Algorithmic Toolbox
University of California San Diego
This online course covers basic algorithmic techniques and ideas for computational problems arising frequently in practical applications: sorting and searching, divide and conquer, greedy algorithms, dynamic programming. We will learn a lot of theory: how to sort data and how it helps for searching; how to break a large problem into pieces and solve them recursively; when it makes sense to proceed greedily; how dynamic programming is used in genomic studies. You will practice solving computational problems, designing new algorithms, and implementing solutions efficiently (so that they run in less than a second).
More resources on Algorithm Complexity
Algorithms, Part I
This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations. Part I covers elementary data structures, sorting, and searching algorithms. Part II focuses on graph- and string-processing algorithms. All the features of this course are available for free. People who are interested in digging deeper into the content may wish to obtain the textbook Algorithms, Fourth Edition (upon which the course is based) or visit the website algs4.cs.princeton.edu for a wealth of additional material. This course does not offer a certificate upon completion.
Complexity Zoo
Comprehensive list of complexity classes.
Visualgo
Interactive visualizations of algorithms and complexity.
Big-O Cheat Sheet
Quick reference for algorithm complexities.
freeCodeCamp - Big O Notation
Beginner-friendly crash course.
mycodeschool - Analysis of Algorithms
Playlist starter on complexity analysis.