The primary topics in this part of the specialization are: shortest paths (Bellman-Ford, Floyd-Warshall, Johnson), NP-completeness and what it means for the algorithm designer, and strategies for coping with computationally intractable problems (analysis of heuristics, local search).

Algorithms Specialization

Shortest Paths

NP-Completeness

Dynamic Programming

May 20th 2024

Course Auditing

Coursera

Stanford University

CS: Software Engineering

41.00 EUR/month

May 6th 2024

Course Auditing

Coursera

University of Colorado Boulder

Categories

Effort

Languages

Basic algorithms on tree data structures, binary search trees, self-balancing trees, graph data structures and basic traversal algorithms on graphs. This course also covers advanced topics such as kd-trees for spatial data and algorithms for spatial data. Trees and Graphs: Basics can be taken for academic credit as part [...]

Data Structures and Algorithms Specialization

May 6th 2024

Course Auditing

Coursera

University of Colorado Boulder

84.00 EUR

Apr 29th 2024

Free Course

Coursera

Princeton University

Categories

CS: Theory

CS: Software Engineering

Effort

Languages

This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations. Part I covers elementary data structures, sorting, and searching algorithms. Part II focuses on graph- and string-processing [...]

Apr 29th 2024