22 ms·

Artificial Intelligence Graduate Certificate

224 points by tma-1 10y ago

ganeshkrishnan 10y ago
Not sure if people remember but Stanford in collaboration with Sebastian Thrun offered one of the first online educational course in Machine Learning. This piqued my interest in ML and I enrolled & completed the course from one of the most rural parts of India (I had to create an extension antenna for my 3g phone to get better reception). Udacity was born due to the popularity of this course. Can't thank Sebastian and Stanford enough for this free course.
- dswalter 10y ago
  That's a [edit:perfectly fine] example to choose for a Stanford MOOC, since Coursera was started based on the success of Andrew Ng's machine learning course. edit: People below (and above) are more knowledgeable than I am.
  - robotresearcher 10y ago
    Thrun's course was offered earlier* and Udacity launched earlier. What's funny? * edit: I just learned the courses were simultaneous. Udacity launched June 2011, Coursera April 2012, according to Wikipedia.
    - bitL 10y ago
      Thrun & Norvig did Intro to AI, Ng did Machine Learning, Koller did PGM (another course related to AI/ML) and Widom did DB/SQL, which is how it all started. Thrun then started Udacity, Ng & Koller started Coursera.
      - deleted 10y ago
        [deleted]
    - cr0sh 10y ago
      No - AI Class (Norvig/Thrun) and ML Class (Ng) both ran at the same time, in the Fall of 2011. I took both courses, but only completed the ML Class (I had to drop the AI Class due to personal issues at the time). I'm not sure which MOOC company started first (in 2012), though - I do think it may have been Udacity. I know that when it did start, it wasn't able to offer the AI Class because of {reasons} (I think maybe licensing of course content or something) - and so instead it offered the CS373 course (at the time titled "How to Build Your Own Self Driving Vehicle" or something like that). By that time (Spring 2012), I had moved on past my earlier problems, and jumped at that course - I took it and completed it as well. Coursera, meanwhile, was able to offer the original ML Class as a premier course (maybe Ng had different rights to the content, or maybe there was issues on the AI Class that had to do with the dual instructor partnership of the class - I'm not sure what really happened there). After about a year (IIRC?), Udacity was able to finally offer the original AI Class as part of their courses (I think now renamed "Introduction to Artificial Intelligence"). Today, I'm taking the Udacity Nanodegree course, as I've noted before here. I think this offering from Stanford is interesting, but it doesn't seem like it is currently "available" to enroll, because the two required courses seem closed or something? Maybe they're taking enrollment for a future starting date. That said, while the tuition isn't outside of something I could do, I currently think the best use of my money and time - after I complete the Udacity thing - would be to pursue getting a BA on CompSci or something of that nature, then pursuing other paths. Should've done it a long time ago when I was younger - but I was dumb.
      - XenophileJKO 10y ago
        Let's not do anything drastic. If you've finished those courses and have decent experience a bachelor's degree will get you little to no practical value. If there are holes in your knowledge, by all means fill them, but a degree of little value is not a good investment in this line of work. You are better off filling holes in your knowledge and build something awesome. That's it. You want an interview & offer at Google, facebook, Microsoft, it's pretty easy with a solid portfolio and a few months study or refresh on algorithms.
  - realitygrill 10y ago
    Actually, Thrun's AI course, Ng's ML course, and Widom's Databases course were announced and ran pretty much simultaneously. They were all successful, but only Thrun decided to split off because of it.
    - melling 10y ago
      I noticed that Andrew's course is still available. https://www.coursera.org/learn/machine-learning https://www.coursera.org/learn/machine-learning Is it still a good introduction to machine learning? It's several years old now. Are there better courses available?
      - ktta 10y ago
        That course is a very good basic machine learning course. It has many of the stepping stones to complex machine learning problems, no matter which specific field. So yes, it is a good intro to machine learning. There are new advances coming up all the time. But you will definitely need to know most of the topics in that course. That is, if you want to properly understand most of the latest techniques.
        visarga 10y ago
        It also works great psychologically - concretely, Andrew is capable of inspiring enthusiasm and confidence.
        mwambua 10y ago
        I see what you did there. :) Someone even made a drinking game out of it: https://www.reddit.com/r/mlclass/comments/lvxuz/mlclass_drinking_game_drink_every_time_professor/ https://www.reddit.com/r/mlclass/comments/lvxuz/mlclass_drin...
      - nl 10y ago
        It's a good course. The only(?) real criticism of it is the reliance on Matlab/Octave.
- nafizh 10y ago
  Did that course actually. Sebastian Thrun and Peter Norvig were the instructors. Still have the certificate from the course(back then they used to provide signed certificates from the instructors for free).
Xcelerate 10y ago
If one's goal is to work at OpenAI, FAIR, or DeepMind, which would be a better use of time — obtaining this certificate or getting quality papers into NIPS / ICML?
- Kephael 10y ago
  Certainly the latter, getting published in top journals or conferences is several orders of magnitude more difficult.
- ChuckMcM 10y ago
  Wow tough call. The certificate would represent a baseline of understanding which can be then further trained, a good publication history in NIPS/ICML Etc. would represent a solid contribution to the field. I would not be surprised if those were, to a first approximation, equivalent.
  - poikniok 10y ago
    This has to be sarcasm right?
    - kahnjw 10y ago
      Clearly
b1gtuna 10y ago
Would anyone recommend this over doing a masters degree in the similar area of study but at a local university (ie. not Standford)?
- snowcrshd 10y ago
  I'm curious about this as well. I have interest in AI, but I'm not sure how companies would see this online degree (even through it is from Stanford).
  - mindcrime 10y ago
    I would think it depends on the company. Remember, the world is a LOT bigger than GoogHooBookSoftBer or whatever. Walk into Tom's Auto Salvage or City Chevrolet or Barney's Screen Doors and Small-Engine Repair and show them that you can produce value for their business, and I don't think they're going to give a hoot if your degree/certificate/whatever is from Stanford, Yale, UNC-W, ECPI, or University of Phoenix.
- nkozyra 10y ago
  Hard to say without having taken these classes. GT isn't Stanford but a top 10 MSCS that offers an ML specialization for ~$8k-$10k. Whether that provides more value or employment opportunity I cannot say, but it is encouraging to see more to universities offering an alternative to traditional degree programs. I think there's a path for non-MS, non-PhD backgrounds, but probably not now. Outside of the big companies, ML/AI is often a solution without a problem. So until they learn practical application I think supply will outnumber demand and most of the jobs will go to PhD AI/statistics backgrounds.
  - mindcrime 10y ago
    Outside of the big companies, ML/AI is often a solution without a problem. I would say just the opposite. There isn't a business too small to benefit from ML/AI. That is, assuming you acknowledge that there's more to ML/AI than "deep learning". Not everybody needs a deep neural network. Sometimes you just need linear regression or a random forest. If you come at it from that point of view, the knowledge you gain from taking Andrew Ng's machine learning course is enough to create value for companies / organizations. A lot of the discussions on this topic here on HN seem to be based on an assumption that you have to be doing cutting edge original research to be useful. I think that's very far from the case. Now the problem is, does the mom and pop bakery on the corner know that they could benefit from ML? And perhaps the more salient question is "are they looking for somebody to do ML for them"? The answer is probably "no" in both cases, so you might have to do some work to sell to that market. But the value you can create is real. Help them optimize production so they throw away less bread on slow days, etc. and you're talking direct business impact. I suspect that there will be, for a long time, a wide continuum in terms of how ML/AI skills can help create value. Which means there will be a lot of ways to leverage this field from a career standpoint.
zxcvvcxz 10y ago
How do people in industry generally view these types of certificate programs? Is it markedly "worse" than doing e.g. a Master's on campus? Also - is this closer to a Master's level program or part of an undergraduate curriculum?
- bitL 10y ago
  If you look at pricing, it's below their Master level so I guess is more undergrad-style.
- nkozyra 10y ago
  The available classes align with graduate level one's for their MSCS. If nothing else it's markedly worse because it's 1/3 the classes :). Beyond that I'd expect rigor ... it's Stanford after all.
  - jayajay 10y ago
    I am feeling that even a non-Stanford place would present more rigor than an online Coursera course. When I was in school, I benefited greatly from having 1-1 private conversation time with mathematicians, scientists, grad students, my friends, etc. With Coursera, that person is replaced by Google/Bing/Whatever. If I don't get time to talk to the scientists or grad students (at least), I don't see how Udacity/Coursera/etc. are anything more than a glorified YouTube. Maybe I am disillusioned, but the value proposition from Coursera/Udacity/etc. is looking worse and worse as I look at it more and more... hmm...
    - nkozyra 10y ago
      When you pay for Udacity/Coursera/etc you at least get human interaction with paid instructors and other students.
- torinmr 10y ago
  The courses are identical to the courses one would take if they were getting their Master's at Stanford - the only difference is that only four classes are required, while a Master's requires about 15. I'm enrolled in Stanford's CS Master's program right now through the Honors Cooperative Program (which lets you get a Master's online while working in industry), and I'm currently planning on doing a dual specialization in Systems and AI. For the AI specialization I've already taken CS 221 and 229, and I'll have to take three more AI classes drawn from a list pretty similar to the Elective Courses list in the OP.
sharps_xp 10y ago
Are ML/AI certificate holders competing for the same jobs as ML/AI PhD graduates? I have a list of follow up questions to this but it seems like there's a lot of hype for ML/AI/DeepLearning but no definitive way to track this new job market. These online programs, although more accessible, are doing the same thing as their physical campus counter part and not being transparent about what to expect after finishing their programs.
- ganeshkrishnan 10y ago
  ML/AI is very new field. I heard someone say "AI is like teenage sex. Everyone is talking about it but no one is sure how to do it" So for jobs, ML/AI is pretty much an even field unless there are niche research jobs which only requires Phd gradudates
  - richard___ 10y ago
    According to another HN thread this is actually not true. Only having a certificate, without CS/AI undergrad, makes it almost impossible to get a job. You need Masters at least for most positions, some engineering positions you can get in with Undergrad in CS and taking the right AI courses.
    - jayajay 10y ago
      Do people in the tech industry find any more value in physics/math undergrads than CS? CS is not as rigorous. I always thought that physics/math undergrad + ML certificate might be just as competitive as a masters in ML coming from a non-relevant BS
      - deleted 10y ago
        [deleted]
      - aerioux 10y ago
        I'm going to have to disagree. Physics/Math is useful but your particular field/speciality in CS is relevant as well. I would bet a bit more money on a CS grad to understand convexity, comp geometry and optimization than a physics grad, and math majors don't always have the code skills to develop things for production. Point of argument here being frequently neither do CS Phds and at tech companies you pair Math/CS Phds with 'production' engineers. Also certificates aren't really rigorous necessarily and also are quite easy to one-off versus relevant programs/theses/research experience. production is an overloaded term depending where you go
bitL 10y ago
Oh well, as someone who is currently enrolled into Udacity's Self-driving car and AI nanodegrees, watching ongoing MIT's self-driving course, considering taking GATech's online M.S. degree for ML, I should probably start planning budget for this Stanford offering...
- benliong78 10y ago
  Wow that's a lot of learning. By MIT self driving course are you referring to http://selfdrivingcars.mit.edu/ http://selfdrivingcars.mit.edu/ ?
  - bitL 10y ago
    Yes, that one. It's more difficult than Udacity's SDC but also more real-world oriented. I also have subscribed to most of the Udemy courses related to CNN/RNN/reinforcementL/ML so I have a lot of fun ahead ;-) Hope you enjoy playing with ML as well!
- ConAntonakos 10y ago
  Awesome! I'm also currently taking Udacity's self-driving car nanodegree, but I think I only intend on doing the first of three semesters because I want to concentrate on the fundamentals, and not necessarily self-driving cars. Do you recommend enrolling or checking out the AI nanodegree? Have you looked at the ML one?
  - bitL 10y ago
    It's too early to evaluate AI nanodegree as it has just started and so far we did Sudoku solver ;-) As for ML, I have it on my mind after SDC & AI, though already took Ng's first run of ML one so I am not sure it would be that beneficial. So far SDC is the best fun I had in a while, getting a car drive all by itself on a circuit feels absolutely cool! ;-) Have fun as well, I hope they have more cool stuff prepared for us!
jtagen 10y ago
Why not take the Georgia Tech online MSCS instead? Only $7k, you get a Master's degree instead of a 'Certificate', and you have the option of covering a lot of the same material.
- eranation 10y ago
  Yep. And Sebastian Thrun's course (the Stanford professor, google VP, Udacity founder and google driverless car initiator) is part of that program. You can take AI for robotics for credit there :)
  - XenophileJKO 10y ago
    They require a previous undergraduate degree, which is a no go for me. I'm already a high level software engineer at a top tier company. I have no desire to go back and take an undergraduate degree. But I do like collecting certificates... Currently taking Udacity's self-driving nano-degree, pretty fun for someone with no robotics background.
    - jedberg 10y ago
      How closely do they check the undergrad degree? Some second rate universities will trade you a degree for experience plus cash. Most of them are non-accredited though.
      - alnitak 10y ago
        Do you happen to know any accredited university or institution that would do that? Maybe with some examinations?
        dsacco 10y ago
        I don't think any actual accredited university would allow you to "test out" of an entire four year degree, let alone simply buy it because you have comparable experience.
ClearAsMud 10y ago
Anyone have suggestions on alternative programs that are less expensive, online, and self-paced? 40+ IT guy trying to stay relevant.
- dnkrtz 10y ago
  Columbia University has an Artificial Intelligence MicroMasters on EdX, first cohort started this month. It's free, or 1200$ if you want Columbia course credit.
  - leereeves 10y ago
    According to the EdX page, course credit is only available to Columbia University Master of Computer Science students. https://www.edx.org/micromasters/columbiax-artificial-intelligence https://www.edx.org/micromasters/columbiax-artificial-intell...
    - marcstreeter 10y ago
      Would you provide the actual bit you're interpreting? These are the words I see: ------------- Who is this MicroMasters Program intended for? The MicroMasters Program in Artificial Intelligence is intended for those who have a Bachelor’s degree in Computer Science or Mathematics and have a basic understanding of statistics, college level algebra, calculus and comfort with programming languages. ------------- I don't see it mentioning anything contrary to the above statement. The micro-masters wouldn't be a full fledged master's degree, but could allow admission to receive a full masters (per the below): ------------- Complete, pass and earn a Verified Certificate in all four courses to receive your MicroMasters Credential. Learners who successfully earn the MicroMasters Credential are eligible to apply to the Master of Computer Science program at Columbia University. ------------- Maybe I misunderstood you.
      - leereeves 10y ago
        Other than the tagline "A series of credit-eligible courses recognized by industry", this is the only reference I found to course credit: > Take your Credential to the Next Level > If a student applies to the Master of Computer Science program at Columbia and is accepted, the MicroMasters Credential will count toward 25% of the coursework or 7.5 of the 30 credits required for graduation from the on campus Master of Computer Science program. This part: "Learners who successfully earn the MicroMasters Credential are eligible to apply to the Master of Computer Science program at Columbia University" doesn't seem to mean anything. Isn't everyone already eligible to apply?
deepGem 10y ago
The toughest curriculum in any AI related MOOC I've seen so far. Just CS228 - Probabilistic Graphical Models is enough to bleed someone's brain. Wish Daphne Koller still taught that course.
- XenophileJKO 10y ago
  You are in luck. They have just re-released it on Coursera. https://www.coursera.org/specializations/probabilistic-graphical-models https://www.coursera.org/specializations/probabilistic-graph...
  - deepGem 10y ago
    That's awesome! Thanks for the link
- XenophileJKO 10y ago
  You are in luck. They have just re-released it on Coursera. https://www.coursera.org/specializations/probabilistic-graphical-models https://www.coursera.org/specializations/probabilistic-graph...
Animats 10y ago
$20K for a few online courses? Genesereth teaching logic and automated reasoning? (I took a class from him once. Exam question: "Does a rock have intentions?")
- m-photonic 10y ago
  So, does it?
  - trendia 10y ago
    You have to take the class to find out!
    - Bombthecat 10y ago
      You won't believe what happens next! Find out for just 20k!
      - CervezaPorFavor 10y ago
        In the end, the answer is "it depends."
    - deleted 10y ago
      [deleted]
WhitneyLand 10y ago
Stanford is just trying to cash in on people by having their cake and eating it too. They want to charge 20k, but not let anyone have a chance of further advancing to complete a real degree, no matter how excellent their performance in this program. The reason they do this is solely to protect their brand and exclusivity. They already offer online degrees but the acceptance rate is just as limited as the on campus program. Yes the learning is important, but so is the credential and a certificate doesn't even come close to a degree in the job market. Stanford should pick one: 1) Charge Stanford prices, scale up online, and let any student who can do the work pay tuition and earn a degree. 2) Charge lower prices for certificates and continue to artificially ration real degrees.
- deleted 10y ago
  [deleted]
- adamkochanowicz 10y ago
  For me it's valuable the way they've constructed it. I like the idea that I can take some night classes in addition to my full time job, and just focus on one specific area. Okay, graduate degrees fulfill that purpose too, but with life events now and over the horizon, I just don't have the bandwidth to commit to getting my Masters or a Ph.D. right now. I really have no problem with this.
  - Bombthecat 10y ago
    But why pay for it than?
    - xyzzy123 10y ago
      They're betting that a certificate with "stanford" on it is better than a certificate with "udacity" or "coursera", or "I read a bunch of web pages and books", "heres my kaggle ranking" or "look at this stuff I did on github and corresponding blog posts". [naturally people breaking into the field need not pick just one]. Depending on hiring filters, that might be true. If an application ever gets to an engineer though I'd bet on the last one or two winning. I think a sensible organisation should skip the usual hiring filters in new fields, because [edit](my experience is in security) you can scoop up really good people who happen to have "unconventional" backgrounds if you have competent people evaluating them. Regular HR people tend to do a really bad job with career switchers and the self taught since they mostly work off "signalling value". But in newer or very fast moving fields, the oddballs can be majority of decent applicants. My limited experience is that very technical positions are not actually overwhelmed with applicants, and that it's not hard to evaluate if people have the right stuff because in these areas it's not difficult to devise quite objective challenges without resorting to shibboleths (guess what the interviewer is thinking or, do you come from the same technical culture as me). Arguably ML positions should be the easiest to algorithmically hire for (at least for industry, not hard core research). Just put an automated judge with a fairly low bar on a business relevant objective function between your careers and your "submit job application" page :p Personally I find this a little bit funny, because ML driven competence evaluation in "hard" (reasonably concrete objectives) fields should eventually render credentialism and signalling obsolete. But here we are, the $20k "certificate". All these things said, a structured course of study is super useful for the undisciplined (certainly including me) and dropping "new car money" on something has a way of focusing the mind :)
betadreamer 10y ago
Can you get similar knowledge through books? In general what book do you recommend? I'm specifically interested in deep learning.
- kriro 10y ago
  I think "Artificial Intelligence a Modern Approach" is still the best foundation book. However it certainly is not focused on deep learning. There's chapters on pretty much everything (one on reinforcement learning) but it is build around the idea of intelligent agents first and foremost. Best written CS book I own.
  - sqldba 10y ago
    I'd love to read a book like that but I don't have any maths, and I presume those things are full of maths.
    - kriro 10y ago
      I think this book is actually very approachable without much of a mathematics background. It's structured so that you can usually skip the mathy parts (and there aren't many really). Time and space complexity might be a bit tough but it's not that hard to work through. I think the Bayes related math was explained well and should be approachable with next to no math knowledge. The math is mostly applied and not proofs. There's a fair amount of pseudocode and algorithms but they are explained well and I think it's not hard to follow (our students of different backgrounds usually didn't have problems). I did get a bit tired of the running example of the map of Romania (essentially used for all the search related things). The diagrams for algorithms are very helpful.
theCricketer 10y ago
This costs about $15k - $19k. With all the great lecture and homework content out on the Internet about AI, ML, deep learning, vision and natural language, I wonder if one can put together a more comprehensive and customized version of this that one can learn for free.
- jbarciauskas 10y ago
  EdX is strongly committed to learning being free. You can audit any of the courses in the AI MicroMasters for free. https://www.edx.org/micromasters/columbiax-artificial-intelligence https://www.edx.org/micromasters/columbiax-artificial-intell... (EdX employee)
kriro 10y ago
20k or 10k per required course (there's electives but let's assume the bare minimum) seems steep for an online certificate which seems fairly worthless from a signaling POV. I'm not sure their brand name justifies that price (not sure about the content). The competition is probably the AI nanodegree from Udacity which costs 800$/term with the chance to earn some of that back. If the employer I want the certificate for knows what online certificates are, chances are they are familiar with Udacity (possibly more so than with Stanford in that market).
amelius 10y ago
> Software engineers interested in acquiring a solid foundation in artificial intelligence. Does a "solid foundation in AI" actually exist? I'm asking because it seems that nobody really knows why many algorithms actually work, or even how they should be adjusted to cover new applications. To me it sounds more like "educated guessing".
- grayshirts 10y ago
  If you are talking about ML then: Bayesian stuff, Variational and MCMC, Graphical models, Deep Learning, Linear Algebra, Probability theory, Statistics, Multivariate Calculus, Optimizations - as a baseline. I think the "average" person on HN would not be interested in ML if they had to learn it rigorously. It's much easier to blackbox the entire thing and label yourself as a "ML Engineer" then learn the fundamentals listed above. Having a Stats/Applied Math background would be very helpful.
sp332 10y ago
Darn, I thought they were preparing to give degrees to AIs.
oculusthrift 10y ago
This only makes sense for people whose work will pay for them to take it.

224 points by tma-1 10y ago

Not sure if people remember but Stanford in collaboration with Sebastian Thrun offered one of the first online educational course in Machine Learning. This piqued my interest in ML and I enrolled & completed the course from one of the most rural parts of India (I had to create an extension antenna for my 3g phone to get better reception). Udacity was born due to the popularity of this course. Can't thank Sebastian and Stanford enough for this free course.

dswalter 10y ago
That's a [edit:perfectly fine] example to choose for a Stanford MOOC, since Coursera was started based on the success of Andrew Ng's machine learning course. edit: People below (and above) are more knowledgeable than I am.
- robotresearcher 10y ago
  Thrun's course was offered earlier* and Udacity launched earlier. What's funny? * edit: I just learned the courses were simultaneous. Udacity launched June 2011, Coursera April 2012, according to Wikipedia.
  - bitL 10y ago
    Thrun & Norvig did Intro to AI, Ng did Machine Learning, Koller did PGM (another course related to AI/ML) and Widom did DB/SQL, which is how it all started. Thrun then started Udacity, Ng & Koller started Coursera.
    - deleted 10y ago
      [deleted]
  - cr0sh 10y ago
    No - AI Class (Norvig/Thrun) and ML Class (Ng) both ran at the same time, in the Fall of 2011. I took both courses, but only completed the ML Class (I had to drop the AI Class due to personal issues at the time). I'm not sure which MOOC company started first (in 2012), though - I do think it may have been Udacity. I know that when it did start, it wasn't able to offer the AI Class because of {reasons} (I think maybe licensing of course content or something) - and so instead it offered the CS373 course (at the time titled "How to Build Your Own Self Driving Vehicle" or something like that). By that time (Spring 2012), I had moved on past my earlier problems, and jumped at that course - I took it and completed it as well. Coursera, meanwhile, was able to offer the original ML Class as a premier course (maybe Ng had different rights to the content, or maybe there was issues on the AI Class that had to do with the dual instructor partnership of the class - I'm not sure what really happened there). After about a year (IIRC?), Udacity was able to finally offer the original AI Class as part of their courses (I think now renamed "Introduction to Artificial Intelligence"). Today, I'm taking the Udacity Nanodegree course, as I've noted before here. I think this offering from Stanford is interesting, but it doesn't seem like it is currently "available" to enroll, because the two required courses seem closed or something? Maybe they're taking enrollment for a future starting date. That said, while the tuition isn't outside of something I could do, I currently think the best use of my money and time - after I complete the Udacity thing - would be to pursue getting a BA on CompSci or something of that nature, then pursuing other paths. Should've done it a long time ago when I was younger - but I was dumb.
    - XenophileJKO 10y ago
      Let's not do anything drastic. If you've finished those courses and have decent experience a bachelor's degree will get you little to no practical value. If there are holes in your knowledge, by all means fill them, but a degree of little value is not a good investment in this line of work. You are better off filling holes in your knowledge and build something awesome. That's it. You want an interview & offer at Google, facebook, Microsoft, it's pretty easy with a solid portfolio and a few months study or refresh on algorithms.
- realitygrill 10y ago
  Actually, Thrun's AI course, Ng's ML course, and Widom's Databases course were announced and ran pretty much simultaneously. They were all successful, but only Thrun decided to split off because of it.
  - melling 10y ago
    I noticed that Andrew's course is still available. https://www.coursera.org/learn/machine-learning https://www.coursera.org/learn/machine-learning Is it still a good introduction to machine learning? It's several years old now. Are there better courses available?
    - ktta 10y ago
      That course is a very good basic machine learning course. It has many of the stepping stones to complex machine learning problems, no matter which specific field. So yes, it is a good intro to machine learning. There are new advances coming up all the time. But you will definitely need to know most of the topics in that course. That is, if you want to properly understand most of the latest techniques.
      - visarga 10y ago
        It also works great psychologically - concretely, Andrew is capable of inspiring enthusiasm and confidence.
        mwambua 10y ago
        I see what you did there. :) Someone even made a drinking game out of it: https://www.reddit.com/r/mlclass/comments/lvxuz/mlclass_drinking_game_drink_every_time_professor/ https://www.reddit.com/r/mlclass/comments/lvxuz/mlclass_drin...
    - nl 10y ago
      It's a good course. The only(?) real criticism of it is the reliance on Matlab/Octave.
nafizh 10y ago
Did that course actually. Sebastian Thrun and Peter Norvig were the instructors. Still have the certificate from the course(back then they used to provide signed certificates from the instructors for free).

Xcelerate 10y ago

If one's goal is to work at OpenAI, FAIR, or DeepMind, which would be a better use of time — obtaining this certificate or getting quality papers into NIPS / ICML?

Kephael 10y ago
Certainly the latter, getting published in top journals or conferences is several orders of magnitude more difficult.
ChuckMcM 10y ago
Wow tough call. The certificate would represent a baseline of understanding which can be then further trained, a good publication history in NIPS/ICML Etc. would represent a solid contribution to the field. I would not be surprised if those were, to a first approximation, equivalent.
- poikniok 10y ago
  This has to be sarcasm right?
  - kahnjw 10y ago
    Clearly

b1gtuna 10y ago

Would anyone recommend this over doing a masters degree in the similar area of study but at a local university (ie. not Standford)?

snowcrshd 10y ago
I'm curious about this as well. I have interest in AI, but I'm not sure how companies would see this online degree (even through it is from Stanford).
- mindcrime 10y ago
  I would think it depends on the company. Remember, the world is a LOT bigger than GoogHooBookSoftBer or whatever. Walk into Tom's Auto Salvage or City Chevrolet or Barney's Screen Doors and Small-Engine Repair and show them that you can produce value for their business, and I don't think they're going to give a hoot if your degree/certificate/whatever is from Stanford, Yale, UNC-W, ECPI, or University of Phoenix.
nkozyra 10y ago
Hard to say without having taken these classes. GT isn't Stanford but a top 10 MSCS that offers an ML specialization for ~$8k-$10k. Whether that provides more value or employment opportunity I cannot say, but it is encouraging to see more to universities offering an alternative to traditional degree programs. I think there's a path for non-MS, non-PhD backgrounds, but probably not now. Outside of the big companies, ML/AI is often a solution without a problem. So until they learn practical application I think supply will outnumber demand and most of the jobs will go to PhD AI/statistics backgrounds.
- mindcrime 10y ago
  Outside of the big companies, ML/AI is often a solution without a problem. I would say just the opposite. There isn't a business too small to benefit from ML/AI. That is, assuming you acknowledge that there's more to ML/AI than "deep learning". Not everybody needs a deep neural network. Sometimes you just need linear regression or a random forest. If you come at it from that point of view, the knowledge you gain from taking Andrew Ng's machine learning course is enough to create value for companies / organizations. A lot of the discussions on this topic here on HN seem to be based on an assumption that you have to be doing cutting edge original research to be useful. I think that's very far from the case. Now the problem is, does the mom and pop bakery on the corner know that they could benefit from ML? And perhaps the more salient question is "are they looking for somebody to do ML for them"? The answer is probably "no" in both cases, so you might have to do some work to sell to that market. But the value you can create is real. Help them optimize production so they throw away less bread on slow days, etc. and you're talking direct business impact. I suspect that there will be, for a long time, a wide continuum in terms of how ML/AI skills can help create value. Which means there will be a lot of ways to leverage this field from a career standpoint.

zxcvvcxz 10y ago

How do people in industry generally view these types of certificate programs? Is it markedly "worse" than doing e.g. a Master's on campus? Also - is this closer to a Master's level program or part of an undergraduate curriculum?

bitL 10y ago
If you look at pricing, it's below their Master level so I guess is more undergrad-style.
nkozyra 10y ago
The available classes align with graduate level one's for their MSCS. If nothing else it's markedly worse because it's 1/3 the classes :). Beyond that I'd expect rigor ... it's Stanford after all.
- jayajay 10y ago
  I am feeling that even a non-Stanford place would present more rigor than an online Coursera course. When I was in school, I benefited greatly from having 1-1 private conversation time with mathematicians, scientists, grad students, my friends, etc. With Coursera, that person is replaced by Google/Bing/Whatever. If I don't get time to talk to the scientists or grad students (at least), I don't see how Udacity/Coursera/etc. are anything more than a glorified YouTube. Maybe I am disillusioned, but the value proposition from Coursera/Udacity/etc. is looking worse and worse as I look at it more and more... hmm...
  - nkozyra 10y ago
    When you pay for Udacity/Coursera/etc you at least get human interaction with paid instructors and other students.
torinmr 10y ago
The courses are identical to the courses one would take if they were getting their Master's at Stanford - the only difference is that only four classes are required, while a Master's requires about 15. I'm enrolled in Stanford's CS Master's program right now through the Honors Cooperative Program (which lets you get a Master's online while working in industry), and I'm currently planning on doing a dual specialization in Systems and AI. For the AI specialization I've already taken CS 221 and 229, and I'll have to take three more AI classes drawn from a list pretty similar to the Elective Courses list in the OP.

sharps_xp 10y ago

Are ML/AI certificate holders competing for the same jobs as ML/AI PhD graduates? I have a list of follow up questions to this but it seems like there's a lot of hype for ML/AI/DeepLearning but no definitive way to track this new job market. These online programs, although more accessible, are doing the same thing as their physical campus counter part and not being transparent about what to expect after finishing their programs.

ganeshkrishnan 10y ago
ML/AI is very new field. I heard someone say "AI is like teenage sex. Everyone is talking about it but no one is sure how to do it" So for jobs, ML/AI is pretty much an even field unless there are niche research jobs which only requires Phd gradudates
- richard___ 10y ago
  According to another HN thread this is actually not true. Only having a certificate, without CS/AI undergrad, makes it almost impossible to get a job. You need Masters at least for most positions, some engineering positions you can get in with Undergrad in CS and taking the right AI courses.
  - jayajay 10y ago
    Do people in the tech industry find any more value in physics/math undergrads than CS? CS is not as rigorous. I always thought that physics/math undergrad + ML certificate might be just as competitive as a masters in ML coming from a non-relevant BS
    - deleted 10y ago
      [deleted]
    - aerioux 10y ago
      I'm going to have to disagree. Physics/Math is useful but your particular field/speciality in CS is relevant as well. I would bet a bit more money on a CS grad to understand convexity, comp geometry and optimization than a physics grad, and math majors don't always have the code skills to develop things for production. Point of argument here being frequently neither do CS Phds and at tech companies you pair Math/CS Phds with 'production' engineers. Also certificates aren't really rigorous necessarily and also are quite easy to one-off versus relevant programs/theses/research experience. production is an overloaded term depending where you go

bitL 10y ago

Oh well, as someone who is currently enrolled into Udacity's Self-driving car and AI nanodegrees, watching ongoing MIT's self-driving course, considering taking GATech's online M.S. degree for ML, I should probably start planning budget for this Stanford offering...

benliong78 10y ago
Wow that's a lot of learning. By MIT self driving course are you referring to http://selfdrivingcars.mit.edu/ http://selfdrivingcars.mit.edu/ ?
- bitL 10y ago
  Yes, that one. It's more difficult than Udacity's SDC but also more real-world oriented. I also have subscribed to most of the Udemy courses related to CNN/RNN/reinforcementL/ML so I have a lot of fun ahead ;-) Hope you enjoy playing with ML as well!
ConAntonakos 10y ago
Awesome! I'm also currently taking Udacity's self-driving car nanodegree, but I think I only intend on doing the first of three semesters because I want to concentrate on the fundamentals, and not necessarily self-driving cars. Do you recommend enrolling or checking out the AI nanodegree? Have you looked at the ML one?
- bitL 10y ago
  It's too early to evaluate AI nanodegree as it has just started and so far we did Sudoku solver ;-) As for ML, I have it on my mind after SDC & AI, though already took Ng's first run of ML one so I am not sure it would be that beneficial. So far SDC is the best fun I had in a while, getting a car drive all by itself on a circuit feels absolutely cool! ;-) Have fun as well, I hope they have more cool stuff prepared for us!

jtagen 10y ago

Why not take the Georgia Tech online MSCS instead? Only $7k, you get a Master's degree instead of a 'Certificate', and you have the option of covering a lot of the same material.

eranation 10y ago
Yep. And Sebastian Thrun's course (the Stanford professor, google VP, Udacity founder and google driverless car initiator) is part of that program. You can take AI for robotics for credit there :)
- XenophileJKO 10y ago
  They require a previous undergraduate degree, which is a no go for me. I'm already a high level software engineer at a top tier company. I have no desire to go back and take an undergraduate degree. But I do like collecting certificates... Currently taking Udacity's self-driving nano-degree, pretty fun for someone with no robotics background.
  - jedberg 10y ago
    How closely do they check the undergrad degree? Some second rate universities will trade you a degree for experience plus cash. Most of them are non-accredited though.
    - alnitak 10y ago
      Do you happen to know any accredited university or institution that would do that? Maybe with some examinations?
      - dsacco 10y ago
        I don't think any actual accredited university would allow you to "test out" of an entire four year degree, let alone simply buy it because you have comparable experience.

ClearAsMud 10y ago

Anyone have suggestions on alternative programs that are less expensive, online, and self-paced? 40+ IT guy trying to stay relevant.

dnkrtz 10y ago
Columbia University has an Artificial Intelligence MicroMasters on EdX, first cohort started this month. It's free, or 1200$ if you want Columbia course credit.
- leereeves 10y ago
  According to the EdX page, course credit is only available to Columbia University Master of Computer Science students. https://www.edx.org/micromasters/columbiax-artificial-intelligence https://www.edx.org/micromasters/columbiax-artificial-intell...
  - marcstreeter 10y ago
    Would you provide the actual bit you're interpreting? These are the words I see: ------------- Who is this MicroMasters Program intended for? The MicroMasters Program in Artificial Intelligence is intended for those who have a Bachelor’s degree in Computer Science or Mathematics and have a basic understanding of statistics, college level algebra, calculus and comfort with programming languages. ------------- I don't see it mentioning anything contrary to the above statement. The micro-masters wouldn't be a full fledged master's degree, but could allow admission to receive a full masters (per the below): ------------- Complete, pass and earn a Verified Certificate in all four courses to receive your MicroMasters Credential. Learners who successfully earn the MicroMasters Credential are eligible to apply to the Master of Computer Science program at Columbia University. ------------- Maybe I misunderstood you.
    - leereeves 10y ago
      Other than the tagline "A series of credit-eligible courses recognized by industry", this is the only reference I found to course credit: > Take your Credential to the Next Level > If a student applies to the Master of Computer Science program at Columbia and is accepted, the MicroMasters Credential will count toward 25% of the coursework or 7.5 of the 30 credits required for graduation from the on campus Master of Computer Science program. This part: "Learners who successfully earn the MicroMasters Credential are eligible to apply to the Master of Computer Science program at Columbia University" doesn't seem to mean anything. Isn't everyone already eligible to apply?

deepGem 10y ago

The toughest curriculum in any AI related MOOC I've seen so far. Just CS228 - Probabilistic Graphical Models is enough to bleed someone's brain. Wish Daphne Koller still taught that course.

XenophileJKO 10y ago
You are in luck. They have just re-released it on Coursera. https://www.coursera.org/specializations/probabilistic-graphical-models https://www.coursera.org/specializations/probabilistic-graph...
- deepGem 10y ago
  That's awesome! Thanks for the link
XenophileJKO 10y ago
You are in luck. They have just re-released it on Coursera. https://www.coursera.org/specializations/probabilistic-graphical-models https://www.coursera.org/specializations/probabilistic-graph...

Animats 10y ago

$20K for a few online courses? Genesereth teaching logic and automated reasoning? (I took a class from him once. Exam question: "Does a rock have intentions?")

m-photonic 10y ago
So, does it?
- trendia 10y ago
  You have to take the class to find out!
  - Bombthecat 10y ago
    You won't believe what happens next! Find out for just 20k!
    - CervezaPorFavor 10y ago
      In the end, the answer is "it depends."
  - deleted 10y ago
    [deleted]

WhitneyLand 10y ago

Stanford is just trying to cash in on people by having their cake and eating it too. They want to charge 20k, but not let anyone have a chance of further advancing to complete a real degree, no matter how excellent their performance in this program. The reason they do this is solely to protect their brand and exclusivity. They already offer online degrees but the acceptance rate is just as limited as the on campus program. Yes the learning is important, but so is the credential and a certificate doesn't even come close to a degree in the job market. Stanford should pick one: 1) Charge Stanford prices, scale up online, and let any student who can do the work pay tuition and earn a degree. 2) Charge lower prices for certificates and continue to artificially ration real degrees.

deleted 10y ago
[deleted]
adamkochanowicz 10y ago
For me it's valuable the way they've constructed it. I like the idea that I can take some night classes in addition to my full time job, and just focus on one specific area. Okay, graduate degrees fulfill that purpose too, but with life events now and over the horizon, I just don't have the bandwidth to commit to getting my Masters or a Ph.D. right now. I really have no problem with this.
- Bombthecat 10y ago
  But why pay for it than?
  - xyzzy123 10y ago
    They're betting that a certificate with "stanford" on it is better than a certificate with "udacity" or "coursera", or "I read a bunch of web pages and books", "heres my kaggle ranking" or "look at this stuff I did on github and corresponding blog posts". [naturally people breaking into the field need not pick just one]. Depending on hiring filters, that might be true. If an application ever gets to an engineer though I'd bet on the last one or two winning. I think a sensible organisation should skip the usual hiring filters in new fields, because [edit](my experience is in security) you can scoop up really good people who happen to have "unconventional" backgrounds if you have competent people evaluating them. Regular HR people tend to do a really bad job with career switchers and the self taught since they mostly work off "signalling value". But in newer or very fast moving fields, the oddballs can be majority of decent applicants. My limited experience is that very technical positions are not actually overwhelmed with applicants, and that it's not hard to evaluate if people have the right stuff because in these areas it's not difficult to devise quite objective challenges without resorting to shibboleths (guess what the interviewer is thinking or, do you come from the same technical culture as me). Arguably ML positions should be the easiest to algorithmically hire for (at least for industry, not hard core research). Just put an automated judge with a fairly low bar on a business relevant objective function between your careers and your "submit job application" page :p Personally I find this a little bit funny, because ML driven competence evaluation in "hard" (reasonably concrete objectives) fields should eventually render credentialism and signalling obsolete. But here we are, the $20k "certificate". All these things said, a structured course of study is super useful for the undisciplined (certainly including me) and dropping "new car money" on something has a way of focusing the mind :)

betadreamer 10y ago

Can you get similar knowledge through books? In general what book do you recommend? I'm specifically interested in deep learning.

kriro 10y ago
I think "Artificial Intelligence a Modern Approach" is still the best foundation book. However it certainly is not focused on deep learning. There's chapters on pretty much everything (one on reinforcement learning) but it is build around the idea of intelligent agents first and foremost. Best written CS book I own.
- sqldba 10y ago
  I'd love to read a book like that but I don't have any maths, and I presume those things are full of maths.
  - kriro 10y ago
    I think this book is actually very approachable without much of a mathematics background. It's structured so that you can usually skip the mathy parts (and there aren't many really). Time and space complexity might be a bit tough but it's not that hard to work through. I think the Bayes related math was explained well and should be approachable with next to no math knowledge. The math is mostly applied and not proofs. There's a fair amount of pseudocode and algorithms but they are explained well and I think it's not hard to follow (our students of different backgrounds usually didn't have problems). I did get a bit tired of the running example of the map of Romania (essentially used for all the search related things). The diagrams for algorithms are very helpful.

theCricketer 10y ago

This costs about $15k - $19k. With all the great lecture and homework content out on the Internet about AI, ML, deep learning, vision and natural language, I wonder if one can put together a more comprehensive and customized version of this that one can learn for free.

jbarciauskas 10y ago
EdX is strongly committed to learning being free. You can audit any of the courses in the AI MicroMasters for free. https://www.edx.org/micromasters/columbiax-artificial-intelligence https://www.edx.org/micromasters/columbiax-artificial-intell... (EdX employee)

kriro 10y ago

20k or 10k per required course (there's electives but let's assume the bare minimum) seems steep for an online certificate which seems fairly worthless from a signaling POV. I'm not sure their brand name justifies that price (not sure about the content). The competition is probably the AI nanodegree from Udacity which costs 800$/term with the chance to earn some of that back. If the employer I want the certificate for knows what online certificates are, chances are they are familiar with Udacity (possibly more so than with Stanford in that market).

amelius 10y ago

> Software engineers interested in acquiring a solid foundation in artificial intelligence. Does a "solid foundation in AI" actually exist? I'm asking because it seems that nobody really knows why many algorithms actually work, or even how they should be adjusted to cover new applications. To me it sounds more like "educated guessing".

grayshirts 10y ago
If you are talking about ML then: Bayesian stuff, Variational and MCMC, Graphical models, Deep Learning, Linear Algebra, Probability theory, Statistics, Multivariate Calculus, Optimizations - as a baseline. I think the "average" person on HN would not be interested in ML if they had to learn it rigorously. It's much easier to blackbox the entire thing and label yourself as a "ML Engineer" then learn the fundamentals listed above. Having a Stats/Applied Math background would be very helpful.

sp332 10y ago

Darn, I thought they were preparing to give degrees to AIs.

oculusthrift 10y ago

This only makes sense for people whose work will pay for them to take it.