The primary topics in this part of the specialization are: greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, optimal search trees).
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À propos de ce cours
Résultats de carrière des étudiants
30%
36%
11%
Compétences que vous acquerrez
Résultats de carrière des étudiants
30%
36%
11%
Offert par

Université de Stanford
The Leland Stanford Junior University, commonly referred to as Stanford University or Stanford, is an American private research university located in Stanford, California on an 8,180-acre (3,310 ha) campus near Palo Alto, California, United States.
Programme du cours : ce que vous apprendrez dans ce cours
Week 1
Two motivating applications; selected review; introduction to greedy algorithms; a scheduling application; Prim's MST algorithm.
Week 2
Kruskal's MST algorithm and applications to clustering; advanced union-find (optional).
Week 3
Huffman codes; introduction to dynamic programming.
Week 4
Advanced dynamic programming: the knapsack problem, sequence alignment, and optimal binary search trees.
Avis
Meilleurs avis pour GREEDY ALGORITHMS, MINIMUM SPANNING TREES, AND DYNAMIC PROGRAMMING
I learned more about Greedy Algorithms and Algorithms to compute MST's and their importance on real world problems. Also I got to start to understand Dynamic Programming in a way I didn't before.
Tim Roughgarden is a fantastic teacher! He really cares about explaining in a simple manner and also give you useful hints and advices to dive deeper in all the topics of the course. Thanks, Tim!
Like the other courses in this specialization, the material is interesting and coherent. The pace is not fast enough to get lost and not so slow to insult your intelligence. I enjoyed it a lot!
One of the best courses to make a student learn DP in a way that enables him/her to think of the subproblems and way to proceed to solving these subproblems. Definitely helpful for me. Thanks.
À propos du Spécialisation Algorithmes
Algorithms are the heart of computer science, and the subject has countless practical applications as well as intellectual depth. This specialization is an introduction to algorithms for learners with at least a little programming experience. The specialization is rigorous but emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details. After completing this specialization, you will be well-positioned to ace your technical interviews and speak fluently about algorithms with other programmers and computer scientists.

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