Algorithms: Design and Analysis, Part 2
About this Course
Welcome to the self paced course, Algorithms: Design and Analysis, Part 2! Algorithms are the heart of computer science, and the subject has countless practical applications as well as intellectual depth. This course is an introduction to algorithms for learners with at least a little programming experience. The course is rigorous but emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details. After completing this course, you will have a greater mastery of algorithms than almost anyone without a graduate degree in the subject. Specific topics in Part 2 include: greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes), dynamic programming (knapsack, sequence alignment, optimal search trees, shortest paths), NP-completeness and what it means for the algorithm designer, analysis of heuristics, local search. Learners will practice and master the fundamentals of algorithms through several types of assessments. There are 6 multiple-choice problem sets to test your understanding of the most important concepts. There are also 6 programming assignments, where you implement one of the algorithms covered in lecture in a programming language of your choosing. The course concludes with a multiple-choice final. There are no assignment due dates and you can work through the course materials and assignments at your own pace.Created by: Stanford University
Level: Intermediate
Related Online Courses
Welcome to this Spark AR Studio advanced course. In this course, you will build on your advanced skills and techniques to continue with your very own Spark AR journey! The goal of this course is to... more
The aim of this course is to equip learners with advanced skills in network automation and make them industry ready. In this course, you will learn about SDN Deployment. The course has been... more
A lo largo de los años, la inteligencia artificial ha logrado muchos años de evolución. Existen antecedentes desde los años 50s que brindaron los fundamentos para llegar al crecimiento del pod... more
Robots are rapidly evolving from factory workhorses, which are physically bound to their work-cells, to increasingly complex machines capable of performing challenging tasks in our daily... more
In this course you will learn about the different experiences patients go through in a medical context. The patient journey explores the interaction between the patient and the healthcare providers... more