Design algorithms and analyze their complexity in terms of running time and space usage; Create applications that are supported by highly efficient algorithms and data structures for the task at hand; ...

Complexity analysis techniques: worst-case, average-case, probabilistic, and amortized analysis; Sorting algorithms: insertion sort, quicksort, mergesort, heapsort; Data structures: heaps, hashtables, ...

Providing a summary of important algorithms and data structures along with their key characteristics and use cases. It can be used as a quick reference for solving programming problems or refreshing ...

Specialization: Data Science Foundations: Data Structures and Algorithms Instructor: Sriram Sankaranarayanan, Assistant Professor Prior knowledge needed: Mathematical Background: We expect that the ...

Learn how to implement different types of Maps such as: HashMap; TreeMap; Also, learn the difference between the different Maps implementations: HashMap is more time-efficient. A TreeMap is more space ...

Introduction to the fundamental principles of data structures and algorithms and their efficient implementation. Developing algorithmic thinking. Basic toolkit for the design and analysis of ...

Navigating a busy cityscape with a fleet of autonomous vehicles requires each to seamlessly maneuver through traffic with split-second decisions. Path planning is the backbone of such advanced ...