Hacker Courses The online courses programmers keep recommending, ranked from 20 years of public forum comments.
i
18.085 Computational Science and Engineering I
Image: ocw.mit.edu
#143 overall

18.085 Computational Science and Engineering I

MIT OpenCourseWare

3 recommenders · 3 threads · recommended in 3 years, 2011–2025 · score 3.1

Go to course ↗

MIT's 18.085 Computational Science and Engineering I, taught by Gilbert Strang, covers applied linear algebra, differential equations, and solving models numerically, often in MATLAB. The course is built around the companion text 'Computational Science and Engineering' and its recorded lectures.

Commenters call it one of the best math courses they've taken and praise Strang as a fantastic teacher, with lectures available free on MIT OpenCourseWare.

Mathematicsintermediatefreevideo lectures#applied linear algebra#differential equations#numerical methods#matlab#strang

Recommendations by year

20062026

What commenters said (3)

  1. Strongly recommendsjaviramos2025in “Robotics 101 at UMich: Applied numerical linear algebra as intro linear algebra”

    I took 18.085 (applied linear algebra) as a grad student at MIT. The best taught math course I've ever taken. Strang is a fantastic teacher.

  2. Strongly recommendshackermailman2020in “Ask HN: Recommendations for applied engineering and math books for programmers?”

    Gilbert Strang has an engineering text 'CSE' for creating models using differential eq and solving them entirely in MATLAB or other software. All lectures on MIT ocw https://ocw.mit.edu/courses/mathematics/18-085-computational... it's probably the best math course I've ever done.

    If you go on MIT Stellar you can get the most recent lectures if you want, but the book hasn't changed. MIT likely has a few more of these kinds of courses if you look at their most recent offerings, I've only done that book/course(s)

    Maybe you also want to program drones or robots or self driving cars http://symbolaris.com/course/lfcps.html this heavily uses differential invariants and all the lectures are open.

  3. Recommendsdvse2011in “Recommended Readings in AI - a list by Russell and Norvig”

    Certainly nothing remotely comparable to SICP exists. From my point of view people who are interested in these topics are much better off getting some intuition for basic problems in scientific computing and then making the requisite connections themselves. I can wholeheartedly recommend the recent book by Gilbert Strang "Computational Science and Engineering" [1] and companion video lectures for MIT courses 18.085 and 18.086.

    1. http://www-math.mit.edu/cse/

Related courses

Keyboard

In the course grid
←↑→↓
Move between courses
Home End
Start / end of row (with Ctrl: first / last)
PgUp PgDn
Jump several rows
Enter
Open course
S
Save / unsave course
1–5
Best, Trending, Hidden gems, Evergreen, Saved
[ ]
Previous / next topic
On a course page
← →
Previous / next course in your list
S
Save / unsave
O
Open the course website
Esc
Back to the grid
Everywhere
/
Search
T
Light / dark theme
?
This help