A broad survey of the computer science discipline, focusing on the computer's role in representing, storing, manipulating, organizing and communicating information. Topics include hardware, software, ...

This course continues our data structures and algorithms specialization by focussing on the use of linear and integer programming formulations for solving algorithmic problems that seek optimal ...

It covers basic algorithm design techniques such as divide and conquer, dynamic programming, and greedy algorithms. It concludes with a brief introduction to intractability (NP-completeness) .

Introduction to Programming Systems An introduction to computer organization and system software. Developing skills for composing large programs, including modularity, abstraction, programming style, ...

Topics include algorithm design and program development; data types; control structures; functions and parameter passing; recursion; data structures; searching and sorting; and an introduction to the ...

Introduction to theory of algorithms guided by basic Python programming. Algorithmic thinking: Do you know how to multiply integers? Basic toolkit for the design and analysis of algorithms, and an ...

Algorithm design and analysis is fundamental to all areas of computer science and gives a rigorous framework for the study optimization. This course provides an introduction to algorithm design ...

Professor Adam Cannon’s famed Introduction to Computer Science and Programming in Java (COMS W1004) is one of Columbia’s most well-known CS courses, but we all want to know what a course is really ...

Instructors of a new self-paced version of Introduction to Computer Programming found that three weeks before the end of classes, about half of the students enrolled were halfway through the course ...

For 20 years, Paul Gries, a University of Toronto associate professor of computer science, teaching stream, has wanted to introduce a “self-paced” version of Introduction to Computer Programming, ...