Description. An introduction to fundamental data types, algorithms, and data structures. Our emphasis is on applications and scientific performance analysis of Java implementations.
Part I focuses on elementary data structures, sorting, and searching. Topics include union-find, binary search, stacks, queues, bags, insertion sort, selection sort, shellsort, quicksort, 3-way quicksort, mergesort, heapsort, binary heaps, binary search trees, red-black trees, separate chaining and linear probing hash tables, Graham scan, and kd-trees.
Part II focuses on graph and string-processing algorithms. Topics include depth-first search, breadth-first search, topological sort, Kosaraju-Sharir, Kruskal, Prim, Dijkistra, Bellman-Ford, Ford-Fulkerson, LSD radix sort, MSD radix sort, 3-way radix quicksort, multiway tries, ternary search tries, Knuth-Morris-Pratt, Boyer-Moore, Rabin-Karp, regular expression matching, run-length coding, Huffman coding, LZW compression, and the Burrows-Wheeler transform.
Prerequisites. The programming prerequisite for the course is familiarity with Java, including loops, arrays, functions, recursion, and objects. We introduce advanced features of Java as necessary (such as generics and iterators). The mathematics prerequisite is high-school algebra.
Lectures. There are two lectures (75 minutes each) per week. Each lecture is broken up into about 4–6 segments, separated by interactive quiz questions to help you process and understand the material.
Readings. Our textbook is the basic reference for the material we will be covering. Although the lectures are designed to be self-contained, we will assign suggested (but optional) readings for students who wish more extensive coverage of the material.
Algorithms, 4th Edition by Robert Sedgewick and Kevin Wayne, Addison-Wesley Professional, 2011, ISBN 0-321-57351-X.
You can purchase the textbook in either hardcover or electronic format from amazon.com.
Our booksite is open to everyone and contains a wealth of supplementary information, including synopses of the textbook and Java code that you will be using throughout the course.
Exercises. There is one exercise set associated with each lecture. An exercise set consists of three drill questions, designed to ensure that you understand the basics. We expect that each exercise set will take approximate 10–30 minutes to complete. You may attempt each exercise set up to 10 times (your best score is recorded); you will receive a different set of questions on each attempt. Solutions are provided after each attempt.
Programming assignments. There is one Java programming assignment per week. Some of the programming assignments require that you implement a data structure or algorithm from scratch; others require that you apply a data structure or algorithm to solve a problem from science, commerce, or recreation. We expect that each programming assignment will take approximately 4–12 hours to complete, depending on your programming experience. You may attempt each programming assignment up to 10 times (your best score is recorded). After each attempt, we will provide feedback on correctness and efficiency.
Final exam. The final exam is cumulative and designed to make sure you understand how each algorithm works and when it is effective. The final will not involve Java programming. You may attempt the final exam up to 3 times (your best score is recorded).
Job interview questions. Each week, we will also provide a few algorithmic job interview questions based on the material for the week, inspired by questions asked at leading technology companies. The questions are for self-enrichment and are not assessed; however, we will provide some hints and you are welcome to discuss solutions in the discussion forums with your classmates.
Discussion forums. Please be sure to make use of the discussion forums if you need help, and please contribute to the forums if you think that you can provide help. Such forums have proven to be an important and fun part of the online course experience. Staff members will monitor these forums.
Honor code. All students in the course must agree to abide by the Coursera honor code. In particular, do not post solutions or partial solutions to programming assignments; however, you are permitted to discuss general ideas and problem-solving approaches. You are also permitted to discuss solutions to exercises and job interview questions.
Copyright. All rights reserved. All video recordings, lecture slides, assessments and other materials made available in connection with this course are subject to copyright protection and may be used only for private study by persons who are enrolled in this course. Any other use of these materials must be with the express, written permission of Robert Sedgewick and Kevin Wayne.
Certificates. No certificates, statements of accomplishment, or other credentials will be awarded in connection with this course.
Credits. We are grateful to many for help in developing this course. We thank Daniel Kearns, Laura Shaddock, and Jeffrey Himpele for video production; Josh Hug for programming assignment infrastructure; and Andrew Morrison for exercise infrastructure. We also thank the Coursera team, especially Jiquan Ngiam, Koh Pang Wei, and Daniel Chia for extending the Coursera platform to enable our advanced assessments and Daphne Koller for inspiring us to teach a MOOC.