list 6 sequences
assignment Level : Intermediate
chat_bubble_outline Language : English
language Subtitles : Korean
card_giftcard 600 points
Users' reviews
-
starstarstarstarstar

Key information

credit_card Free access
verified_user Fee-based Certificate
timer 60 hours in total

About the content

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 algorithms. All the features of this course are available for free. It does not offer a certificate upon completion.

more_horiz Read more
more_horiz Read less
dns

Syllabus

  • Week 1 - Course Introduction
    Welcome to Algorithms, Part I.
  • Week 1 - Union−Find
    We illustrate our basic approach to developing and analyzing algorithms by considering the dynamic connectivity problem. We introduce the union−find data type and consider several implementations (quick find, quick union, weighted quick union, and weighted qui...
  • Week 1 - Analysis of Algorithms
    The basis of our approach for analyzing the performance of algorithms is the scientific method. We begin by performing computational experiments to measure the running times of our programs. We use these measurements to develop hypotheses about performance. Ne...
  • Week 2 - Stacks and Queues
    We consider two fundamental data types for storing collections of objects: the stack and the queue. We implement each using either a singly-linked list or a resizing array. We introduce two advanced Java features—generics and iterators—that simplify client cod...
  • Week 2 - Elementary Sorts
    We introduce the sorting problem and Java's Comparable interface. We study two elementary sorting methods (selection sort and insertion sort) and a variation of one of them (shellsort). We also consider two algorithms for uniformly shuffling an array. We concl...
  • Week 3 - Mergesort
    We study the mergesort algorithm and show that it guarantees to sort any array of n items with at most n lg n compares. We also consider a nonrecursive, bottom-up version. We prove that any compare-based sorting algorithm must make at least n lg n compares in...
  • Week 3 - Quicksort
    We introduce and implement the randomized quicksort algorithm and analyze its performance. We also consider randomized quickselect, a quicksort variant which finds the kth smallest item in linear time. Finally, we consider 3-way quicksort, a variant of quickso...
  • Week 4 - Priority Queues
    We introduce the priority queue data type and an efficient implementation using the binary heap data structure. This implementation also leads to an efficient sorting algorithm known as heapsort. We conclude with an applications of priority queues where we sim...
  • Week 4 - Elementary Symbol Tables
    We define an API for symbol tables (also known as associative arrays, maps, or dictionaries) and describe two elementary implementations using a sorted array (binary search) and an unordered list (sequential search). When the keys are Comparable, we define an ...
  • Week 5 - Balanced Search Trees
    In this lecture, our goal is to develop a symbol table with guaranteed logarithmic performance for search and insert (and many other operations). We begin with 2−3 trees, which are easy to analyze but hard to implement. Next, we consider red−black binary searc...
  • Week 5 - Geometric Applications of BSTs
    We start with 1d and 2d range searching, where the goal is to find all points in a given 1d or 2d interval. To accomplish this, we consider kd-trees, a natural generalization of BSTs when the keys are points in the plane (or higher dimensions). We also conside...
  • Week 6 - Hash Tables
    We begin by describing the desirable properties of hash function and how to implement them in Java, including a fundamental tenet known as the uniform hashing assumption that underlies the potential success of a hashing application. Then, we consider two strat...
  • Week 6 - Symbol Table Applications
    We consider various applications of symbol tables including sets, dictionary clients, indexing clients, and sparse vectors.
record_voice_over

Instructors

Kevin Wayne
Senior Lecturer
Computer Science

Robert Sedgewick
William O. Baker *39 Professor of Computer Science
Computer Science

store

Content designer

Princeton University
Princeton University is a private research university located in Princeton, New Jersey, United States. It is one of the eight universities of the Ivy League, and one of the nine Colonial Colleges founded before the American Revolution.
assistant

Platform

Coursera

Coursera is a digital company offering massive open online course founded by computer teachers Andrew Ng and Daphne Koller Stanford University, located in Mountain View, California. 

Coursera works with top universities and organizations to make some of their courses available online, and offers courses in many subjects, including: physics, engineering, humanities, medicine, biology, social sciences, mathematics, business, computer science, digital marketing, data science, and other subjects.

You are the designer of this MOOC?
What is your opinion on this resource ?
Content
0/5
Platform
0/5
Animation
0/5