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Learner Reviews & Feedback for Dynamic Programming, Greedy Algorithms by University of Colorado Boulder

4.9
stars
12 ratings
3 reviews

About the Course

This course 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) and using linear/integer programming solvers for solving optimization problems. We will also cover some advanced topics in data structures. 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. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder....

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1 - 4 of 4 Reviews for Dynamic Programming, Greedy Algorithms

By Spyros T

Oct 26, 2021

i went through this course just for a quick refresh on some basic algorithms and i ended completing all three courses from the specialization! the explanations from Pr.Sriram Sankaranarayanan are crystal clear and the way he presents the material is super! i finnaly understood dynamic programming and P-NP complexity classes, topics that were very comfusing for me. Thank you Proffesor!

By Dave M

Sep 21, 2021

Excellent. This course covers some difficult topics, but the lectures and homework assignments were superb and made them quite approachable.

By Abdikhalyk T

Dec 1, 2021

very good courses

d

By Rishabh S

Aug 5, 2021

Assignment language should be clearly mentioned.