Handbook

How can a practitioner of algorithms help small-scale producers interested in sustainable farming?
How can you solve strategy games by efficiently using computation time and memory?
What do the relationships between difficult problems imply about the existence of feasible solutions to them, from both theoretical and practical standpoints?

In this course, you will learn the building blocks to develop problem-solving software in fields as diverse as finance, logistics, policy and entertainment. You will apply techniques including divide-and-conquer, greedy selection and dynamic programming in order to develop fast and accurate algorithms in contexts such as graphs and strings, and study reductions involving linear programming and NP-hard problems. You will also develop the ability to think critically and communicate about algorithms in terms of correctness and efficiency.

Join us to become a more effective, persistent and creative problem solver.