Some people like to say that this is nothing new because video lectures were posted on the internet for several years now (for example MIT Open Courseware etc.), but I think this misses the point entirely. There is a huge difference between low-quality video/audio recording of a prof mumbling for an hour and post-processed, perfected snippets of videos presented in a coherent fashion, and most importantly with supplementary materials that encourage people to actually apply their knowledge and get feedback. In addition, the fact that many people take the class at the same time also enhances the experience for everyone, and we've seen study groups form everywhere around internet.
Full disclosure, by the way, I'm a CS PhD student at Stanford and I am a (voluntary) co-creator of the programming assignments for the current ML class. It is a lot of work, but the way I see it, we only have to put great assignments together a single time, and thousands of people can enjoy them and benefit from them for years and years to come. That is what I call time well spent.
I hope all these classes go well, and I'm looking forward to telling my kids about what education used to be like in the old days. I have a feeling that they'll find it hard to believe me.
As a consumer of Stanford's online classes(though not the ML class. I'm waiting for the CS 229 - vs the CS 229A - version), let me take the opportunity to thank you. Your efforts are totally appreciated. You are right, this is revolutionary. Glad to see that Stanford is keeping up (and building!) momentum rather than this being a one off effort.
The real hero behind the assignments is Jiquan Ngiam (http://cs.stanford.edu/~jngiam/) who is in charge and does most of the work. He is awesome, brilliant, very hard working, and I thoroughly enjoy hacking with him on the ML class until late AM.
Our personal thanks to you and the other "1.5 people" working on that. ;)
I agree that this is potentially revolutionary. Before these courses, I couldn't have imagined doing a 'distance-learning' course. I suspect there are many other folks that feel the same.
Also, thank you for your work on the ML programming exercises! I've found them fantastic in getting my head around how to practically 'encode' the things from the videos. Much appreciated.
Both are great resources, and I don't know that the Stanford classes will be able to sustain their ability to get people to create their own study groups. Our study group here in Cleveland Ohio gets 5 - 10 people each week, but we're drawing from areas almost an hour away. Future ML and AI classes will have a tougher time having that same draw, as those most interested will have already gone through the material and would be much less likely to drive an hour each week for a study group.
Survey classes like the ML and AI class work very well with this format. I'm looking forward to seeing how it fits with more specific classes. There are times in the AI class that are a bit "hand-wavy", which is OK for an over-view/survey class. I'd find that a bit more annoying on something like the upcoming natural language processing class.
Really? Or are you pioneers? I know reading your comment just greatly increased the probability that I will take another class (currently in db-class) and seek out a study group next time.
The AI and ML classes drew a lot of attention to start with (over 100k signups). Follow up or repeat classes will obviously draw less interest. I'm interested in seeing how that translates to viable study group sizes. The good news is that the minimum viable size of a study group is fairly small.
Also, good point about the programming exercises. Especially with topics like this I think it is easy to fall into trap of thinking you "got it" if you just watch the videos. Programming exercises force you to think it through on a whole different level and, I think, lead to better understanding and retention.
Anyway, great, I hope you stick with the class!
I swear, it's an extra pleasure hearing a song I like on the radio (over just playing it myself), knowing that a lot of other people are listening to it too. Maybe that's a new form of 'social computing' to be exploited :).
They're great stuff and he's really gotten me to understand a lot of the "why" of physics rather than just the "how".
Having said that, I'd love to have homework along with them, even just suggested problems with an answer key.
I have a question though, is there a way these classes can be made to be taken anytime a student wants?
The problem I am facing is that since I am also working fulltime, I just in time manage to submit the homework, and as a result, I can not take more than one classes at the same time, like the DB and AI classes in this case.
More importantly, for evaluation purposes, the quizzes and exercises can be submitted late, though penalized in points. Since what you get out of the course for having a high score (a certificate/letter of completion?) is worth about as much as toilet paper, you can still do the exercises and be evaluated on them even weeks later. We'll have to see if they keep the system running past the end of the semester - probably won't happen with ML, but maybe DB will stick around a bit.
AI, well, that doesn't have any homework.
So, next semester, sign up for all the courses, stick with all of them past the introduction week, pick one or you you'll focus on, and dabble in the rest.
Well, maybe not the CS101 course...
I don't feel quite like I am taking a real masters level computer science class mainly because the assignments are easier (you guys set up a lot of the boiler plate for us and we implement a few core algorithms). That said, the assignments have been a big part of me retaining the concepts and since they are not ball breakers, I can actually keep up with 30-60 minutes a day, with perhaps a couple hours one day on the weekend.
Professor NG is also an amazing teacher. I'm cautiously optimistic that the other teachers will be as good.
I started the site noexcuselist.com as a page to direct people to the best places to learn on the web. In doing so, I had to go through tons of web pages claiming that they taught things for free. The sites that I was really excited for like the Open Courseware sites were a bit of a disappointment for me. It'd be pretty hard for someone to learn a entire topic using it due to the incomplete lectures, some classes that weren't available, and the lack of lecture notes and homework that went with it.
I'm pretty excited to see the development of this one that you're working on though. Good luck and keep us posted!
By the way, will http://jan2012.ml-class.org/ be the same as the current ml-class? I mean is it the same course, or a more advanced one?
I was very impressed with the quality and especially how easy it is to submit them.
And the submission process is just mind-numbingly simple (which is good!).
Personal opinion being what it is for me I find it far easier to listen to Professor Sahami's recorded lessons (CS 106A) for an hour than I do Prof. Widom's into to DB classes. This is not intended as a slight to any person at Stanford. The real difference comes down to watching someone engage an audience and some one speaking to a camera.
Strictly my opinion based on a very small sample pool.
E-learning has the potential to: decrease the costs of getting an education, create the potential for "mass customization" of education, reduce credentialism in society, make learning an end in itself for many people, force universities to become less complacent, and probably many other effects I am overlooking right now.
Starting an e-learning startup is something I REALLY want to do. I love learning and I love startups.
I hope I can make that happen someday (nudges everyone with similar dreams).
When the number of dimensions is much greater than the number of samples and most of your cells in a matrix are equal to zero then most of the ML algorithms don't behave too well. It's very common problem in NLP to have sparse matrices.
New classes: (start in Jan/Feb 2012)
Computer Science 101: http://www.cs101-class.org/
Software Engineering for Software as a Service: http://www.saas-class.org/
Human-Computer Interfaces: http://www.hci-class.org/
Natural Language Processing: http://www.nlp-class.org/
Game Theory: http://www.game-theory-class.org/
Probabilistic Graphical Models: http://www.pgm-class.org/
Old Classes: (already started)
Machine Learning: http://www.ml-class.org/
Introduction to Artificial Intelligence: https://www.ai-class.com/
Introduction to Databases: http://www.db-class.org/
Technology Entrepreneurship: http://www.startup-class.org/
Learn Launchpad: http://www.launchpad-class.org/
So what are these courses? Video isn't working for me at the moment but judging by the descriptions they seem to be more involved than the CS courses:
Quoting from the Launchpad description:
Instead you will be getting your hands dirty talking to
customers, partners, competitors, as you encounter the
chaos and uncertainty of how a startup actually works.
Hey, think this means there might be even more courses coming out later?
I think its ideal to never go more than 2-3 minutes without asking us something, even if its trivial.
Right now I'm taking the AI classes, some of the units follow this rule and keep us paying attention through what I imagine would otherwise be some pretty dense stuff.
A few of the units (looking at you Professor Norvig) have had stretches 15+ minutes of lecture without asking us anything, just going to say, retention from those stretches was low.
Personally I really like it when they quiz our intuition of a subject before they lecture it, though it seems like other people complain about that on the reddit forum
101 is taught by Nick Parlante, though, who was one of my favorite profs at Stanford.
To me it has been surprising how big difference in experience the technical execution between classes made. Both Norvig and Thrun are clearly good teachers, but AI class failed because of the poor technical implementation.
The video editing is also fine. If such minor issues break your rhythm, you might need to rethink your approach to the lessons.
Given that there are still thousands of students in the class and enjoying it, it didn't "fail" at all.
Video editing in AI class is against the knowledge that we have learned in 100+ years of movie editing. Cutting 1-2 seconds but keeping the same scene gives a jarring experience.
They cut out a few seconds so that you don't need to watch Norvig or Thrun to finish writing of a word or sentence, but that's saving time in the wrong place in my opinion. If you watch Khan Academy or ML class, those 1-2 seconds give a natural pause, that you can use to think about the subject.
I've nothing against the pen and paper approach, although occlusion is sometimes a problem. Based on my experience with Khan, AI and ML classes drawing by hand is the essential thing, is it less important if it's done electronically or by pen and paper.
Anyway, my main point is that execution of e.g. Khan Academy and ML class are better than AI class, and I'd personally prefer that inspiration for new online education courses is taken from them instead of AI class approach.
On the other hand, the videos themselves are actually better (I love the pen-and-paper approach), and there's a lot more small questions within lectures, which helps keeping my ADD in check.
The AI class is like a beta test and there are plenty of bugs and problems. The content is still good, but the programming problems and automated grader that would be necessary for students to really absorb the advanced material doesn't seem to be on their radar. The result is a certain superficiality.
The ML class is much more developed. In the first few weeks the contrast of the finished, professional seeming ML class with the rough and hacky AI class was extreme but AI is catching up.
I'm looking forward to improvements in both platforms and new material in the spring. Other competitors like Kahnacademy are exciting, too.
I'd like to see more study groups around the world building this into a movement with broadening impact. Neither class had direct support for forming study groups. If you have to go on Reddit to get together with people, you're excluding 50-90% of the people who would use a simple no-friction geo-aware meetup-style tool if it were on the site's front page and main menu. Since study groups have a minimum size threshold to remain viable, that eliminates a magnified portion of potential participants.
So I'm pleased and still hope that this could be a mass-movement that leverages technology to change the way education is done around the world. Competing platforms is a better bet than one great platform for perfecting hard to build but needed features like labs, programming assignments, study group support, office hours and teachers' assistants, and homework help and hints.
The future, at least in our industry, is bright.
I'm sure things will improve in the next iteration, though, and after all I'm very grateful that all these courses are publicly available for free.
It was quite intensive thinking, though, really requiring concentration and effort; the courses themselves (ie just video) were maybe about 1 hour per unit, and there were two units per week.
Q: Will the materials still be available after the course is over?
At the very least, all of the materials in the OpenClassroom repository will be available, including videos with embedded quizzes, lecture notes, course materials, software guides, and extensive do-it-yourself exercises with solutions.
From AI class FAQ;
Will the videos be available without enrolling?
Yes, however you will not have access to any other features of the course including homeworks, exams, discussion groups, and posts from the professors.
So I guess you're out of luck as far as the web app, quizzez etc. All the videos are on Youtube so they will be available after the class has finished
Thank you so much, Stanford, the teachers for the modern and brave choice to teach people all around the world, thanks for all the students engaged in making the classes available for everybody. and thanks hn buddies for always giving the good news.
Will enroll to SaaS and hci or nlp.
On a serious note, does anyone know if there are plans to continue these courses next year? I suppose it will really depend on how well each class goes, but I mostly feel pressured to take these because I'm afraid I'll miss them.
I've been enjoying crawling my way through the great ML classes by Prof Andrew Ng, and had been wondering if by any luck other classes would be provided for future semesters. Seeing this just makes me really happy, and thankful to Stanford. Not only is it the future of education but also gives countless people around the globe a chance to learn topics they may otherwise have never had access to (I am one in this category).
Signing up for NLP!
also, what about the DB class ? will it be running again in 2012 ?
I couldn't "attend" more than one at the same time (especially the advanced tracks) and I already joined the ML class.
See here: http://ideashower.posterous.com/idea-platform-that-universit...
If anyone wants to work on this, contact me :)
Their patent pledge promises that they will not assert their rights against any open-source or home-grown initiative, which is why Stanford et al. are able to get away with hosting their own content in this format.
It's a harsh reality that by itself makes the case for patent reform.
The lectures are broken up into segments (which you might find convenient or annoying). There's not much more than that, unfortunately. If you want exercises, his problem sets are mostly from Kleinberg & Tardos, sometimes with problems from CLRS.
Thanks for everyone at Stanford working on this and making it possible. What an amazing collaboration between teachers and students (as the current ML, DB and AI classes show as well).
The only problem with the winter classes is I can't decide which to take!
The probabilistic graphical models looks like it may have a similar format as the introductory video mentions automatically graded programming exercises.
I think another part that worked well was that getting 100% for each exercise is readily achievable. I want to finish each exercise perfectly so I don't break my 100% record for the course. I think this works well for motivation.
Has anybody here tried this before? Are the videos webcasts or pre-recorded video that I can download/view at anytime?
Also is it open for everybody or will the sign ups be restricted?
All in all this looks awesome and I'm very much interested in the Game Theory and SaaS classes! :)
Course is like a typical Uni course. Lectures, readings, tests and exams.
I received an email a week before the class started.
Videos came out and could be watched in the browser or downloaded.
Open to anyone.
I went through all the videos on that subject in preparation for AI Class and it helped me tremendously.