Dynamic Programming

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Algorithmic Thinking (Part 2) (Coursera) Coursera
Rice University

Algorithmic Thinking (Part 2) (Coursera)

CS: Theory

Dive deeper into the world of Algorithmic Thinking in Part 2 of this insightful online course offered by Coursera. Designed for those who have already grasped the basics, this advanced class will train you in the mathematical concepts and processes that experienced computer scientists use to solve complex computational problems efficiently. Elevate your problem-solving skills and learn how to build more effective algorithms.

Jun 15th 2026
4 Weeks
Python Computing Algorithms
Details
算法基础 (Coursera) Coursera
Peking University

算法基础 (Coursera)

CS: Theory

本课程是为初学者设计的，旨在系统地介绍和练习计算机算法的基本概念和技巧。从简单的枚举到复杂的动态规划，通过大量编程练习，帮助学生提高解决问题的能力和编程技能。这门课将成为学习其他计算机科学课程或应用算法解决实际问题的重要基础。

Jun 15th 2026
5-12 Weeks
Programming Algorithms Recursion
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Algorithmic Toolbox (Coursera) Coursera
University of California, San Diego,Higher School of Economics - HSE University

Algorithmic Toolbox (Coursera)

CS: Software Engineering CS: Theory

Discover the power of algorithms with 'Algorithmic Toolbox', a comprehensive Coursera course that teaches you how to tackle everyday computational challenges. Learn sorting and searching, divide-and-conquer strategies, greedy algorithms, dynamic programming, and more through engaging video lectures and hands-on practice.

Jun 15th 2026
5-12 Weeks
Algorithms Debugging Data Structures
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Advanced Algorithms and Complexity (Coursera) Coursera
University of California, San Diego,Higher School of Economics - HSE University

Advanced Algorithms and Complexity (Coursera)

CS: Software Engineering CS: Theory

Step up your algorithmic skills with our Advanced Algorithms and Complexity course. Dive into intricate problem-solving techniques, including network flows, optimal matchings, and disjoint paths. Perfect for those ready to advance beyond the basics and explore sophisticated applications in various fields like computer vision and scheduling.

Jun 15th 2026
5-12 Weeks
Algorithms Data Structures Machine Learning
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Shortest Paths Revisited, NP-Complete Problems and What To Do About Them (Coursera) Coursera
Stanford University

Shortest Paths Revisited, NP-Complete Problems and What To Do About Them (Coursera)

CS: Software Engineering CS: Theory

Dive into advanced algorithmic concepts with 'Shortest Paths Revisited, NP-Complete Problems and What To Do About Them'. This course unravels the intricacies of shortest path algorithms, delves into the realm of NP-completeness, and equips you with strategies to tackle computationally hard problems effectively.

Jun 15th 2026
4 Weeks
Algorithms Data Structures Dynamic Programming
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Approximation Algorithms Part I (Coursera) Coursera
École normale supérieure

Approximation Algorithms Part I (Coursera)

CS: Software Engineering CS: Programming

Dive into the world of Approximation Algorithms Part I, an insightful online course designed to equip you with the skills needed to tackle NP-hard combinatorial optimization problems effectively. This course explores efficient methods for approximating solutions that balance computational efficiency with performance guarantees.

Jun 8th 2026
5-12 Weeks
Algorithms Computer Science Linear Programming
Details
Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming (Coursera) Coursera
Stanford University

Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming (Coursera)

CS: Software Engineering CS: Theory

Dive into the world of efficient problem-solving with our specialized online course on Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming. This course is designed for those who want to enhance their algorithmic skills and learn how to tackle intricate computational challenges effectively.

Jun 8th 2026
4 Weeks
Programming Algorithms Clustering
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Fundamentals of Reinforcement Learning (Coursera) Coursera
University of Alberta,Alberta Machine Intelligence Institute

Fundamentals of Reinforcement Learning (Coursera)

Data Science

Dive into the world of Reinforcement Learning, a crucial subfield of Machine Learning that focuses on developing intelligent agents capable of making decisions based on interaction with their environment. This course provides an in-depth understanding of statistical learning techniques where an agent takes actions to maximize rewards. Ideal for those interested in interactive AI and automated decision-making processes.

Jun 8th 2026
4 Weeks
ML Artificial Intelligence Machine Learning
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