Dynamic Programming, Greedy Algorithms can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform.

Greedy Algorithm: An iterative procedure that, at each step, selects the component offering the greatest immediate improvement in the approximation of an element.

CS 336 or Permission of Instructor Description This is an advanced undergraduate course on algorithms. This course examines such topics as greedy algorithms, dynamic programming, graph algorithms, ...

We consider the problem of approximating a given element f from a Hilbert space $\scr {H}$ by means of greedy algorithms and the application of such procedures to the regression problem in statistical ...

Brief Description of Course Content Covers the fundamentals of algorithms and various algorithmic strategies, including time and space complexity, sorting algorithms, recurrence relations, divide and ...

Greedy bases are those bases where the Thresholding Greedy Algorithm (introduced by S. V. Konyagin and V. N. Temlyakov) produces the best possible approximation up to a constant. In 2017, P. M. Berná ...

Introduction to programming in Python. Introduction to the theory of algorithms: running time and correctness of an algorithm. Recursion. Data structures: arrays, linked lists, stacks, queues, binary ...