Introduction to Algorithms
Discover the fundamentals of algorithms; this course provides the analysis and design techniques needed to enhance efficiency in problem-solving.
Introduction to Algorithms
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Course Description
Course Schedule
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Curriculum
Course Videos
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Lecture 1: Algorithms and Computation
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Lecture 2: Data Structures and Dynamic Arrays
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Lecture 3: Sets and Sorting
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Lecture 4: Hashing
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Lecture 5: Linear Sorting
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Lecture 6: Binary Trees
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Lecture 7: Binary Heaps
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Lecture 8: Breadth-First Search
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Lecture 9: Depth-First Search
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Lecture 10: Weighted Shortest Paths
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Lecture 11: Bellman-Ford
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Lecture 12: Dijkstra
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Lecture 13: APSP and Johnson
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Lecture 14: Dynamic Programming
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Lecture 15: Complexity
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Lecture 16: Course Review
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Lecture 17: Algorithms — Next Steps
About This Course
This course is designed for individuals who wish to learn the foundational building blocks of computer science and develop efficient, optimized solutions for complex problems. Offered by MIT, this comprehensive program covers essential topics such as the mathematical foundations of algorithms, complexity analysis, sorting and searching algorithms, tree structures, graph algorithms, and dynamic programming.
Throughout the program, participants will learn how algorithms are developed, how to choose the most appropriate solution approaches for different types of problems, and how to perform performance analysis of these solutions. Theoretical concepts are reinforced with practical examples, with the goal of cultivating strong algorithmic thinking and problem-solving skills.
This course serves as an ideal starting point for anyone seeking to build a solid foundation in fields such as software engineering, data science, or artificial intelligence.
About the Instructors
Prof. Erik Demaine
A member of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), Prof. Demaine is a world-renowned expert in algorithm theory, data structures, and algorithmic geometry.
Dr. Jason Ku
A researcher and instructor at MIT, Dr. Ku specializes in combinatorial algorithms and problem-solving techniques. He leads the problem-solving sessions within the course.
Prof. Justin Solomon
An expert in computer vision and graphics, Prof. Solomon also teaches the applied aspects of algorithms and optimization techniques.
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