Emergent Phenomena in Science and Everyday Life

University of California, Irvine
via Coursera
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Before the advent of quantum mechanics in the early 20th century, most scientists believed that it should be possible to predict the behavior of any object in the universe simply by understanding the behavior of its constituent parts. For instance, if one could write down the equations of motion for every atom in a system, it should be possible to solve those equations (with the aid of a sufficiently large computing device) and make accurate predictions about that system’s future.

Note: The fractal image (Sierpinkski Triangle) depicted on the course home page was generated by a software application called XaoS 3.4, which is distributed by the Free Software Foundation under a GNU General Public License.

Upon completing this course, you will be able to:
1. Explain the difference in assumptions between an emergent versus reductive approach to science.
2. Explain why the reductivist approach is understood by many to be inadequate as a means of describing and predicting complex systems.
3. Describe how the length scale used to examine a phenomenon can contribute to how you analyze and understand it.
4. Explain why the search for general principles that explain emergent phenomena make them an active locus of scientific investigation.
5. Discuss examples of emergent phenomena and explain why they are classified as emergent.

Instructor(s)

Michael Dennin, Jun Allard, Donald Saari, Andrea Nicholas, Fred Y.M. Wan, Siddharth A. Parameswaran
University of California, Irvine
via Coursera
Free (audit)
English
Paid Certificate Available
Approx. 12 hours to complete
Self paced
Subtitles: Subtitles: French, Portuguese (European), Russian, English, Spanish