Introduction to Computational Mathematics and Big Data Visualization

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Course DatesMeeting TimesStatusInstructor(s)CRNRegistration
July 13, 2020 - July 31, 20207/13 - 7/31M-F 3:30P-6:20POpenCaixia Chen

Course Description

This course is designed to introduce future STEM (Science, Technology, Engineering and Mathematics) students to computational mathematics, parallel computing techniques commonly used in scientific computing and large-scale 3D data analysis methods and software for numerical simulation.

This course is project-oriented and aims to develop students' interest in STEM, understand the basic concepts of numerical analysis, parallel computing and data visualization, and develop students' ability to apply computational mathematics to analyze and solve practical scientific and engineering problems arising in CDS&E (Computational and Data-Enabled Science and Engineering).
Topics covered includes introduction to scientific computing and numerical simulation, introduction to parallel computing, data analysis and visualization.

By the end of this course, students will:
- have a good introduction to the numerical methods used in computing sciences.
- have a good introduction to parallel computing and big data visualization techniques.
- have a good introduction to computational and data-enabled science and engineering.
- be able to solve problems from algebra class numerically.
- be able to utilize some computational mathematics and programming skills to solve some practical
- develop critical thinking techniques for approaching scientific and engineering problems, preparing
them for future studies in STEM majors.

Prerequisites: Comfort with high-school algebra is recommended.

Course Information

  • Course Code: CECS0921
  • Length: 3 weeks

Program Information


Brown’s Pre-College Program in the liberal arts and sciences, offering over 200 non-credit courses, one- to four-weeks long, taught on Brown’s campus. For students completing grades 9-12 by June 2020.

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