MIT Missing Semester 2026
missing.csail.mit.edu
missing.csail.mit.edu
I did take one of the MIT intro CS MOOCs at one point for kicks. Very good. But it was more or less learn Python on your own if you don't already know it (or how to program more broadly). That doesn't really happen in a lot of other disciplines other than some areas of the arts.
Now, I'm sure some would argue "tough." What are you doing at MIT then? And certainly, there are SO many opportunities these days to get some grounding in a way that may not be as readily possible with chemistry much less nuclear engineering for example. But it is something I think about now and then.
I think it was this one, unfortunately archived now. I don't know the new one
https://ocw.mit.edu/courses/6-00-introduction-to-computer-sc...
I can only report that, had you dumped me into that content with those assignments, with no prior background I'd probably have been dropping that class.
The online version was more Grimson on the algorithms and Guttag (who wrote the Python book) on a bit of the programming. But the emphasis was more on the algorithms.
I'm also a CS guy so I can't directly challenge this on the whole, but my experiences in some classes outside of this in other domains didn't feel like they were 'comfortably' paced at all. Without extensive out-of-class work I'd have been completely lost in no time. In fact one electrical engineering course I took was ironically considered a weed out course, for computer science, as it was required, and was probably the most brutal (and amazing) class I've ever taken in my life.
I had basically a machine shop course in mechanical engineering in college. OK, it was a bit more than that but I had no "shop" in high school.
Certainly nothing in high school anything that would have really prepared me for a civil engineering or or chemical engineering degree.
I had actually done a little bit of fiddling around with electronics (and maybe should have majored in that). But certainly college would have been a whole different level. (With a whole lot more math which was never my strong suit.)
So, yeah, these days I think there's a different baseline assumption for CS/programming than many other majors.
Git, shell, basics.. even simple python if you have any at all programming experience - not nearly as hard as what they're teaching in the class.
Most of the time something like that like learning latex or git basics.. they'll say.. you'll pick up what you need. They're not gonna spend 12 weeks on those subjects they aren't hard enough.
Of course, you were struggling with fairly primitive tools at the time as well. Made a typo? Time to beg the grad students running the facility for some more compute cycles.
Although it's out of print I don't immediately see a full copy online. https://www2.seas.gwu.edu/~kaufman1/FortranColoringBook/Colo...
I thought that was pretty strange at the time because like 5% of the students end up going into research. So that was basically like him saying I'm totally cool with our educational program being misaligned for 95% percent of our customers...
Maybe it makes sense for the big picture though. If all the breakthroughs come from those 5%, it might benefit everyone to optimize for them. (I don't expect they would have called the program particularly optimized either though ;)
But it's also the case that (only half-joking) a lot of faculty at research universities regard most undergrads as an inconvenience at best.
In my experience, the more advanced the material, the worse the teachers are. Or more precisely, the improvement in teaching does not usually keep up with the increase in difficulty. (There appears to be no correlation, in fact.)
Which implies that the better a university is (the more difficult the material), the more it relies on filtering rather than education.
Which seems to be in line with how the top universities are perceived anyway as selection criteria, primarily places to get a network, rather than places to get an education.
It's neither good nor bad, but it is a little sad :)
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I do notice that my assumption here is that the more difficult the university is, the better it is. I think this is broadly true, both objectively and subjectively, at least for my purposes.
I think there are a number of ways in which financial incentives and University culture are misaligned with this reality.
A chemistry, physics, or even MechE BS is coming out only at the very beginning of their training, and will require lots of specific on-the-job training if they go into industry. School is about the principles of the field and how to think critically / experimentally. E.g. software debugging requires an understanding of hypothesis testing and isolation before the details of specific tech ever come into play. This is easy to take for granted because many people have that skill naturally, others need to be trained and still never quite get it.
Edit: of course if only 5% of grads are going on to research then maybe the department is confused. A lot of prestigious schools market themselves as research institutions and advertise the undergrad research opportunities etc. If you choose to go there then you know what you're getting into.
Out of one side of their mouth maybe.
Out of the other, they absolutely are not telling potential undergrads that they may tolerate them but they're really focused on research.
This. I went to the University of Iowa in the aughts. My experience was that because they didn't cover a lot of the same material in this MIT Missing Semester 2026 list, a lot of the classes went poorly. They had trouble moving students through the material on the syllabus because most students would trip over these kinds of computing basics that are necessary to experiment with the DS+A theory via actual programming. And the department neither added a prereq that covers these basics or nor incorporated them into other courses's syllabi. Instead, they kept trying what wasn't working: having a huge gap between the nominal material and what the average student actually got (but somehow kept going on to the next course). I don't think it did any service to anyone. They could have taken time to actually help most students understand the basics, they could have actually proceeded at a quicker pace through the theoretical material more for the students who actually did understand the basics, they could have ensured their degree actually was a mark of quality in the job market, etc.
It's nice that someone at MIT is recognizing this and putting together this material. The name and about page suggest though it's not something the department has long recognized and uncontroversially integrated into the program (perhaps as an intro class you can test out of), which is still weird.
While this comes out of CSAIL, I wouldn't ascribe too much institutional recognition to this. Given the existence of independent activities period, it's probably a reasonable place for it given MIT's setup. Other institutions have "math camp" and the like pre-classes starting.
It's probably a reasonable compromise. Good schools have limited bandwidth or interest in remedial education/hand-holding and academics don't have a lot of interest in putting together materials that will be outdated next year.
I think they rarely escape doing this hand-holding unless they're actually willing to flunk out students en masse. Maybe MIT is; the University of Iowa certainly wasn't. So they end up just in a state of denial in which they say they're teaching all this great theoretical material but they're doing a half-assed job of teaching either body of knowledge.
I also don't think this knowledge gets outdated that quickly. I'd say if they'd put together a topic list like this for 2006, more than half the specific tools would still be useful, and the concepts from the rest would still transfer over pretty well to what people use today. For example, yeah, we didn't have VS Code and LSP back then, but IDEs didn't look that different. We didn't (quite) have tmux but used screen for the same purpose. etc. Some things are arguably new (devcontainers have evolved well beyond setting up a chroot jail, AI tools are new) but it's mostly additive. If you stay away from the most bleeding-edge stuff (I'm not sure the "AI for the shell (Warp, Zummoner)" is wise to spend much time on) you never have to throw much out.
There certainly are fits and starts in the industry. I'm not sure the past 5 years or so looks THAT different from today. (Leaving aside LLMs.)
From my peripheral knowledge, MIT does try to hand-hold to some degree. Isn't the look-left and look-right, one of those people won't be here next year sort of places. But, certainly, people do get in over their head at some places. I tutored/TAd in (business) grad school and some people just didn't have the basics. I couldn't do remedial high school arithmetic from the ground up--especially for some people who weren't even willing to try seriously.
I could see it being obsolete quickly to the extent that when someone was trying to learn devops and saw a book on the (virtual) shelf that didn't cover containers next to one that did, they'd pick the latter every time. You probably saw this in your sales tanking. But I'm not sure many of the words you actually did write became wrong or unimportant either. That's what I mean by additive. And in the context of a CS program, even if their students were trying out these algorithms with ridiculously out-of-date, turn-of-the-century tools like CVS, they'd still have something that works, as opposed to fumbling because they have no concept of how to manage their computing environment.
The way DevOps evolved was sort of a mess anyway but welcome to tech.
I sort of agree more broadly but I can also see a lot of students rolling their eyes at using outdated tools which is probably less the case in other disciplines.
the same MIT that doesn't give out grades in the first year? (just Pass / NoPass)
the high achievers who scored solid grades to get there literally kill themselves when they pull Cs and Ds, even though it's a hard class and is sort of "look left, look right"
Yes, poor grades were often a shock to people accustomed to being straight A students in high school. Though most made it through or ended up, in some cases, going elsewhere.
Pretty sure most college CS programs have an optional class for those new to programming ( Introduction to Java or C or Python ). But after that, you are expected to learn new languages/tools on your own mostly.
Not sure how common at what are considered top schools without looking at course catalogs. I expect if you're really new to programming, jumping into a CS program at an elite school could be a bumpy ride given 90% of the class will have a fair bit of experience and the class will be pitched to that level.
I am fairly certain 100% of the top CS programs ( and 99% that every CS program ) in the country have an intro to programming class for incoming freshman with no background in programming - usually Python, Java or C. MIT does. Besides, there are tons of material online to learn programming on your own.
> I expect if you're really new to programming, jumping into a CS program at an elite school could be a bumpy ride given 90% of the class will have a fair bit of experience and the class will be pitched to that level.
Agreed. But the challenge isn't insurmountable.
But my general sense based on some level of connections is you're expected to figure out a lot of, for lack of a better term, practicalities on your own. I don't think there's a lot of hand-holding in many cases--probably more so in some domains than others.
Unfortunately I heard that class was retired and there was no direct replacement, which is a shame. It was an excellent crash course in shipping.
So the word on the street was that his was a good class to take if you wanted a chance to learn the programming language. (Because you have only so much time in the day to allocate to labs.)
And rumor was also not to say to the professor that you want to learn that language, because word had gotten back to him about the off-label draw of his class to many, and he didn't like it.
Example problem:
> Find every Orange Line station in Fall 2018 that, during time period 01 and the direction of 0, had a total ons passenger count greater than average for all Orange Line stations during that same time period, same season, and in the same direction. Report the station name and the total ons value. Sort the results by total ons in descending order and then station name in ascending order. Display the output like ‘Malden Center|21400’.
The lectures were primarily about algorithms, basic data structures etc and the extra "labs", taught by Teaching Assistants, was almost always for reviewing the lecture notes with a focus on answering questions.
At no point was there any discussion around "hey, here is a good way to design, write and test a program in a compiled language". My prior experience was with BASIC so just figuring out how to compile a program was a skill to pick up. I thankfully picked it up quickly but others struggled.
Another thing I saw often was people writing ENTIRE programs and then trying to compile them and getting "you have 500 compilation errors". I never wrote programs this way, I was more "write a couple lines, compile, see what happens etc" but it always struck me that even just suggesting that option in class would have helped a lot of folks.
(This being HN, I'm sure some people will say that students figuring this stuff out on their own helps weed out non-serious people but I still don't 100% buy that argument)
Edit: Nvm, they comment on it. https://missing.csail.mit.edu/2026/development-environment/
wonder how that's gonna work and if students will learn...
For similar reasons I think arts and humanities students should take marketing and business courses.
Which seems like a brilliant idea (part of their 4-1-4 academic calendar.)
- University being cost prohibitive to 90 percent of all humans as financial driven institutions, not performance.
- Before AI, 20 + years of google data indexing/searches fueling academia
- study groups before that allowing group completion (or, cheating, in your view)
- The textbook that costs 500 dollars, or the textbook software from pearson that costs 500, that has the homework answers.
I think it's a silly posit that students using AI is...anything to even think about. I use it at my fortune 500 job every day, and have learned about my field's practical day-to-day from it than any textbook, homework assignment, practical etc.
Totally dependent on school/department/professor policy.
Some are very strict. Others allow working together on assignments. (And then there are specific group projects.)