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) .

View on Coursera Course Description. This course continues our data structures and algorithms specialization by focussing on the use of linear and integer programming formulations for solving ...

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

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, ...

Harvard University is now offering free online Computer Science courses, making Ivy League education accessible to all. These self-paced courses, avai ...

For students who are open to the full range of possibilities, the recommended first course is CS 1090 Introduction to Computing Principles, a foundational course on the path to all the computing ...

The graph below shows the total number of publications each year in Probabilistic Programming and Inference Algorithms. References [1] On the hardness of analysing probabilistic programs.

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 ...