- Course Number: 16:198:513
- Course Type: Graduate
- Semester 1: Fall
- Semester 2: Spring
- Credits: 3
Core material for Computer Science degree candidates. Discussion of representative algorithms and data structures encountered in applications.
- Category: A (M.S.), A (Ph.D.)
- Prerequisite Information:
Familiarity with Prim and Kruskal minimum spanning tree algorithms and Dijkstra shortest path algorithm.
For MS students 16:198:512 is a pre-requisite.
Ph.D. students can directly register for 513.
- Course Links: 16:198:512 - Introduction to Data Structures and Algorithms
- This course is a Pre-requisite for the Following Courses: 16:198:514 - Design And Analysis Of Data Structures And Algorithms II, 16:198:522 - Network and Combinatorial Optimization Algorithms, 16:198:529 - Computational Geometry, 16:198:538 - Complexity Of Computation, 16:198:540 - Combinatorial Methods In Complexity Theory, 16:198:541 - Advanced Data Management, 16:198:550 - Massive Data Mining, 16:198:580 - Topics In Computers In Biomedicine
Worst case, average case, and amortized analysis. Data structures: search trees, hash tables, heaps, Fibonacci heaps, union-find. Algorithms: string matching, sorting and ordering statistics, graph algorithms. NP-completeness.
- Expected Work: 6-7 homework assignments. There is a midterm and final examination.