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InformIT Algorithms - 24-part Video Lecture Series - 2015

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InformIT Algorithms - 24-part Video Lecture Series - 2015

InformIT Algorithms - 24-part Video Lecture Series - 2015

English | Size: 7.31 GB (7,847,767,761 Bytes)
Category: CBTs

These Algorithms Video Lectures cover 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.
This collection of video lectures provides a comprehensive exploration of fundamental data types, algorithms, and data structures, with an emphasis on applications and scientific performance analysis of Java implementations.

About the Instructors

Robert Sedgewick is the William O. Baker Professor of Computer Science at Princeton University. He is a Director of Adobe Systems and has served on the research staffs at Xerox PARC, IDA, and INRIA. He earned his PhD from Stanford University under Donald E. Knuth.

Kevin Wayne also teaches in the Department of Computer Science at Princeton University. His research focuses on theoretical computer science, especially optimization and the design, analysis, and implementation of computer algorithms. Wayne received his PhD from Cornell University.

Skill Level

All Levels

What You Will Learn

These videos survey the most important computer algorithms in use today. The algorithms described in these lectures represent a body of knowledge developed of the last 50 years that has become indispensable. These lectures present:

Implementations of useful algorithms
Detailed information on performance characteristics
Examples of clients and applications
The early lectures cover our fundamental approach to studying algorithms, including data types for stacks, queues, and other low-level abstractions. Then we cover these major topics:

Sorting algorithms, highlighting the classic Quicksort and Mergesort algorithms.
Searching algorithms, including search methods based on balanced search trees and hashing.
String-processing algorithms, from tries and substring search to regular expression search and data compression.
Graph algorithms, starting with graph search, shortest paths, and minimum spanning trees, and working up to maximum flow/minimum cut and applications.
Reductions, linear programming, and intractability.

Who Should Take This Course

The study of algorithms and data structures is fundamental to any computer-science curriculum, but it is not just for programmers and computer science students. These lectures are intended for:

Any student (from high school to graduate level) having a good introduction to programming, with an interest in majoring in any science or engineering discipline (including computer science).
Anyone using a computer to address large problems that require an understanding of efficient algorithms.
Anyone interested in preparing for a career in industry involving software or computer applications.

Course Requirements

Basic familiarity with Java
Some background in programming
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