Many aspiring developers appear to have the mistaken belief that memorizing standard algorithms is essential. While this may be true for some job interviews, it is not particularly important for becoming a successful developer.
Developers should learn algorithms to practice algorithmic thinking, which is crucial for success, even if memorizing them isn't always the primary goal for job interviews. Key algorithms include brute force, the simplest approach; greedy algorithms, which make locally optimal choices; and divide and conquer, known for its efficiency in breaking down problems. Dynamic programming enhances efficiency by remembering past results, and randomized algorithms incorporate random numbers into their logic. Understanding these types helps developers approach problem-solving systematically.
So, are the things you learn in an algorithm class useless? Absolutely not. 
That’s why we’ve compiled a list of ten algorithms for aspiring developers to practice thinking algorithmically. 
The brute force algorithm is the simplest algorithm that can be devised to solve a problem.
This is one of the most used algorithms in programming. This algorithm divides the problems into subproblems and then solve each of them and then combine them to form the solution of the given problems.
This is the most sought-after algorithm because it provides the most efficient solution to a problem. This algorithm is quite efficient in terms of time complexity because it simply means remembering the past and applying it to future corresponding results.
This is a type of algorithm that makes decisions based on random numbers, i.e. it employs random numbers in its logic.
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