6.046J - Introduction to Algorithms - Fall 2005, MIT OCW

This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow; computational geometry; and number-theoretic algorithms.

Introduction

This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow; computational geometry; and number-theoretic algorithms.

Highlights

• Covers a wide range of fundamental algorithm design techniques and analysis methods
• Taught by renowned professors Charles Leiserson and Erik Demaine
• Includes problem sets, exams, and video lectures to reinforce learning
• Suitable for both undergraduate and graduate students in computer science and engineering

Recommendation

This course is highly recommended for students looking to gain a deep understanding of algorithm design and analysis. It provides a solid foundation in the core concepts and techniques that are essential for success in computer science and software engineering. The course is suitable for both beginners and experienced learners, and the diverse range of topics covered makes it a valuable resource for anyone interested in improving their problem-solving and algorithmic skills.