Check out our interactive lecture material on computationalthinking.mit.edu!
MIT's numbering scheme gone nuts: (1.C25/6.C25/12.C25/16.C25/18.C25/22.C25)
This course is part of the Common Ground.
Lectures: Mondays and Wednesdays 1-2:30 PM in room 4-149.
Prerequisites: 6.100A, 18.03, 18.06 or equivalents (meaning some programming, dif eqs, and lin alg)
Instructors: A. Edelman, more TBA
Teaching Assistants: TBA
Office Hours: TBA
Lecture Recordings: ( Hopefully) Available on Canvas under the Panopto Video tab. Should be published the evening after each lecture.
Links: Worth bookmarking.
Piazza TBA | Canvas TBA | Julia | |
---|---|---|---|
Discussion | HW submission | Language |
Focuses on algorithms and techniques for writing and using modern technical software in a job, lab, or research group environment that may consist of interdisciplinary teams, where performance may be critical, and where the software needs to be flexible and adaptable. Topics include automatic differentiation, matrix calculus, scientific machine learning, parallel and GPU computing, and performance optimization with introductory applications to climate science, economics, agent-based modeling, and other areas. Labs and projects focus on performant, readable, composable algorithms and software. Programming will be in Julia. Expects students have some familiarity with Python, Matlab, or R. No Julia experience necessary.
Counts as an elective for CEE students, an advanced subject (18.100 and higher) for Math students, an advanced elective for EECS students, and a computation restricted elective for NSE students. AeroAstro students can petition department to count this class as a professional subject in the computing area. (Professors may be open to petitioning for counting for other programs.)
Class is appropriate for those who enjoy math and wish to see math being used in modern contexts.
While not exactly the same as our past Computational Thinking Class... not entirely different either.
Make mathematics your playground:
Throughout the course, students will be encouraged to adopt a new approach to thinking about, learning, and communicating technical systems and concepts.
We will demonstrate and produce Julia code which exemplifies a living, interactive approach to make math a fun and playful experience.
Perhaps similar to a CIM class (though this class is NOT officially a CIM , sorry)
we will have students present early versions of notebooks, with critiques (and
you get to critique the professor too). Nearly all university classes emphasize communication through writing and presentations, this class adds
communication through computation.
Percent | Comment | |
---|---|---|
Three Class Presentations | 25% | |
Final Project | 35% | |
Class Participation | 15% | |
Homeworks | 25% |
Homework | Assigned | Due | Topic | Solution |
---|---|---|---|---|
HW0 | Sep 4 | Sep 11 | Getting Started |
Lectures at a glance (Lectures being updated from 2023 as we go, but this semester there will be many more student presentations and discussions. Participation is a must.)
# | Day | Date | Lecturer | Topic | Slides / Notes | Notebooks |
---|---|---|---|---|---|---|
0 | Julia tutorial | Cheat Sheets | ||||
1 | W | 9/4 | Edelman | Communicate With Computation | Intro to Class | Intro to Julia, Tutorial, Hyperbolic Corgi, Images, Abstraction, |
2 | M | 9/9 | Edelman | Maybe you know Random Variables, but not as types? | slides Pluto Video | Random Variables As Types |
MOSTLY IGNORE BELOW | ||||||
3 | R | 9/14 | Edelman | Automatic Differentiation | Reverse Mode AutoDiff Demo | |
4 | T | 9/19 | Edelman | Matrix Calculus | Matrix Calc 1 | Matrix Jacobians, Finite Differences |
5 | R | 9/21 | Edelman | Matrix Calculus | Matrix Calc 2 | Linear Transformations, Symmetric Eigenproblems |
6 | T | 9/26 | Edelman | Differential Equations Lec 1 | Time Stepping (background), ODEs and parameterized types (main topic), Resistors and Stencils (touched on this) | |
7 | R | 9/28 | Edelman | Differential Equations Lec 2 | ||
8 | T | 10/3 | Edelman | Imaging and Convolutions | Image Transformation notebook | |
9 | R | 10/5 | Edelman | Imaging and Convolutions 2 | Seam Carving notebook, Linear Transformations notebook | |
T | 10/10 | Student Holiday | ||||
10 | R | 10/12 | Edelman | HPC and GPUs | HPC and GPU Slides | |
11 | T | 10/17 | Dalle | Package development | Challenge, Good practices | |
12 | R | 10/19 | Dalle | Performance | Quiz | Package creation, Performance |
13 | T | 10/24 | Dalle | Graphs | Quiz | Graphs |
14 | R | 10/26 | Dalle | Linear programming | Quiz | Linear programming |
15 | T | 10/31 | Ferrari | Greenhouse Effect | ||
16 | R | 11/2 | Ferrari | Equilibrium and transient climate sensitivity | Earth's Temperature Model Mean Surface Temp Modeling | |
17 | T | 11/7 | Drake | Economic Model of Climate | Slides | Economic Model, Optimization with JUMP |
18 | R | 11/9 | Edelman | Snowball Earth & Parallel/GPU computing | Snowball Earth and hysteresis | |
19 | T | 11/14 | Persson | Mesh Generation | Mesh generation | Computational Geometry |
20 | R | 11/16 | Persson | Mesh Generation | ||
21 | T | 11/21 | Edelman | Floating-point Arithmetic | ||
R | 11/23 | Thanksgiving | ||||
22 | T | 11/28 | Klugman | Fast inverse square root | Notebook | |
23 | R | 11/30 | Silvestri | Climate Science | Solving the climate system | |
24 | T | 12/5 | Silvestri | Climate Science | ||
25 | R | 12/7 | Edelman | Discrete and Continuous, are they so very different? | ||
26 | T | 12/12 | Class Party |