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Avis et commentaires pour d'étudiants pour Dynamic Programming, Greedy Algorithms par Université du Colorado à Boulder

12 évaluations
3 avis

À propos du cours

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

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1 - 4 sur 4 Avis pour Dynamic Programming, Greedy Algorithms

par Spyros T

26 oct. 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!

par Dave M

21 sept. 2021

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

par Abdikhalyk T

1 déc. 2021

very good courses


par Rishabh S

5 août 2021

Assignment language should be clearly mentioned.