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mndt
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I have a BS in math and to think of it Chaos theory was why I got into this field to begin with.
Which educational/career path should i follow from now on?
Which educational/career path should i follow from now on?
union68 said:http://www.cam.cornell.edu/Graduate/Courses/#dynamical"
http://www.math.umd.edu/research/dynamics/"
http://www.math.psu.edu/dynsys/"
http://www.math.sunysb.edu/dynamics/"
I am an applied math major, so those are all math programs. I'm strongly considering going into dynamics as well. I have taken PDEs, ODEs, classical dynamics, and have signed up for my first official "dynamical systems" class next semester. This is a pretty common route.
Many physicists study non-linear dynamics as well, for what it's worth. Both of my classical dynamics books contain entire chapters on chaos.
Not enough info for ya? http://www.dynamicalsystems.org/ap/pg/"
Chaos theory is a branch of mathematics and physics that studies complex systems that appear to be random and unpredictable, but actually follow specific patterns and behaviors.
Careers related to chaos theory include chaos theorists, mathematicians, physicists, engineers, computer scientists, and data analysts. These professionals use chaos theory to study and analyze complex systems in various industries, such as weather forecasting, economics, biology, and social sciences.
To pursue a career related to chaos theory, one needs a strong foundation in mathematics, physics, and computer science. Critical thinking, problem-solving, and analytical skills are also crucial, as well as a strong understanding of complex systems and their behaviors.
Most careers related to chaos theory require a minimum of a bachelor's degree in mathematics, physics, engineering, computer science, or a related field. Many professionals in this field also have advanced degrees, such as a master's or doctorate, in their specific area of interest.
Chaos theory has numerous real-world applications, including weather prediction, financial market analysis, population dynamics, and cryptography. It also has practical applications in engineering, such as designing stable and efficient systems, and in computer science, such as developing algorithms for data analysis and machine learning.