This week on the channel +1.5M views this week

MIT OpenCourseWare's modeling class starts with a problem, not a system

Hazhir Rahmandad's hands-on seminar joins twelve new uploads, with examples spanning horse markets, energy efficiency and predator-prey dynamics.

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MIT OpenCourseWare Story of October 26, 2026Trari Newsroom

Why this story? The channel's weekly summary: what went up this week, what is drawing views now, and where the channel stands among similar channels.

Session 1: Stocks: Horse Market, Oil Market, and Transportation System

Things we can learn from the video

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5:20Students build models before class, submit their work, and use classroom critiques to refine their approach.
23:55The modeling process moves from problem definition through qualitative structure, simulation, calibration and analysis.
33:25Problem definition can begin with an observed behavior, a mechanism or a policy question.
42:25Model a specific problem rather than an entire system to avoid unmanageable complexity.
53:30Start with one stock variable, test equilibrium, and expand the model iteratively.
56:40Trace causal feedback loops, then break a suspected loop to test an explanation for the model's behavior.

Where do you start when a model threatens to become as complicated as the world it describes? Hazhir Rahmandad's answer is to narrow the problem, then build something small enough to test.

That practical instinct runs through "Session 1: Stocks: Horse Market, Oil Market, and Transportation System," MIT OpenCourseWare's most-watched new upload of the week, approaching 100,000 views. The Spring 2025 seminar bridges introductory coursework and professional modeling practice. Students submit their attempts before class, then work through critiques together. Getting something imperfect onto the page is part of the method.

Rahmandad warns against trying to model an entire system instead of a specific problem: complexity can swallow the project. For anyone stuck at the beginning, he offers a concrete route forward: start with a single stock variable, test it in equilibrium, and add structure gradually. Later, he explains how breaking a suspected feedback loop can help test whether it actually causes the behavior a model produces.

The comments have their own classroom logistics. Viewers point newcomers past the opening administration to the substantive discussion, while another describes learning advanced computer science and mathematics through OCW while still in school.

Twelve uploads filled the week, including lessons on predator-prey relationships, energy efficiency and market boom-and-bust dynamics. The opening session also has the strongest daily momentum, followed by the predator-prey lesson. An earlier conversation about MIT Open Learning's Wikipedia collaboration remains active too.

The channel added 10,000 subscribers over the week, matching the weekly gains at 3Blue1Brown and Johnny Harris, though its daily viewing is a little below its usual level. For OCW learners, the week's distinctive addition is a seminar that makes the unfinished model part of the lesson.

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What viewers say

Very Informative and Useful Content is uploaded by you for us. Getting free content from the world's Top School is not less than a lifetime present for me. MIT OCW has helped me learn Computer Science and Mathematics of higher level at the age of 16; I appreciate it so much. Thanks, MIT OCW, for such generous act of providing quality education free for us.
@JEE2028TOPPERSee it on YouTube
Starts @ 11:56
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This is the best Netflix
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2 more comments

10:32 wow very conscientious on this. Respect for having that perspective for his course system
@lukedowneslukedownes5900See it on YouTube
Tough lecture to ontologically put together, but still helpful
@lukedowneslukedownes5900See it on YouTube

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