Introduction to Algorithm Analysis and Big O Notation

This video introduces algorithm analysis and big O notation. It starts where a previous video leaves off talking about counting operations (https://youtu.be/pgMjh_G7ejw) in order to derive a growth rate function T(n). Then we discuss extracting the worst case time complexity of the algorithm O(n) from the growth rate function. Finally, we draw a chart to introduce the most common families of algorithms by time complexity (e.g. constant, logarithm, linear, log linear, etc.) https://github.com/gsprint23/Cpp-Crash-Course