Introduction to Algorithms (MIT)

This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow; computational geometry; number-theoretic algorithms; polynomial and matrix calculations; caching; and parallel computing.

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·         Video lectures: 6.064J/18.410J (MIT)

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Machine Structures

Course Introduction: The subjects covered in this course include C and assembly language programming, how higher level programs are translated into machine language, the general structure of computers, interrupts, caches, address translation, CPU design, and related topics. The only prerequisite is that you have taken Computer Science 61B, or at least have solid experience with a C-related programming language.

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·         Video Lectures: CS61C (Berkeley)

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Data Structures and Advanced Programming

Course Description:The CS 61 series is an introduction to computer science, with particular emphasis on software and on machines from a programmer’s point of view. CS 61A covered high-level approaches to problem-solving, providing you with a variety of ways to organize solutions to programming problems: as compositions of functions, collections of objects, or sets of rules. In CS 61B, we move to a somewhat more detailed (and to some extent, more basic) level of programming. As in 61A, the correctness of a program is important. In CS 61B, we’re concerned also with engineering. An engineer, it is said, is someone who can do for a dime what any fool can do for a dollar. Much of 61B will be concerned with the tradeoffs in time and memory for a variety of methods for structuring data. We’ll also be concerned with the engineering knowledge and skills needed to build and maintain moderately large programs.

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·         Video Lectures: CS61B (Berkeley)

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