Online courses directory (684)

Learn the essential exploratory techniques for summarizing data. This is the fourth course in the Johns Hopkins Data Science Specialization.

Exploring geographic information systems (GIS) is a self-paced course where participants will learn about GIS and how the technology is being used in the real world to support problem-solving and decision-making. Participants will create and manage spatial databases, produce well-designed maps, and undertake spatial data analysis using free online software tools. These activities require proficiency in fundamental computer and Internet skills. Participants will have the opportunity to obtain digital badges throughout the course. This course is offered through Canvas Network as a non-credit course created by Simon Fraser University. Students enrolled in only this course are not considered students of Simon Fraser University.

This course provides an introduction to the design of feedback systems. Topics covered include: properties and advantages of feedback systems, time-domain and frequency-domain performance measures, stability and degree of stability, root locus method, Nyquist criterion, frequency-domain design, compensation techniques, application to a wide variety of physical systems, internal and external compensation of operational amplifiers, modeling and compensation of power converter systems, and phase lock loops.

This course is an introduction to the theory and practice of financial engineering and risk management. We consider the pricing of derivatives, portfolio optimization and risk management and cast a critical eye on how these are used in practice. We will also feature some interview modules with Emanuel Derman .

This subject describes and illustrates computational approaches to solving problems in systems biology. A series of case-studies will be explored that demonstrate how an effective match between the statement of a biological problem and the selection of an appropriate algorithm or computational technique can lead to fundamental advances. The subject will cover several discrete and numerical algorithms used in simulation, feature extraction, and optimization for molecular, network, and systems models in biology.

This is a foundation subject in modern software development techniques for engineering and information technology. The design and development of component-based software (using C# and .NET) is covered; data structures and algorithms for modeling, analysis, and visualization; basic problem-solving techniques; web services; and the management and maintenance of software. Includes a treatment of topics such as sorting and searching algorithms; and numerical simulation techniques. Foundation for in-depth exploration of image processing, computational geometry, finite element methods, network methods and e-business applications. This course is a core requirement for the Information Technology M. Eng. program.

This class was also offered in Course 13 (Department of Ocean Engineering) as 13.470J. In 2005, ocean engineering subjects became part of Course 2 (Department of Mechanical Engineering), and the 13.470J designation was dropped in lieu of 2.159J.

This course introduces concepts, algorithms, programming, theory and design of spatial computing technologies such as global positioning systems (GPS), Google Maps, location-based services and geographic information systems. Learn how to collect, analyze, and visualize your own spatial datasets while avoiding common pitfalls and building better location-aware technologies.

When developing chips it is essential that they get verified thoroughly because it is very hard or impossible to fix them once they have been manufactured. In this class, you will learn how to program verification environments that verify chip functionality efficiently, as well as understand and leverage automation such as constrained random test generation and improve code reuse leveraging a standardized methodology.

This team-taught multidisciplinary course provides information relevant to the conduct and interpretation of human brain mapping studies. It begins with in-depth coverage of the physics of image formation, mechanisms of image contrast, and the physiological basis for image signals. Parenchymal and cerebrovascular neuroanatomy and application of sophisticated structural analysis algorithms for segmentation and registration of functional data are discussed. Additional topics include: fMRI experimental design including block design, event related and exploratory data analysis methods, and building and applying statistical models for fMRI data; and human subject issues including informed consent, institutional review board requirements and safety in the high field environment.

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