services in health care environment, followed by topics on organizing IT services and staff, the development of IT strategic plans, and IT budgeting. The course has a term project providing students a hands-on experience in HCIS design and research. Two or three health IT leaders and experts will be invited as guest lectures to share their first-hand experience with us.

This course provides students with a comprehensive overview of the principles, processes, and practices of software project management. Students learn techniques for planning, organizing, scheduling, and controlling software projects. There is substantial focus on software cost estimation and software risk management. Students will obtain practical project management skills and competencies related to the definition of a software project, establishment of project communications, managing project changes and managing distributed software teams and projects. We also focus on the Project Management Body of Knowledge (PMBOK) as a framework in this course. This is now a world-wide de facto standard for project management and recommended by IEEE and ANSI as well for their project management standard.