SAP-img.com provides documentation and guides covering SAP R/3 on ABAP, BAPI, ALV programming, SAPscripts, SmartForms, CATT, LSMW, DMS and other IMG like areas, such as MM, LE, SD, PP, APO, WF, HU, PM, PS, QM, HR, FI, CO, BW and BC.

Here are some SAP guides and documents that you can download in zip format. (These are pdf files when unzipped.)

Guide to SAP BASIS Steps for SAP Kernel Update In Windows
SAP BASIS- Steps to Configure SAP Help Library
SAP HR PA Infotypes Guide
SAP FI (Deleting No.range of Particular Company)
Flow of Production Planning
Guide to ABAP MM, SD, FI, PS, PP, PM, HR, Tables


This site's SAP PP Tips and Production Planning/Control page will also help you with learning more about SAP Production Planning Modules and its related areas. It provides certification samples, interview questions and answers, as well as common tcodes used in SAP PP.  You can also ask any Production Planning and Control question in their SAP PP Forum. The SAP PP modules are mostly utilized in Manufacturing, as thhey allow you to create BOM, routing, work center, plan orders, production orders, and confirmations.  They are integrated with other SAP modules, such as SAP MM and SAP SD through MRP which is also part of PP. Here are just a few of the resources on this page:

SAP PP Certification Exam:
mySAP Certification - Criteria
SAP PP Certification Sample Questions and Answers
SAP PP Self Test Certification Questions

Questions on Production Planning:
SAP PP Questions and Answers
Sample Questions on SAP PP
SAP PP Test Questions (MCQ)
Steps of a Typical Production Process

Interview Preparation:
Interview Questions and Anwsers on SAP PP
SAP PP Interview Questions

Transaction Codes in SAP PP:
Transaction Code To View All SAP Tables
Commonly Used Tcodes in PP Module Part 1
Commonly Used Tcodes in PP Module Part 2
Commonly Used Tcodes in PP Module Part 3
Tcodes of Common SAP PP Process

Here is another online programming textbook from Princeton, Introduction to Programming in Java. It teaches the classic elements of programming, using an "objects-in-the-middle" approach that emphasizes data abstraction. The author uses specific applications, taken from fields ranging from materials science to genomics to astrophysics to internet commerce, to teach and demonstrate the programming concepts and techniques presented. Also available are hundreds of easily downloadable Java programs and real-world data sets.


Chapter 1: Elements of Programming
introduces variables; assignment statements; built-in types of data; conditionals and loops; arrays; and input/output, including graphics and sound.

Chapter 2: Functions
introduces modular programming. We stress the fundamental idea of dividing a program into components that can be independently debugged, maintained, and reused.

Chapter 3: Object-Oriented Programming
introduces data abstraction. We emphasize the concept of a data type and its implementation using Java's class mechanism.

Chapter 4: Algorithms and Data Structures
introduces classical algorithms for sorting and searching, and fundamental data structures, including stacks, queues, and symbol tables.

To get started.
Here are instructions for installing a Java programming environment on your Mac OS X, Windows, or Linux computer.

Full programming model.
Also provided are I/O libraries for reading and writing text and binary data, drawing graphics, and producing sound.


Here are Lecture Slides and Demos that accompany this textbook, An Introduction to Programming in Java:

Elements of Programming:
1.1  Your First Program
1.2  Built-In Types of Data
1.3  Conditionals and Loops  While loop
1.4  Arrays  Shuffle
1.5  Input and Output
1.6  Random Surfer

Functions:
2.1  Functions  Function call
2.2  Libraries and Clients
2.3  Recursion  Factorial  Euclid  Towers of Hanoi
2.4  Percolation  Depth-first search

Object-Oriented Programming:
3.1  Data Types
3.2  Creating Data Types  Mandelbrot explorer  Mandelbrot song
3.3  Designing Data Types
3.4  N-Body Simulation
3.5  Purple America  US Elections (1960 - 2008)

Algorithms and Data Structures:
4.1  Performance
4.2  Sorting and Searching  Binary search  Merge
4.3  Stacks and Queues  Linked list  Iteration
4.4  Symbol Tables  Inorder  GrowingTree
4.5  Small-World Phenomenon  BFS  Oracle of Kevin Bacon

This free online computer science book, Introduction to Computer Science (at Princeton University), is an interdisciplinary approach that teaches all of the classic elements of programming, using an "objects-in-the-middle" approach that emphasizes data abstraction. The book focuses four areas of computer science: programming, machine architecture, theory, and systems. The programming topics and concepts are presented by demonstrating specific applications, taken from fields ranging from materials science to genomics to astrophysics to internet commerce. Also available is the program code. You can use this online book to learn or increase your programming skills. Section 1.1 contains detailed instructions for installing a Java programming environment on your system.


Chapter 1: Elements of Programming
introduces variables, assignment statements, built-in types of data, conditionals and loops, arrays, and input/output, including graphics and sound.

Chapter 2: Functions
introduces modular programming. We stress the fundamental idea of dividing a program into components that can be independently debugged, maintained, and reused.

Chapter 3: Object Oriented Programming
introduces data abstraction. We emphasize the concept of a data type and its implementation using Java's class mechanism.

Chapter 4: Algorithms and Data Structures
introduces classical algorithms for sorting and searching and fundamental data structures, including stacks, queues, and symbol tables.

Chapter 5: A Computing Machine
introduces an imaginary machine that is similar to real computers. We specify the machine in full detail and consider machine-language programs.

Chapter 6: Circuits
introduces circuits and logical design, culminating in a description of how a machine might be built from the ground up.

Chapter 7: Theory of Computation
introduces the scientific discipline concerned with understanding (efficient) computational phenomena, whether it be man-made, in nature, or imaginary.

Chapter 8: Systems
introduces the basic components of computer systems that support programming: compilers, operating systems, networks, and application systems.

Chapter 9: Scientific Computation
introduces some of the most important algorithms that play crucial roles in our computational infrastructure, including numerical integration, matrix computation, data analysis, and Monte Carlo simulation.


Here are Lecture Slides that accompany this Computer Science book.

A Computing Machine:
0  Prologue  LFSR
5.1 - 5.3  A von Neumann Machine  Visual X-TOY
5.4 - 5.5  Machine Language Programming  Crazy 8

Building a Computer:
6.1  Boolean Logic and Gates  Hydraulic computer
Sequential Circuits
TOY Machine Architecture
 
Theory of Computation:
7.1 - 7.3  Regular Expressions and DFAs  DFA
7.4 - 7.6  Turing Machines  Turing machine simulator  Adder
7.7  Intractability
7.8  Cryptography  Crypto history

Systems:
8.4  Networking

Scientific Computing:
9.1  Floating Point
9.8  Monte Carlo Simulation

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]