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Free Computer and I.T. Books

March 3, 2011

Algorithms Online Book and Course Lecture Slides

Here is an online algorithms textbook, Algorithms, 4th Edition, hosted by Princeton University. It presents and covers all of the fundamental knowledge you need to understand and apply when using algorithms and data structures in your programming and application development. These are the most important algorithms and data structures in use today. The book uses specific applications to science, engineering, and industry to facilitate the concepts. Here is a list of the algorithms and clients in this textbook.

Algorithm Book Chapters:

Chapter 1: Fundamentals introduces a scientific and engineering basis for comparing algorithms and making predictions. It also includes our programming model.

Chapter 2: Sorting considers several classic sorting algorithms, including insertion sort, mergesort, and quicksort. It also includes a binary heap implementation of a priority queue.

Chapter 3: Searching describes several classic symbol table implementations, including binary search trees, red-black trees, and hash tables.

Chapter 4: Graphs surveys the most important graph processing problems, including depth-first search, breadth-first search, minimum spanning trees, and shortest paths.

Chapter 5: Strings investigates specialized algorithms for string processing, including string sorting, substring search, tries, regular expressions, and data compression.

Chapter 6: Context highlights connections to systems programming, scientific computing, commercial applications, operations research, and intractability.

Also, here are the Lecture Slides and Notes for Princeton's Algorithms and Data Structures course.

These algorithm course lectures target algorithms for sorting, searching, and string processing, as well, including geometric and graph algorithms. They include information on developing implementations, understanding their performance characteristics, and estimating their potential effectiveness in applications.

Algorithm Lectures:

1. Union-find
2. Analysis of algorithms
3. Stacks and queues
4. Elementary sorts
5. Efficient sorts
6. Advanced topics in sorting
7. Priority queues
8. Elementary symbol tables
9. Binary search trees
10. Balanced BSTs
11. Hashing
13. Undirected graphs
14. Directed graphs
15. Minimum spanning trees
16. Shortest paths
17. Radix sorts
18. Tries
19. Pattern matching   DFA   KMP  
20. Data compression   Huffman*   LZW*
21. Geometric algorithms   convex hulls 
22. Geometric search    sweep line intersection
23. Reductions
24. Combinatorial search   The Longest Path [mp3]

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January 15, 2011

How-to Program online book

This How-to Program book is for those wanting to learn how to program or needing a refresher of programming basics. It provides you all the information and examples necessary to first understand, and then to apply, the fundamentals of computer programming and how to code computer programs. The books focus is programming logic and how it is used by developers to write efficient and effective computer programs. The beginning chapters teach logic structures and structured programming, and the later chapters discuss and demonstrate more advanced programming techniques, such as object orientated and event driven programming. The examples provided in the book include pseudo code, flowcharts, UML (Unified Modeling Language), illustrations, case studies, and coding examples in Python, Visual Basic .Net, Java. The chapters are from 35 to 57 pages in length each, and in doc format. PDF format is also available.

Contents of How to Program book:

Chapter 1 Understanding Program Logic and Programming (pdf)

Chapter 2 Introduction to Program Logic (pdf)

Chapter 3 Fundamentals of Program Development (pdf)

Chapter 4 Control Structure Fundamentals (pdf)

Chapter 5 Fundamentals of Modularization (pdf)

Chapter 6 Introduction to Arrays and Structures (pdf)

Chapter 7 The Basics of Files and Databases (pdf)

Chapter 8 Learning About Classes and Objects (pdf)

Chapter 9 Object Orientated Programming Continued (pdf)

Chapter 10 Object Orientated Programming Design (pdf)

Chapter 11 Fundamentals of Event Driven Programming (pdf)

Chapter 12 Graphical User Interface Programming Fundamentals (pdf)

Chapter 13 Project Start to Finish (pdf)

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September 2, 2010

403 Downloadable Computer and Programming eBooks

Here are 403 freely available and downloadable computer and programming ebooks, covering many topics and areas, as listed below. These computer ebooks are in chm and pdf formats, along with some in compressed zip format.

Topics covered by these Computer and Programming eBooks:

 - C ++ programming
 - C++ Game programming
 - C++ Data Structures
 - C++ Design Patterns, Coding Standards
 - C language Algorithms
 - Linux programming
 - XML
 - Cryptography using C and C++
 - DB2
 - Compilers
 - Linux System Administration
 - Embedded Linix, Linux Kernel, Linux Device Drivers
 - Ubuntu Linux, Debian Linux, Fedora Linux
 - Unix administration
 - Wireless Networking
 - Wifi Security
 - dotNet programming
 - ASP .Net
 - ASP .Net Ajax
 - VB .Net programming (Visual Basic dotNet )
 - VB .Net Algorithms and Data Structures
 - Visual C++ programming
 - ADO .Net
 - MSCE/MSDE 70-330, 70 340 - C# (C Sharp) and VB .Net Security
 - Borland C++ Builder
 - Windows Administation

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April 25, 2010

70 Computer and IT ebooks

Here are 70 computer and I.T. ebooks covering areas in Linux, Networking, some Certifications, Cisco, and Security. Other topics include Algorithms, Hardware, Regular Expression, PHP and MySLQ, VBA, and Hardware.

eBook Topics on this site:

 - Linux
 - LPI Exam
 - Linux+ Certification
 - RHCE Exam
 - Linux Commands
 - PHP and MySQL with Linux
 - Unix
 - Network+ Certification
 - Server+ Certification
 - Solaris Certification
 - Network Admin
 - Cisco, CCNA
 - Cisco Routers and IOS
 - Network Security
 - Apache
 - SSL Certificates
 - Regular Expressions
 - Algorithms
 - VBA
 - Visual Basic
 - Data Compression
 - PC Hardware

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Filed under: Free Computer and I.T. Books — computer_teacher @ 10:04 am

July 15, 2008

New York University Algorithms Course

This Algorithms course, from New York Univeristy, teaches the analysis, correctness and efficiency of computer algorithms. It discusses basic algorithms, such as balanced binary trees, sorting and selection, graph traversal, graph connectivity, breadth-first and depth-first searches, spanning tree, shortest paths. It also covers computational techniques that include divide-and-conquer, greedy method, and dynamic programming. It then reviews randomized algorithms, amortization, and an introduction to NP-Completeness Theory. Detailed lecture notes for this course are linked below. For more detailed information and learning material on algorithms, you can visit NIST's Dictionary of Algorithms and Data Structures.

The student for this algorithms course should be familiar with computer programming, data structures, and some discrete mathematics. Problems solved using computers can be roughly classified into problems-in-the-large and problems-in-the-small. The former is associated with large software systems, compilers or text editors. The latter is identified with mathematically well-defined problems such as sorting, multiplying two matrices or solving a linear program. The methodology for studying such "large" and "small" problems are quite distinct: Algorithmics is the study of the small problems and their algorithmic solution.

Algorithms can be classified into four basic themes:
  (a) data-structures (e.g, linked lists, stacks, search trees)
  (b) algorithmic techniques (e.g., divide-and-conquer, dynamic programming)
  (c) basic computational problems (e.g., sorting, graph-search, point location)
  (d) analysis techniques (e.g., recurrences, amortization, randomized analysis)

Algorithms Lecture Notes  (in pdf format)

Lecture 1: Introduction to Algorithmics
(36 pages, 377kb)

Lecture 2: Recurrences
(49 pages, 455kb)

Lecture 3: Balanced Search Trees
(46 pages, 479kb)

Lecture 4: Pure Graph Algorithms
(36 pages, 408kb)

Lecture 5: Greedy Method
(48 pages, 488kb)

Lecture 6: Amortization Method
(42 pages, 418kb)

Lecture 7: Dynamic Programming
(38 pages, 378kb)

Lecture 8: Randomized Algorithms - Quick Probability
(31 pages, 317kb)

Lecture 9: Randomization and Derandomization
(9 pages, 132kb)

Lecture 14: Minimum Cost Paths
(25 pages, 265kb)

Lecture 30: NP Completeness
(20 pages, 246kb)

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Filed under: Best New Free Computer IT Training Tutorial Resources — computer_teacher @ 8:12 pm

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