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Julia: Solving Real-World Problems with Computation, Fall 2026
(course material work in progress)

Real-world problems

We will take applications such as climate change and show how you can participate in the big open source community looking to find solutions to challenging problems with exposure to github and parallel computing.

An interactive lecture about climate economics. You can see the user moving the global CO2 emissions in one graph, and a second graph with global temperatures over 200 years responds.

Corgi in the washing machine

You will learn mathematical ideas by immersion into the mathematical process, performing experiments, seeing the connections, and seeing just how much fun math can be.

An image of prof. Philip the Corgi, but the whole image is swirled and twisted using a mathematical transformation. Overlaying grid lines are also twisted, showing the non-linearity of the transformation.

Revolutionary interactivity

Our course material is built using real code, and instead of a book, we have a series of interactive notebooks. On our website, you can play with sliders, buttons and images to interact with our simulations. You can even go further, and modify and run any code on our website!

An interactive lecture about the Newton method. A parabolic function is graphed, and we use sliders to control the number of iterations of the Newton method. Each iteration shows a tangent, demonstrating the algorithm.

Learning Julia

In literature it’s not enough to just know the technicalities of grammar. In music it’s not enough to learn the scales. The goal is to communicate experiences and emotions. For a computer scientist, it’s not enough to write a working program, the program should be written with beautiful high level abstractions that speak to your audience. This class will show you how.

A snippet of Julia code defining a new type called Sphere, with fields 'position', 'radius' and 'index of refration'.

Check out our interactive lecture material on computationalthinking.mit.edu!

Fall 2026 course page, under construction.

  • Instructor: Alan Edelman
  • Cross-listed as: 1.C25/6.C25/12.C25/16.C25/18.C25/22.C25
  • Time: Mondays and Wednesdays, 2:30 PM to 4:00 PM
  • Room: 45-102
  • MIT listing: Department of Mathematics course list

Teaching Experiment

We are working with two core beliefs:

  1. Humans like to learn, at least when it is not too stressful.
  2. LLMs can help us leapfrog our learning.

We will use LLMs to learn something beyond our prerequisites. Perhaps some of you will learn general relativity, a sophisticated climate model, Lie algebra, or how a car does regenerative braking, but the key requirements are:

  1. The material is something you conventionally would not have the background for, and you are on the honor system here.
  2. You learn it, create a Julia notebook (LLMs allowed!), and teach it to all of us, seminar style.

For the rest of the class, we want you engaged and asking questions.

Grading

Projects may be completed individually or in small groups, with each student responsible for understanding and presenting their part.

  • Homework: 25%
  • Class participation and questions: 10%
  • Learning proposal: 10%
  • Project notebook and development: 25%
  • Final seminar presentation: 30%

The first homework is a proposal for what you want to learn. Explain what interests you about the subject, what you hope to understand, and why it is a genuine reach beyond your current background. You should convince us that this is something you would not ordinarily be prepared to learn in this class without help, and that it is substantial enough for a notebook and a seminar-style presentation.

Project presentations will begin around the halfway point of the semester. The second half of the course will be devoted to student presentations, questions, and discussion.

Sign up for a presentation date between Oct 21 and Dec 7 by making a GitHub pull request. We may be able to have two or three projects on a date, and teams of two are allowed. Students who present earlier in the semester will receive a little extra credit for being courageous.

Calendar

Dates follow the MIT Registrar calendar.

# Day Date Lecturer Note
1 W Sep 9 Edelman
2 M Sep 14 Edelman
3 W Sep 16 Edelman
4 M Sep 21 Urschel
5 W Sep 23 Edelman
6 M Sep 28 Edelman
7 W Sep 30 Urschel
8 M Oct 5
9 W Oct 7
M Oct 12 Indigenous Peoples Day - holiday
10 T Oct 13 Monday schedule of classes
11 W Oct 14
12 M Oct 19
13 W Oct 21 Student presentations
14 M Oct 26 Student presentations
15 W Oct 28 Student presentations
16 M Nov 2 Student presentations
17 W Nov 4 Student presentations
18 M Nov 9 Student presentations
W Nov 11 Veterans Day - holiday
19 M Nov 16 Student presentations
20 W Nov 18 Student presentations
21 M Nov 23 Student presentations
W Nov 25 Class canceled for Thanksgiving
22 M Nov 30 Student presentations
23 W Dec 2 Student presentations
24 M Dec 7 Student presentations
25 W Dec 9 Class party

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