Akademik Dersler - İçerik

Critically design and analyze algorithms
Compare and analyze different implementations of the same solution
Tweak and fine-tune algorithms for improved performance
Compute and compare space and time complexity of algorithms
Define different algorithm types: Iterative, recursive, randomized, greedy
Understand and describe amortized analysis
Discuss advanced algorithm design techniques
Discuss Algorithm Design Techniques, including – greedy algorithms, divide-and-conquer algorithms, Dynamic programming, Randomised Algorithms and Back-tracking
Discuss the fundamentals of Data Compression, including Huffman coding and decoding algorithm
Discuss string and pattern matching techniques – brute-force method, Knuth-Morris-Pratt method
Discuss dynamic programming algorithms such as
Understand the fundementals of data structures
Describe advanced data structures such as binomial heaps, fibonacci heaps
Study advanced graph problems such as all-pairs shortest paths, min-flow max-flow problem, graph partitioning
Define computational complexity classes
Give a basic intuitive definition of P, NP, NP-Hard, and NP-Complete
Give examples of NP-Complete problems
Prove NP-Complete problems by reduction
Define approximation algorithms and how they are used