Investigate the flexibility and power of project-oriented computational analysis, and enhance communication of information by creating visual representations of scientific data.
Thank you for joining the Scientific Computing course! Please take a few moments to read through the course welcome page followed by watching the introductory and week one lecture videos. There is a lot of useful information there about the course.
For now, you should plan to allocate between five and 10 hours per week on the course. There will be roughly two hours of lectures per week, as well as weekly quizzes (graded automatically) for each lecture.
In this course you will learn how to recognize and solve numerically practical problems which may arise in your research. Given the computational nature of the course, access to MATLAB (www.mathworks.com) or Octave (www.gnu.org/software/octave) is essential. MATLAB provides student editions for $99 that can be downloaded via the web. 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.
To complement the course, a set of notes detailing each individual lecture is included. The notes should be read through thoroughly and routinely as all the course content is contained therein. It is imperative that the student engage in a focused effort to learn the notes as the lectures are simply a supplement to the notes, not the other way around. You are also encouraged to interact with each other within the discussion forums in order to arrive at the various solution sets.
Again, welcome, and I hope that you enjoy this course!
Dr. Nathan Kutz
Mon 7 Jan 2013 12:01 AM PST
Welcome to Week 1 of Scientific Computing!
Scientific computing surveys practical solution techniques for differential equations. Week 1 begins by exploring methods to numerically approximate and solve ordinary differential equations. In Lecture 1 some time-stepping methods for approximating and solving ordinary differential equations are derived. Lecture 2 goes over analyzing stability and accuracy of these methods. Boundary value problems are addressed in Lecture 3, and the classic and quite intuitive Shooting algorithm to solve these class of problems is introduced. You will be expected to finish Quizzes 1, 2 and 3 at the end of Lectures 1, 2 and 3 respectively.
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