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Learn how to analyze the time complexity and the space complexity of an algorithm by using the big O notation
An excellent training about Engineering
Time and space complexity analysis (big-O notation)
You have issues with time and space complexity analysis? No worries, get ready to take a detailed course on time and space complexity analysis that will teach you how to analyze the time and space complexity of an algorithm, an important skill to have in computer science and competitive programming! The course contains both theory and practice, theory to get all the knowledge you need to know about complexity analysis (notations, input cases, amortized complexity, complexity analysis of data structures.) and practice to apply that knowledge to analyze the time and space complexity of different algorithms! And to make your learning experience better, the course will have quizzes, extra resources, captions, animations, slides, good audio quality. et cetera. And most importantly, the ability to ask the instructor when you don’t understand something! Hours and hours of researching, writing, animating, and recording, to provide you with this amazing course, don’t miss it out! The course will cover: Complexity analysis basicsBig-O, big-Omega, and big-Theta notationsBest, average, and worst caseComplexities hierarchyHow to analyze the time and space complexity of an algorithmHow to compare algorithms efficiencyAmortized complexity analysisComplexity analysis of searching algorithmsComplexity analysis of data structures main operationsCommon mistakes and misconceptionsAnd a few more chapters will be added soon: Complexity analysis of sorting algorithmsComplexity analysis of recursive functionsComplexity classes (P vs NPproblem)Complexity analysis of 15 popular interview coding problemsHope to see you in the course!
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