Informit – Algorithms 24 part Lecture Series (2015)
24+ Hours of Video Instruction
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. The instructors offer readings related to these lectures that you can find in Algorithms, Fourth Edition, the leading textbook on algorithms today. These lectures provide another perspective on the material presented in the book and generally cover the material in the same order, though some book topics have been combined, rearranged, or omitted in the lectures.
You also can find related resources on the instructors’ web site, including the following:
Full Java implementations
Exercises and answers
Programming assignments with checklists
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.
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:
Anyone using a computer to address large problems that require an understanding of efficient algorithms.
Width: 1280 pixels
Height: 720 pixels
Bit rate: 598 Kbps
Frame rate: 30.000 fps
Aspect ratio: 16:9
Bit depth: 8 bits
Color space: YUV
Audio track: 1
Codec: AAC LC
Bit rate: 63 Kbps
Sampling rate: 44 Khz
Extract the archives with Winrar 5 or WinZip(zip files) & password