Cost: $100

This course provides the principles of evaluating numerical differentiation, integration, and interpolation. Students will also practice how to estimate the numerical accuracy using relative error. Prerequisite: students must possess basic math skills in algebra and calculus and basic understandings of Newton’s second law before enrolling this course.

Course Objectives

Upon successful completion of this course, students will be able to:

  1. To introduce principles of numerical differentiation and integration.
  2. To practice the implantations of mathematical principles into the user-friendly computer code.
  3. To estimate the numerical accuracy.
  4. To identify advantages and disadvantages on each differentiation and integration.
  5. To practice the numerical differentiation and integration in engineering problems.

Credit Hours

Successful completion of this badge is awarded 0.5 online hours of credit. Workload for completion is based on the expectation that students will spend a minimum of 7.5 hours in instruction over the length of the badge and an additional 15 hours on preparation, readings, studying, writing, research and other assignments as determined by the badge instructor. Activities will involve working online, participating in asynchronous activities, and other offline work.

Credit Criteria

Grading Scale: Badge/No Badge

Evaluation: 100% completion of badge criteria


Instructor

Gisuk Hwang

Gisuk Hwang

Dr. Hwang currently works in Department of Mechanical Engineering at Wichita State University as an assistant professor. Prior to this, he worked in Environmental Energy Technologies Division at Lawrence Berkeley National Laboratory (2010-2013) as a post-doctoral fellow after he earned his M.S. (2006) and Ph.D. (2010) from the Department of Mechanical Engineering at the University of Michigan, in the field of polymer electrolyte membrane fuel cells and thermal energy management systems. His research interests are the development and optimization of the nano-/micro-scale heat and energy transport/conversion systems using modeling and experiments.