Explore the concept of random walks in this 55-minute lecture from MIT's Computational Thinking Spring 2021 course. Delve into visualizing random walks, understanding Julia programming concepts, and examining the dynamics of hard discs. Learn about the motivation behind using random walks and how to implement a simple random walk. Gain insights into Julia benchmarking techniques and discover how to generate and analyze the trajectory of a random walk. Advance your understanding by exploring more general random walks using types, distinguishing between mutable and immutable structs, and working with functions that have type parameters. Conclude with a discussion on the update function and the rationale behind using immutable objects. This lecture provides a comprehensive overview of random walks and their implementation in Julia, suitable for those interested in computational thinking and programming.
Overview
Syllabus
Introduction.
Visualising random walks.
Julia concepts.
Motivation: Dynamics of hard discs.
Why use random walks?.
Simple random walk.
Julia: Benchmarking.
Trajectory of a random walk.
Making it more general: Random walks using types.
Mutable vs immutable structs.
Functions with type parameters.
update function discussion, why immutable objects?.
Taught by
The Julia Programming Language
