Advanced Algorithms
MIT OpenCourseWare offers this first-year graduate course in algorithms, covering fundamental techniques and advanced methods of algorithmic design, analysis, and implementation. Topics include amortization, randomization, fingerprinting, word-level parallelism, bit scaling, dynamic programming, network flow, linear programming, fixed-parameter algorithms, and approximation algorithms. The course applies these techniques across domains such as string algorithms, network optimization, parallel algorithms, computational geometry, online algorithms, external memory and cache-aware algorithms, streaming algorithms, and data structures. Materials include lecture notes, problem sets, and exams from MIT's Electrical Engineering and Computer Science department, licensed under CC BY-NC-SA 4.0. The course is free to access through MIT OpenCourseWare, with no certificate offered. It suits students who already have a strong undergraduate algorithms background and want exposure to research-level techniques and analysis methods used in modern algorithm design.