18.S191: Introduction to computational thinking for real-world problems

Welcome to the new 18.S191 course!

This is an introductory course on Computational Thinking. We use the Julia programming language to approach real-world problems in varied areas applying data analysis and computational and mathematical modeling. In this class you will learn computer science, software, algorithms, applications, and mathematics as an integrated whole.

Topics include:

Image analysis
Particle dynamics and ray tracing
Epidemic propagation
Climate modeling

Professors

Alan Edelman, David P. Sanders, Grant Sanderson, & James Schloss

Course Materials

A summary of all course materials posted so far is here.

Julia learning materials may be found here

Logistics

TR 2:30–3:30pm Eastern, online (Go to the lecture page on this site to stream it.)

Tuesdays: Prerecorded videos, released on YouTube and played live on this site.
Thursdays: Live sessions (same YouTube link 2:30–3) and MIT-only discussion (3-3:30); link to follow

Start date: September 1, 2020

Office hours TBD.

Discussion forum and homework submission

Discord: discussion (we encourage you to hang out here during class!)
Piazza: (MIT only) allows for anonymity to other students, discussion
Canvas: (MIT only) homework submission. If you're a non-MIT student, please find a partner to cross-grade homeworks via Discord.

Evaluation

12 weekly problem sets with equal weight; your lowest score will be dropped.
Released on Thursdays and due before the following Thursday's class. (No problem set during Thanskgiving week.)
No exams

Problem sets consist of code. MIT students enrolled in the course must submit homeworks via Canvas. If you are not a student then we encourage you to join the Discord and find a cross-grading partner.