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  1. 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.

  2. Administrative Details, Exams - Time limit, Conflicts, Course Grade Breakdown, Assignment Details - Submission, Grading, Late Days, Course Email, Newsgroup, Facebook/Twitter, Mailing List, Course Prerequisites, Languages and Paradigms Taught - C++ vs. Pure C, Procedural Paradigm vs. Object-Oriented Paradigm, Assembly, Concurrent Programming Overview, Example of Data Sharing Issues with Concurrent Programming, Scheme, Functional Paradigm Ov...more

  3. November 16, 2007 lecture by Ge Wang for the Stanford University Human-Computer Interaction Seminar. In the first part of this talk, Ge presents the design, philosophy, and development of ChucK, a computer music programming language intending to provide a different approach, expressiveness, and thinking with respect to time and parallelism in audio programming - as well as a platform for precise and rapid experimentation. In the second par...more

  4. This course is all about understanding: understanding what's going on inside your computer when you flip on the switch, why tech support has you constantly rebooting your computer, how everything you do on the Internet can be watched by others, and how your computer can become infected with a worm just by turning it on. In this course we demystify computers and the Internet, along with their jargon, so that students understand not only wha...more

  5. Imperative/Procedural Paradigms (C) and Object-Oriented Paradigm(C++), Introduction to the Functional Paradigm (Scheme), Which Is Based on Synthesizing the Return Values of Functions, Example of a Scheme Function Definition that Converts Celsius to Fahrenheit, Scheme Environment (Kawa) Details, Scheme Primitives, Scheme Lists, Expressing Functions and Function Calls as Lists, Function Examples: <, >, and, Scheme List Operations: Car and Cd...more

  6. Pseudocode. Constructs: instructions, variables, conditions, branches, and loops. Languages: interpreted and compiled. Scratch.

  7. Overarching Features of Python: Scripting Language, Imperative, Object-Oriented, Functional, More Python Overview - Dynamic Typing, Use of Whitespace and Tabs, Python Environment, Execution of Basic Statements, Calling Methods Using Objects (And Anonymous Objects Like String Literals), Evaluating Assignments, Python Strings, String Methods, and Lists/Sublists (Including Index Wrapping), Strings as Lists of Characters in Python, Replacing C...more

  8. Sort Template with Callback, Supplying the Callback Function, One Last Convenience: Default Callback Function, Why Object Oriented Programming, Class Division, Class Interface in ".h" File, Storage for Objects, Accessing Members of a Class, Class Implementation, Implementing Member Functions, Maintaining Object Consistency, Constructors of a Class, Destructors of a Class, Basic Thoughts on Object Design, Internal vs External Representation...more

  9. Fundamental dynamic data structures, including linear lists, queues, trees, and other linked structures; arrays strings, and hash tables. Storage management. Elementary principles of software engineering. Abstract data types. Algorithms for sorting and searching. Introduction to the Java programming language.