Algorithms_DataStructure_Specialization

this is repo about my solutions of problems in Data Structures and Algorithms Specialization in coursera site from algorithmic toolbox to Genome Assembly Programming Challenge

Motivations to study it?

there are many reasons push me to spend good time with algorithms and their implementations

• I love programming but programming languages themselves are just tools to implement ideas (algorithms) so I decide to learn more about the ideas themselves.

• I want to be an efficient and excellent programmer. so I searched on google and found that enough understandin of algorithms and data structure will make you an efficient programmer

• I love problem solving so I began solve problems on codeforces but there are very hard problems that I could not solve them. After that I know that study algorithms will enable you to solve them

• algorithms are everywhere in digital tech. It is important to know albeit little about them

• high companies request graduates who are good in algorithms.

Courses and Their content

• algorithms toolbox

  • Week 1 :

    • stress testing : test your efficient algorithm vs your naive algorithms by generating rondom test cases. starting with small output and edge cases

    • complexity notations : bigO() : upper limit of your algorithm Theta() : lower limit of your algorithm omega() : if algorithm upper limit equal lower limit

  • Week 2 :

    • Fibonancci Numbers and other maths Functions like gcd(), lcm()
      • specialization problems
      • more probelems

  • Week 3 :

    • Greedy algorithm
      • specialization problems
      • more probelems

  • Week 4 :

    • Divide and Conquer
      • specialization problems
      • more problems