Scientific computing problems are the ubiquitous and inevitable problems for any students in science and engineering. The de facto top selected scientific computing language, MATLAB, is taught, and used for solving scientific computing problems in various engineering mathematical branches.  This course guides the students how to relay on computers to get solutions of scientific computing results effectively, accurately and creatively, when equipped with model, powerful computer tools.

Under the optimized course framework, starting from the essential knowledge (basic ideas, methods and concepts in MATLAB programming), direct computer-aided solutions to various mathematical branches are extensively introduced. MATLAB is used as the main line, around that the solution patterns are constructed.  Significant number of examples are used in the course.  Classroom teaching on all the textbook aspects is the main body of the course. Further extensions to each topic are also explored. Example-based dedicated special talks are also provided.

Concentrations are made on two aspects of the course – fundamental knowledge and applications. They mainly include the introductory talks on MATLAB and programming, and also comprehensively utilize such a language to solve practical scientific computing problems.  The main topics include: MATLAB language essential with scientific visualization facilities, and based on the language, to find the computer solutions to calculus problems, linear algebra problems, integral transform and complex function problems, equation solution and optimization problems, differential equation problems, data interpolation and curve fitting problems, probability and statistics problems, and nontraditional mathematics problems.

Undergraduate and postgraduate students of all science and engineering disciplines, scientific and engineering researches. Through the course study, the participants will be equipped with MATLAB programming skills, and have their capabilities in tackling practical scientific computing problems boosted to a higher level.

Essential knowledge of the following preliminary courses, but not necessary. Zero preliminary background is also possible for the study.

• Computer language and programming (for example C)

• Adavanced Mathematics

• Linear Algebra

• Integral Transform

• Optimization.
  

• Dingyu Xue and YangQuan Chen “Scientific Computing with MATLAB” (Second Edition)， Boca Radon: CRC Press, 2016

• Further reading: Five Titles by Dingyu Xue, A Subseries on Scientific Computing, Berlin: De Gruyter, 2020