Scientific Computing
- Product type
Scientific Computing
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Description
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Investigate the flexibility and power of project-oriented computational analysis, and enhance communication of information by creating visual representations of scientific data.
About the Course
Investigate the flexibility and power of project-oriented computational analysis. Practice using this technique to resolve complicated problems in a range of fields including the physical and engineering sciences, finance and economics, medical, social and biological sciences. Enhance communication of information by creating visual representations of scientific data.This course is a survey of numerical solution techniques for ordinary and partial differential equations. Emphasis will be on the appl…
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When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan .
- Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
- Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.
Investigate the flexibility and power of project-oriented computational analysis, and enhance communication of information by creating visual representations of scientific data.
About the Course
Investigate the flexibility and power of project-oriented computational analysis. Practice using this technique to resolve complicated problems in a range of fields including the physical and engineering sciences, finance and economics, medical, social and biological sciences. Enhance communication of information by creating visual representations of scientific data.This course is a survey of numerical solution techniques for ordinary and partial differential equations. Emphasis will be on the application of numerical schemes to practical problems in the engineering and physical sciences. Apply advanced MATLAB routines and toolboxes to solve problems. Review and practice graphical techniques for information presentation and learn to create visual illustrations of scientific results
About the Instructor(s)
J. Nathan Kutz PhD, Applied Mathematics, Northwestern UniversityJ. Nathan Kutz specializes in a unified approach to applied mathematics including modeling, computation and analysis. His current focus is phenomena in dimensionality reduction and data-analysis techniques for complex systems. This includes work in laser dynamics and modelocking in fiber lasers, neuro-sensory systems and theoretical neuroscience, and gesture recognition algorithms for portable electronic devices. Kutz has authored numerous scientific articles on these subjects as well as segments of books devoted to his area of expertise.
Recommended Background
To be successful in the course, a strong background in linear algebra is required. Familiarity with methods of ordinary differential equations and basic programming structure is also required. With this background, students should be able to develop the codes necessary for the homework in the course.Given the computational nature of the course, access to MATLAB (www.mathworks.com) or Octave (www.gnu.org/software/octave) is essential. Octave is a free (or by donation) alternative to MATLAB that can also be downloaded and installed via the web. Either software should suffice for all the needs of the course, but MATLAB is the strongly recommended alternative.
Provided by:
University: University of Washington
Instructor(s): J. Nathan Kutz
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