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Structure and Interpretation of Computer Programs, 2nd Edition, (H. Abelson, G.J. Sussman) Videos
This book emphasizes the role of computer languages as vehicles for expressing knowledge and it presents basic principles of abstraction and modularity, together with essential techniques for designing and implementing computer languages.
Author(s): Hal Abelson and Gerald Jay Sussman
NA Pages 
Lecture Notes on Programming Theory for Management Information Systems
This note exlains the following toipics: Basic Business Data Analysis, Python as a Basic and Business Calculator, X Y Plots, Simple Data Analysis, Manipulating Data and More Complex Data Analysis, Reading In and Writing Out Text Data, Automating and Managing Information Systems, Managing Files, Managing Collections of Files Directories, Managing Collections of Files Searching and Designing Power Programs.
Author(s): Johnny Wei Bing Lin
140 Pages
This book explains the following topics: Linear Codes, Probability as Fancy Counting and the q-ary Entropy Function, Combinatorics, The Greatest Code of Them All: Reed-Solomon Codes, What Happens When the Noise is Stochastic: Shannon's Theorem, Bridging the Gap Between Shannon and Hamming: List Decoding, Code Constructions, Code Concatenation, Algorithms, Decoding Concatenated Codes, Efficiently Achieving the Capacity of the BSCp, Efficient Decoding of Reed-Solomon Codes, Efficiently Achieving List Decoding Capacity, Applications.
Author(s): Venkatesan Guruswami, Atri Rudra and Madhu Sudan
NA Pages
Algorithmic Introduction to Coding Theory
This note introduces the theory of error-correcting codes to computer scientists. This theory, dating back to the works of Shannon and Hamming from the late 40's, overflows with theorems, techniques, and notions of interest to theoretical computer scientists. The course will focus on results of asymptotic or algorithmic significance. Principal topics include: Construction and existence results for error-correcting codes, Limitations on the combinatorial performance of error-correcting codes, Decoding algorithms, Applications in computer science.
Author(s): Madhu Sudan
NA Pages
Programming from the Ground Up (J. Bartlett)
This book covers the following topics: Computer Architecture, Functions, Files, Reading and Writing Simple Records, Developing Robust Programs, Sharing Functions with Code Libraries, Intermediate Memory Topics, High-Level Languages and Optimization.
Author(s): Jonathan Bartlett
326 Pages
A Gentle Introduction to Programming (A. Cumming)
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Designing and Building Parallel Programs (I. Foster)
This book provides a practitioner's guide for students, programmers, engineers, and scientists who wish to design and build efficient and cost-effective programs for parallel and distributed computer systems. It covers the following topics: Parallel Computers and Computation, Designing Parallel Algorithms, Quantitative Basis for Design, Putting Components Together, Tools, Fortran M, High Performance Fortran, Message Passing Interface and Performance Tools.
Author(s): Ian Foster
NA Pages
Concepts, Techniques, and Models of Computer Programming (P. Roy, S. Harid, PDF, 939p) Mirror
This book covers the following topics: Introduction to Programming, General Computation Models, Declarative Programming Techniques, Declarative Concurrency, Relational Programming, Object-Oriented Programming, Encapsulated State, Concurrency and State, Specialized Computation Models, Semantics and Virtual Machines.
Author(s): P. Van Roy and S. Haridi
567 Pages
Learning to Program (Alan Gauld)
Simple Sequences, The Raw Materials, Loops, Branching, Modules & Functions, Handling Files, Handling Text, Error Handling, Regular Expressions, Object Oriented Programming, Event Driven Programming, GUI Programming, Recursion, Python in Practice, Working with Databases, Using the Operating System, Inter-process communications and Network programming.
Author(s): Alan Gauld
NA Pages
How to Think Like a Computer Scientist
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Patterns for Adaptive Programming (AP)
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