Information Session: Artificial Intelligence Online Programs I March 2025

Key Takeaways

My name is Pax Haymire. I'm the senior director of academic programs here at the Stanford Engineering Center for Global and Online Education at Stanford online. If you've joined us before and you're from you're wondering what the Stanford Engineering Center for Global and Online Education is, uh we changed our name from SCPD or the Stanford Center for Professional Development earlier this year. We are now uh instead of SCPD, we are now Sego. So I'll be talking today a little bit about our credit bearing programs in artificial intelligence and I am also joined by my colleague Petra Perakova who will be introducing herself. So hello, welcome everybody. Um uh nice to meet you virtually. My name is Petra Parikova and I'm the senior associate director of our computer science and AI professional programs and I will be talking to you a little bit more about our professional side of the portfolio. And yeah, we have we we're super excited that you are here with us. Hopefully you will have a lot of questions and please keep them coming. We will try to answer as many as we can throughout this presentation and also kind of at the end to give you very quick overview of what we offer at um Stanford Engineering Center for Global and online education. We offer different options uh focused on AI um for technical professionals also for business professionals and also for professionals in healthcare. For the technical professionals, we actually have a very very um uh thorough portfolio that we'll tell you a little bit more about. So, Pax will be talking to you a little bit more about the AI graduate certificate and I will talk to you a little bit more about the AI professional certificate. But I did want to also make sure that you all know that um if you want to preview anything or like if you're kind of just excited to see what what we are covering in our classes, we also have a lot of content available on YouTube. So a lot of kind of the classes that are technical are also available on YouTube. So I did want to kind of give you that information right up front. If you are joining us uh from different organizations and maybe you are less interested in kind of the technical details and technical um kind of technical backgrounds in artificial intelligence. We also have some offerings that are specifically geared towards the business uh on the business side of the portfolio. the the kind of the big one uh that is uh that has been developed just recently is a generative AI program that focuses on technology, business and society. So not even just business and applications but also kind of ethical considerations that we cover in this program. Then we have mastering generative AI for product innovation. So if we have some product managers out there or like people kind of interested in kind of um developing products or like finding the right market, this might be the right course to look into. We have building an AI enabled organization. It covers a little bit more kind of about uh how to go around kind of the the recent changes that are coming up as well as the AIdriven leadership, how to be a good leader and AI UX design essentials. So this is kind of on the business side of the portfolio. We will not we will not talk much about this part. We will really focus most mostly on the technical aspects but if we do have some people who are more interested in this like please let us know if you have any questions and we will try to respond to those as much as we can. And then uh also if we have some health care professionals, people working in kind of health care, medicine, we have AI in healthcare and also applications of machine learning and medicine which is specifically kind of also geared towards you if you're uh coming from the more healthcare background. And I think with that uh let me kind of also tell you where to find out more. Um um I encourage you to go to this site if you don't want to kind of type this uh up in your browser. We also have a lot of links available on the platform. So I believe it's on your kind of top right corner you will see kind of this page with Stanford online AI courses and programs where you can explore a little bit more. A lot of the options we have here are paid but as mentioned we also try to offer a lot of webinars a lot of sessions and kind of a lot of material on YouTube if you want to take a look but yeah like um with that I will hand it hand over back to Pax who will tell you more about the graduate certificate option. Thanks, Petra. And uh thank you for already posting some questions. Again, please continue to ask them. Just to respond to one off off the bat here is we don't make the slides available, but that link that you can see in your in your interface, that will take you to a page that has all the information we're going to cover today and more too. So, you can really go in and dive into comparing these programs. So I'm going to talk a little bit about the AI graduate certificate that's available through uh Stanford online. So first to back up what is a graduate certificate? So the the certificate generally speaking is it is accredited through the same regional creditor that accredits Stanford's degrees. It consists of three of four graduate level courses and these are the actual courses that are happening on campus. You take them for credit earn a transcript. you take them as an online student at the same time as the onampus student. So that's usually between 12 and 20 units of work and you have about three years you have up to three years to complete uh to complete that certificate. So the cost is is on a per unit basis and you can see an estimate here of what the cost is with this year's um this year's tuition. Tuition does come up uh it changes every year along with does on on Stanford and that's kind of the core of the graduate certificate. So it's a credit bearing certificate made up of four credit bearing courses and you have about three years to complete it. Now just to take a look at this is a snapshot of of the courses that are currently available or part of that certificate and what you'll see is there are two there's a the there's actually one required course either machine learning which is CS229 or artificial intelligence principles and techniques which is the core introductory artificial intelligence course uh available uh at Stanford for for graduate students. In addition to that, you can complete up to three electives. Up to because you could complete both 229 and 221, both machine learning and artificial intelligent principles, artificial intelligence principles and techniques. And then two electives or you can complete either CS229 or 221 and two electives. And there are a lot of electives in there. You can look through them and we add more periodically. And we have additional courses that aren't listed there but are related to artificial intelligence. And if you take one of those courses, then you can petition the department to have it count towards the certificate as well. So those would be things like what we're offering this quarter, lang language large language or language modeling from scratch or um or or uh sometimes we have uh natural language uh I think natural I think it's natural language understanding for speech. So there are different kinds of uh courses as well that aren't listed here but that are available and you can petition to have it count. So again these are four what's required are four graduate level courses. So what does that actually mean when I say the actual course? So this what happens the way we we do it is the classes happening on campus right? So we're going to follow the academic quarter. So we spring quarter started today. Today is the first day of spring quarter. So there are hand there are courses happening on Stanford's campus. We have extended a handful of those, well actually up to 70 each quarter out to online students. You enroll as an online student. You're taking the same class. You're responsible for the same assignments. You're responsible for the same deadlines. You're doing the same work as the onampus students. And you're joining as an online student. So each of those courses are going to vary just as they did at at your university. They'll vary by the instructor. Uh even the same course which can be offered multiple times a year may vary a little bit depending on which instructor is offering it. Generally there will be a mix of written programming assignments, projects, exams, problem sets. It'll again vary from from course to course. The lectures themselves usually are not available for real-time interaction. We're recording them as they happen. You can live stream them or you can watch the recording after the the lecture completes at your convenience. Now again, just to remind you, it's the actual Stanford graduate course, so you're following the the academic calendar. So, it's not like you can wait to watch those lectures. You still need to watch them in a fairly timely way to make sure you're keeping up with the coursework and meeting all the deadlines. When you complete the course, you do earn a Stanford transcript and you can earn uh and you earn Stanford units. Now, if you were to be admitted into a master's degree here at Stanford, you could apply up to 18 of those units towards the degree if those units are relevant to the degree. So obviously if you're taking artificial intelligence courses and maybe you pursuing a masters in English may not apply. And then second of course you have to be admitted into the degree and the final approval for the uh for applying those units does does lie with the department itself. And finally as you take these courses or continue to take these courses you do need to earn a B or better. You're not admitted into Stanford. you're being approved on a course byc course basis to take these classes and you do need to earn a B or better uh to continue taking classes and to earn their certificate. So let me say a few more things about it. So who are you know maybe taking a a back taking a step back and just talking through who are some of the students who are interested in this. So it is a very flexible program. It's not as flexible as the professional program which we'll talk about but it is very flexible. Again you have to follow the academic deadlines. If we follow the academic quarters, you are following along with an academic class. And these are intense graduate level courses. Most students report spending 15 to 25 hours a week on a single course, right? They're very intense technical courses. Um they're graduate level computer science, mechanical engineering, or uh aerrow and astronautics courses. So they're they're intense courses, but you have this flexibility. You're not enrolling in a degree program. So you don't need to be continuously enrolled. So maybe you're interested in taking a course this summer. You take the course this summer. Fall h, you know, come fall quarter, you've got a big project at work. You don't need to take a course in fall quarter. You could enroll again in the following winter quarter or in spring quarter. Right? The the key thing is you just need to if you're interested in the certificate, you need to complete all that coursework by the end of three years in order for it to count towards the certificate. That said, you don't need to pursue the certificate. you can just take individual courses either within the certificate or as part of other certificates. So maybe um you're not interested in the certificate, you just want to take one or two courses and then you see another one or two courses and another certificate that you're interested in. That's fine as well. The uh the thing to note uh as I said is is you know you you have that flexibility and so what we're seeing is we generally see two types of students. There are a lot of students who who come who are maybe already have an advanced degree. Maybe you already have a PhD or masters. Maybe you already have a PhD or masters in computer science. But as new developments happen, you're interested in kind of refreshing your skills or filling a particular gap that you had um in your PhD program. Maybe you you didn't have artificial intelligence and you specialize in something else and now you see the demand and you want to come back and study it. Well, that's a perfect use case here. You come in, you take one or two courses, you fill that gap, you do some coursework, you you understand the fundamentals of of uh of the uh you you've understand the you learn to understand those fundamentals. Another example are students who are maybe earlier or um early or mid-career who are interested maybe in going back to graduate school. And so they want to see if graduate school is right for them. They want to see if Stanford's right for them. And so they'll take a handful of courses and they'll test it out. And again, these are the same courses that are happening on campus, right? So, if you're successful here, that indicates you might be successful in another grad in a graduate program here or elsewhere. Now, if you're interested in in in artificial intelligence, uh, but you're not quite ready, and let me jump, uh, I'm going to jump into the prerequisites in a in a second. We do have other programs available, including introductory programming or foundations of computer science. So these are these are similar graduate certificates that are going to give you the the foundational work in programming and some of the mathematics. We don't offer all the prerequisites through Stanford online. So you may if you don't have the background for instance in a lot of the math like calculus and uh and linear algebra. You may need to look elsewhere to build up those prerequisites to build up that knowledge. Let me pause here for a second to see um I see questions about admissions process. Let me take a look at that. Um uh so these are some great questions. So let me uh let me uh keep moving through because I'm going to talk about the admissions process very soon and uh so I'll answer that question and then I'll come back to this great question of of right now as well about about prerequisites. So in general if you're going to be successful in the uh in the graduate courses you're going to need the prerequisites. So there are some hard prerequisites that everyone needs which the first thing is you do need a conferred bachelor's degree and you generally it's it's you're going to generally need a GPA of at least 3.0 or better. Now you're approved on a course byc course basis by the home department of that course. So each department is going to set slightly different uh kind of baseline prerequisites that they need for any course that you're going to take there. So when you go to the course catalog, click on the course, you can scroll down, you should be able to see what the prerequisites are, the baseline prerequisites for that particular course are. Now, in addition to that kind of baseline, a bachelor's degree with a 3.0 or better, is that uh you also you're also going to need college calculus and linear algebra, usually multivariable calculus. You're going to need to have probability theory, and you're going to need to have a strong programming experience. That's going to be just something that that's that's kind of the baseline for taking any of these artificial intelligence courses. Other courses might have higher requirements. There might be additional math or additional specific programming requirements. Again, take a look at the individual course. You're not being admitted into a program. You're being reviewed and approved on a course by course basis. So, we leave it up to you to review, make sure you meet those prerequisites. And so, when you're submitting your application, uh, you know, and the department reviews it, they can see th those prerequisites there. Now, I see a question about it's been a long time since you've taken some of those courses. Uh they will look through your transcripts. You know, part of the application process will be submitting your your your undergraduate or graduate transcripts and they will review those and they'll see if they you meet the prerequisites for the course and the general prerequisites for the department. And if you do, you know, uh and they'll consider other things, but generally if that you do, they they'll approve you to to to take the course if there's a seat. But if you don't if you haven't taken it in 10 years, you're going to of course struggle uh to keep up with the course material. So I do recommend you know reviewing that material. I think uh we have some resources that we can uh that we link to on our site where you can u review the calculus, the linear algebra, but there you can usually use just a lot of the free resources that are available out there. Most of the courses will also have review sessions on some of the core concepts and material including linear algebra and calculus and probability theory um to get you back up to speed if you haven't taken it in a while because you generally don't need everything in linear algebra. You may only need certain portions of it. So they'll kind of highlight the key aspects of these different of these different aspects of math and and uh that you're going to need and they'll help you walk through it. But you do want to make sure you're you're up to speed on that. One other thing I'll say about this is a majority of those artificial intelligence graduate level courses do have public facing websites. You can just Google the course number Stanford and it'll pull it up and there they're going to have more detail about the prerequisites. Sometimes they'll even have some early problem sessions, excuse me, problem sets that you'll be able to look at to see how comfortable you are with the level of the material before you enroll. And finally, I'll say as Petra did is that we have a lot of the lectures as well for these courses available on our YouTube channel, Stanford online YouTube channel. So that's another good way to kind of set a baseline of how how much you need to review and what the level of these courses will be. You can go on our Stanford online YouTube channel. You can watch some of the lecture recordings from machine learning, from natural language understanding, from natural language uh uh from natural language uh processing and from what others we have deep learning. We have a lot of them up there. Reinforcement learning. So take a look at those. It'll give you a good sense of the level and the difficulty of the courses. So that's all building towards what the application is. Now again, as I said, you're not approved for the program. you're approved on a course byc course basis and you don't need to pursue the whole certificate. You can just take individual courses. You can do you do as you as you like as long as you continue to do well in the courses. So, what you'll need to do is go to our our website, Stanford online, create an account, and then you'll submit a non-deree option application. And what the core requirements there is short statement of purpose, some personal information, your professional background, and then your educational background. And that's going to involve your official university transcripts. And we want to see everything including your undergraduate, your masters, PhD if you have it. You just need, you know, the most important of course is the undergraduate because that's what that's the the baseline of what you need. Once you've submitted that application, it is not reviewed by anyone until you enroll in a course. And that's really that step three is really really important. So once you've submitted that application, you go in, you choose the course you want to enroll in and you select enroll now. your application is on file, it's submitted. The department will then will then submit that application to the department to review to see if you meet the requirements for that particular course. Now, let's say you take that course, you complete that course, you do well in that course, then you can look at the the next quarter you want to enroll in it, you select the next next class, you enroll in that class. We again send your application to the department and this time along with your Stanford transcripts. They will review all that and again they will review and either approve or reject you for that ex course. So, it really is on a course byc course basis. You're not admitted into a program. You're not admitted into Stanford. You're being approved to take uh on a one one uh you're being approved on a course by course basis. One course at a time. So, let me pause here. See if there's some other um some good questions. I see. Great. And great question about enrollment periods. So, uh, because we're on the quarter process, enrollment is not continuously open for these courses. They're usually we usually open enrollment about two months before the quarter begins. So, uh, the next enrollment period will be for summer. It opens on April 7th, which is actually next week. So, on April 7th, our enrollment will open for summer courses that are starting in June. In late July, early August is when enrollment will open for our autumn quarter courses. It's only once that enrollment opens that we really have a finalized schedule. Um, but you can go to our our our site and we're working on better ways to kind of show you what the the full year schedule is. But but generally when you come right before the beginning of the quarter, you'll be able to see uh right, excuse me, right at the beginning of our enrollment period, you'll be able to see which courses are available for enrollment that year and then you just click on enroll. So there are four enrollment periods. They start about two months before uh the quarter begins and it's during that enrollment period that you can enroll for the courses for for uh the upcoming quarter. So again for summer it opens on April 7th and those are for courses starting in mid June and for autumn quarter it will be opening late July early August for courses starting in late September. And you can go to our website and go to graduate programs and courses and you can see our full academic calendar which shows the enrollment periods uh for all the quarters uh and we will have our one for 20 for the next academic year should be up in the next uh couple weeks. Okay. In fact, a follow-up question about this was about classes being available and some folks are wondering kind of like why some of the enrollments might be closed right now. So can you tell a little bit more about kind of what to expect from the upcoming quarters and when classes open? All courses are closed for enrollment right now because the enrollment period closed. The quarter has begun. We close is a great question. So if you're metriculated students, their enrollment period goes all the way through basically the first three weeks of the course quarter because they can swap and and shop courses. The enrollment for non-deree students opens earlier but it closes about two weeks before the quarter. And the reason for that is that as I said, you're everyone is reviewed every single time they enroll in a course. So we need that time period to review all the applications to make sure all the paperwork is in place. So right now no enrollment is open. Spring quarter has already started. We're not accepting any more applications for courses. Uh that's starting the spring quarter, but next week enrollment and will open for summer quarter and you can then enroll in summer quarter courses. Yeah, that's a good question. And then there were more questions about the prayer visits and what they need to submit and if some specific kind of document uh would work if they should have like kind of great grades or if it's like sufficient just to submit a transcript and kind of learning more about a step two over here. Yeah, this is a great question. So I see so uh let me just question that just came in. The application process is going to be different depending on the program you're applying for. So the application process I just lay it out. It's for any credit bearing course that you want to take or any graduate certificate that you're pursuing. Right now, we're focusing on the AI graduate certificate, but we have 30 graduate certificates uh that you could pursue and about 200 courses a year that you could take, not just in artificial intelligence. In terms of the prerequisites, we're generally so it will depend on the specific prerequisite, but generally for a math prerequisite, the departments will want to see something on an official transcript. So something from a an accredited university here or abroad, and they're going to want to see a grade usually on that. So if you uh if you did a Corsair on linear algebra, they're probably not going to accept a Corsair on linear algebra. uh but uh but they would take you know a linear algebra class in your undergraduate transcript for programming experience. They're usually much more flexible because a lot of people develop that through their professional uh you know through their work. So if you have a strong background otherwise uh but you don't have any programming courses on your transcript but you can explain either through your work experience or through your statement of purpose how you meet those programming prerequisites. then they will often consider you for for these courses. So for instance, if you have a background in physics, but you've been working as a programmer for the past four years and you're self-trained and you know Python and C++ and etc, etc., they they'll generally consider that. But for the math courses, they're going to want to see something from on on your transcript for those particular courses. It will depend on the department, too. Some departments are very strict about that. They're going to want to see it. Um the the the requirement, interestingly, that most students get get caught up on is multivariable calculus. They're they're going to want to see over a year of college level calculus on your uh on your certificate, but again, excuse me, on your transcripts, but it's going to depend on the department. Uh some departments will be a little bit more flexible on that. So, yeah. And then I I I saw a couple more questions maybe about a graduate program. One of them um packs is about kind of being um abroad and being able first to kind of apply and second kind of being able to follow. So maybe we have people in Europe or Asia and they are not sure if they will be able to participate and yeah if they will have some classmates maybe even from like other countries than the US. Yeah, great question. So this is a g global program. So we do have students from all over the world. Now the majority of our students are located in the US but we do have students from all over the world. Um, and you can apply from from pretty much anywhere. Um, uh, and so yes, it you you can do it if you're in Europe, you can do it if you're in Canada. I I think the the um the caveat here is that obviously there can be challenges. You know, the ability to take an actual class that's happening on campus is both an opportunity and a challenge. It's an opportunity because you are literally taking the same class as the on-ampus students are. You're following along with the same material. you're, you know, attending office hours usually on Zoom to to talk to TAs to get answers. You're you're you're posting on the same forums that where they're posting questions for the teaching team. The challenge, of course, is that you might be in a different timeline uh timeline time zone. Uh and so it can be a challenge to to join those Zoom sessions, etc. Usually, the teaching teams do the best they can to accommodate different time zones and work schedules because most people are actually uh also working full-time. So even if you're local and you're and you may not be able to attend anything between 9 9:00 am and 5:00 pm. So there can be challenges around that. The teaching teams do their best. We do have a pretty generous drop policy which is you can drop up to the third week of the course for a full tuition refund minus a uh right now a $100 processing fee. A drop processing fee. So what would happen is we would encourage you to join and that say you're going to take a course this summer. you know join that first week and and in summer it's the end of the second week because summer is a shorter quarter but you take join that first week you take a look at the syllabus you take a look at the available office hours maybe you ask some questions from the teach from the teaching team about availability of things and and how it might work for you as a a student in say Germany or in Japan and then if you can't do it then you just you drop the course um but generally they they'll make accommodations and they'll they'll work it out for for students uh even overseas So, it is possible overseas. We have plenty of students who do it. Um, but again, as as would be expected, there can be challenges at doing it from a different time zone or while you're working full-time. Um, and so, yes, sir. And there's not necessarily a recency requirement, right? They're going to look at I see these questions about how recently you took the prerequisite. Generally, they're not going to look at how recently you took the prerequisite. Um there there could be exceptions to that, but I would say as a general rule, they're not going to look at, okay, you know, you only did it, you know, you did it 10 years ago, it's not acceptable, but they will expect that if you've done it 10 years ago, that you are going to review it and be up to speed when you when you join the course uh in in the uh when you join the course. So the the the burden will fall more on you to make sure that you're up to speed and you review that that crucial course material. Again, a really valuable resource, especially for a lot of these artificial intelligence graduate courses, is to go and review the public facing website if it's available. Um, and you can get a sense of what the problem sets are. They'll often have review material or highlight what part of a particular math is really important for the course. And that's something you can start doing, you know, even before you you you know, as soon as you submit that application and request to enroll in the course, you can go in and start reviewing just to get a sense of what's going to be involved. course deadlines are going to be in the Pacific time zone, right there. It it follows Stanford's uh Stanford's uh Stanford's deadlines and we're in a Pac we're in California. And Pax, maybe one last question. We I did see a few people interested in a master's degree or kind of following up and kind of learning more or maybe kind of getting admitted to Stanford uh as a graduate student at some point. Like does this help or like how would how would you think about the differences? Yeah. So, a couple things to note. As I said earlier, if you take courses as a non-deree student, you can apply up to 18 of those units towards a relevant master's degree if you're admitted into the degree pending final department approval. Again, those have to be relevant units. Um, a fair number of students do do that. Is being a non-deree student a benefit? It's it's, you know, it doesn't hurt, but it's not it's not like a fast track into the master's degree. The the master's degrees at Stanford are incredibly competitive. they obviously have a lot of students who are coming directly from Stanford applying to those degrees or who have backgrounds at Stanford. So the non-deree uh you know the non your the non-deree courses again you can submit that transcript your Stanford transcript along with your other transcripts as part of your master's degree application but does it it's not a special gateway or backdoor into the master's program you'd be considered along with all the other uh applicants and they would consider your they would absolutely I think take a look at your Stanford transcript as part of that but it's not a um it's not a a a back door. Let me add one more thing to that which is that many of these master's degrees in the school of engineering are also available uh as on a part-time andor online basis. In most cases, what that means is you apply and you're admitted into the master's degree. It's the same master's degree. You apply and you're admitted into the same master's degree and then you can select to pursue it as a what we call an honors cooperative student on a part-time basis with the option to do course work online. Now, some of the degrees like computer science can be completed fully online, but not every course is available online. Not every course in every depth area is available online. So, if you were interested in that and let's say you're in New York and you're interested in pursuing the degree and you were admitted in the master's program, you could go ahead and pursue it. You could probably complete the whole degree online, but you're going to have a limited selection of courses that you can do fully online. And that's something that you also uh depend on final department approval, right? So, you were to be admitted in the degree and then you would make a request to pursue it on a part-time or online basis. And different departments are going to have different rules around that. Uh they'll have different guidelines about who can be a part-time student and they have different guidelines about transferring from part-time to uh to full-time status. Other questions? Um, I think that covered at least most of them from what I seen, but let us know if you have any other ones or if we missed anything, let us know and we can follow up also at the end um of the session. Okay, great. So, I can um now tell you a little bit more about the professional program portfolio or kind of the professional program in AI we have. So, Pax was talking about the graduate version. And now I will be talking about a professional version which is based on kind of the graduate version equivalent. So I will be talking to you about some of the classes we have available. But just to kind of note right up front, the classes are still very challenging and they cover the same depth and breadth of the subject as the graduate program. We just offer some additional flexibility that I will show you. uh maybe for those who might not necessarily need the credit or kind of they might be kind of like tied with their employer to like take some specific um specific programs or courses or something like that. So I will tell you a little bit more about that. I also did see that some people are interested maybe in some other offerings we have. Um I think hopefully you got kind of an email address included with the invitation to this webinar which I think is like uh we we just recently changed it so unfortunately don't remember it by heart but please let us know if you have any questions about those sessions or if you have some questions about that now and we will try to get to that at the end but as noted in the beginning we will try to cover kind of mainly the graduate and the professional program in this specific session. So uh that's kind of a long introduction. So talking more about the AI professional program, we currently have eight classes um available um you will see kind of if you look into the detail that they are actually kind of graduate course equivalent. So when Pax was talking about CS229 machine learning, we are talking about XCS229 machine learning. When Pax was talking about CS224 and natural language processing with deep learning, we have XCS224 and natural language processing with deep learning. uh we run these classes kind of off academic schedule um with some other kind of modifications we made. So the upcoming classes as they are coming the next one is machine learning with graphs which is starting next Monday. Then we have machine learning starting on May 5th and then the next class is May 19 deep generative model. So you see they kind of run off cycle a little bit and most of the enrollments are currently open uh with the exception of maybe two classes that are currently paused. So like if you see these two classes, they're currently in pause. We are not sure if you will run them again, but we are kind of trying to gather interest and talk to faculty about next steps. If uh you are kind of wondering right up front about like which class is good to take first um and you are not really sure, I will probably point you to artificial intelligence principles and techniques which is a little bit kind of um class that is covering a lot of the concepts in artificial intelligence. So it can give you really good overview wide overview of different aspects and then you can kind of get a little bit more familiar with like different um aspects of AI and dive a little bit deeper. Uh if you already have some background in AI though we have I just recently kind of recording a recorded a short video kind of telling you a little bit about different paths or like which courses to take based on your prior knowledge and experience and we link that resource in the additional resources on the platform. So hopefully you see it. I I think it's like one of the last links. So that's a question that always comes up and I did want to note it down in the beginning. But to tell you a little bit more about how we run that and what kind of additional flexibility means in this case, it means that we use the recorded lectures with Stanford faculty that were run as part of the graduate offering and then we kind of segment them by topic and kind of remove some additional kind of maybe optional content to focus on the core aspects with the goal of not making it simpler but maybe making it a little bit more focused. But what it means also usually is that we don't have any kind of final exams. We usually don't have any project work as part of the courses and we usually try to kind of focus on the core assignments. So maybe in the graduate class you will have final exam project and six assignments. We will kind of scale it down together with faculty and maybe focus on just five core assignments instead of like the full set of um like the kind of the criteria for the graduate class. We run these sessions kind of throughout the year, usually twice or three times a year depending on the cohort. Some of the classes run only once and we run them in 10 week uh sprints or cohorts with approximately 160 learners in each cohort. Um we still kind of use the same set of written and programming assignments. We try to sometimes add additional links, but I would say it doesn't always happen. But what where we spend a lot of time on are autograders to try to kind of help you debug a little bit more and kind of get a little bit more feedback as you are working towards the assignments maybe. Uh there were some questions in the kind of chat or like at the inbox about support. Um so Pax was describing to you that like they're usually teaching assistants as part of the graduate versions. We have uh course facilitators who took the graduate class and who are supporting our cohorts with content related questions. So if people have questions about kind of the assignments, lectures like something going on uh they have a chance to connect with their course facilitator and kind of individual calls or like ask in a Slack community or ask questions. So um I think some people were wondering is it just email or like you know like how does it work like we definitely offer uh a lot of support in both the graduate and the professional program uh to try to help you through that and I already mentioned a slack community which is pretty vibrant um you can always take classes kind of one by one and decide that maybe that's it this is like a specific class I want to take for some spec specific reason uh with my employer or you can take three classes and then you would be getting AI professional certificate. So again like if you take one class you will still be getting a certificate if you take three classes you will be getting the AI professional certificate kind of in addition to the course certificates. Um there is a question kind of about the final exam right now we don't have any final exam as any uh with as part of any of the AI professional courses. This is just an example of a schedule. Um we kind of give you all the materials right from the beginning. So you have access to all the content all the assignments from day one and then we have kind of a structure of assignment deadlines that are staggered towards uh throughout the 10 weeks. So you always have kind of some time to complete the assignments. Um I talked to you a little bit more about kind of the written assignments or what to expect. Like here is a screenshot which might be a little bit hard to read probably but uh if you are able to read it it's basically uh kind of very similar to the graduate version right like we really ask a lot about like there might be some math like it's it's not necessarily easy um uh to complete that um we also have like a lot of proofs and things like that especially I would say machine learning classes coming up soon and I know a lot of people are thinking about that as a good starting point. I definitely agree, but I would still encourage you to sign up if you do have kind of a solid background in kind of math, um, college math and linear algebra. Uh, programming assignments. Um, we develop kind of robust autograders to like help you work through that. And they're all written in pure Python. We often don't even allow kind of common packages because the idea is to really try to like get you learn things from scratch. But it depends a little bit on the class. I don't want to like suggest that they are not practical or applicable, they are definitely very helpful. Um, if you really want to get a solid background in the field uh to be able to approach very difficult programs problems, but I did want to also tell you that like you should still expect them to be pretty hard um uh for completing um support and community. This this is what we value a lot. So we kind of connect you with a course facilitator who will be a available via zoom calls, emails and slacks to um respond to your content related questions. And there's a lot of kind of people already as part of Slack. So it's a good chance also to meet other kind of fellow um learners from all around the globe and like having a chance to talk to them uh connect with them and kind of maybe like uh create some um group teams to work on the assignments. uh prerequisites. I will not talk about this in too much detail because it's very similar to the graduate program and to the things that Pat was describing. We do not require such a kind of uh long application or you uploading the transcripts. Basically, we ask you few questions where we try to kind of get a more understanding of like what your background is and if you're able to kind of uh follow the assignments, which means that you should be able to explain like how proficient you are in Python. You should be able to explain kind of like your level of college calculus, linear algebra and probability. Maybe you like took some engineering degree or like maybe you were taking some classes in the past that cover this. So, this is what we are looking for in the application. And we also ask a little bit more about your background. So we just kind of know. But the application I would say is fairly short. Usually people complete it in like 10 to 20 minutes uh maximum. But we ask you to kind of present enough details. The resource I pointed out before kind of the video with um good classes to take or like good sequence or kind of like a good path to take also includes a little bit more information about each particular class and kind of like what specific prerequisites might be helpful. Uh I gave you an example of like XCS229 machine learning. we still require the same prerequisites but that specific class is very heavy on kind of math and like logical proofs um and kind of like uh it does include a lot of written assignments. So like maybe the prerequisites even though they are the same depending on your prior knowledge and experience you might need to catch up a little bit more than for other classes like XCS221 artificial intelligence and techniques. And I think with that I will probably wrap this up but let me take a look at the Q&A box or ask PAX if we have seen anything that we should bring up. I think there are a couple that just go into the relationship between the two programs and why you might pursue one over the other. Um and so again these are the two course the two certificate programs side by side. And again you don't have to pursue the certificate in either you can take individual courses in either one. And the key differences are are laid out here. So again, for the graduate certificate, you're taking the actual Stanford graduate course. Um the time commitment is going to be a little bit more than with the professional certificate, sometimes a lot more. Uh you do earn credit and the price is on a per tuition and will usually be uh substantially more expensive. So usually between four and $6,000 for a course versus around $2,000 for a professional course. The content though is very similar in terms of the support in the graduate certificate. You're going to have access to the the forums where people post qu all students post questions, some office hours. You may have access to office hours with the instructors, but it's also possible those those office hours fill up very fast. These are very large classes, not just for the online students, but the on-ampus students. So there may be two instructors, 30 TAs, and you know 600 students. So you it doesn't necessarily mean that you're going to have a lot of or any one-on-one time with the instructor on the professional certificate side. Right? Again, slightly lower time commitment, but still covering the same material. Right? We they've we've, as Petra explained, we've adjusted it in order to make it a little bit more flexible and geared towards a a professional learner who doesn't have the time to go into as great depth as you would on the graduate course. You don't earn graduate credit. you do get a professional certificate and continuing educ and and you're eligible for continuing education units. And then in terms of the support, we do have industry experienced facilitators who have taken the material uh the course the graduate course and are familiar with the material and they would be following along helping you answering questions on Slack. So there there are similar experiences there similar c material slightly different experiences and what you want to think about is what's most important to you. Is it that flexibility? uh you know, you're less interested in the projects and you're just interested in mastering the material and you're a little bit more sensitive to the price, then maybe the professional certificate is right for you. If you really want that graduate credit, you want to do the full go as deep as you can, uh then the acade certificate is going to be uh right for you. Uh Petra, would you add anything else there? Um and I would also say say and somebody asked about kind of the minimum credit for the professional program or anything like that. So our professional program is pass fail. So we provide you with a certificate if you're able to pass the class and passing rate is 70%. So like if you achieve 70% kind of throughout the class uh you will be getting the certificate in the graduate program you will be getting kind of uh credit so you will be getting the certificate and you will be getting uh so it also depends a little bit on kind of what you need uh what you're looking for and I would definitely say there are some questions kind of why would you choose one over the other ones I think ps described it very well um we see some people really want to go in that breath like do take the they want to take the exam, they do want to do the project, they do want to kind of follow alongside the graduate version, right? So like kind of teach alongside of the Stanford graduate student. So it's definitely a great option for them to enroll in the graduate certificate. If you're kind of less um less focused on that and you maybe have a little bit less time available, you will get everything kind of from day one in the AI professional program and then you can kind of like keep working almost on your own pace, right? like we have some assignment deadlines but like you can work on it a little bit more flexibly. Uh and at the end like you if you succeed you will be getting the certificate but there is no kind of graduate credit or anything like that. Um so that's what I would say. We also sometimes get questions like why would you kind of decide to take any of these if materials are available kind of online. It's definitely also a great question. So we definitely offer a lot of support, definitely a lot of accountability, right? Like for any of these options like I know myself like if I try to learn something kind of on my own like without having some sort of a deadline structure or anything like that might be hard and also without being able to ask questions and follow up. This content is very hard as both Pax and myself kind of described to you. So it's it's pretty challenging and also like how exciting it is to like take classes along with the Stanford students or like take the Stanford content kind of directly from us is definitely a big value. I don't know PAX if you would anything else to that but those are the main reasons I usually tell people. Obviously there are many more with the community kind of and all of that but uh yeah go ahead. Yeah I mean you know we're we're part of Stanford. I mean one of the goals here is just to make this material more broadly available and so we have it available kind of all through through freely we have material available on YouTube that you can watch it for those of you who are motivated or don't need to go in depth or just want to kind of watch the lectures that's available not for all the courses to be clear just some some of the courses both only some of the courses both in the professional and in the graduate and of course you know the lectures in the graduate are redone every year we're recording them live in the classroom and then for you know for YouTube we we maybe have ones from three or four years ago. So, there's there's that as well. But then the professional certificate, as Petra said, it's really it's just going to depend on what your level of commitment is, how deep you want to go into this material. Um, you know, they're both about 10 weeks long, but the professional certificate doesn't necessarily follow the quarter system, right? So, they're they they're going to be launching courses maybe multiple times a year, whereas with the graduate course may only be offered once a year. So, there may be more opportunities to take some of the courses through the professional certificate. The other thing to notice some people asked about can you do both at the same time. Absolutely. And that's another really nice feature here. There there are quite a few of our our students and learners who do look at these as complimentary um as complimentary or even having a synergy between them. And one aspect of that is for the professional certificate uh you need to take three courses but you can take one graduate course and have it count towards the professional certificate. So some students will take two core courses through the professional certificate then take essentially an elective that's not available in the professional certificate as a graduate course and then they'll count that towards the professional certificate. On the flip side is that and the other piece where that's that's can be very valuable. Someone asked about how hard are these graduate classes. They can be quite hard. So sometimes a student won't do well won't get a B in the graduate course but they can still count it towards the professional certificate. I think if they get a C minus or better, you can still count it towards the professional certificate. So, it allows you I didn't do as well as I had hoped in that graduate course, but I can still, you know, take two more professional classes and earn that professional certificate as well. The other thing to note is that in terms of prerequisites, the professional courses are very similar uh to the graduate courses. So if you take X XCS229 which is the professional machine learning class that can count towards uh satisfying the prerequisite for a graduate course that requires that um if you take 22x if you take those courses as well in the professional course you can um essentially place out of them for the graduate certificate instead of taking a core course and three electives you could just take four electives. So there's a nice synergy between the the the two programs. You always need to take four courses for the graduate four credit bearing courses for the graduate certificate. You always need to take three courses for the professional certificate, but there's there's a a synergy between the two of them that a lot of uh learners take advantage of. And so some people, especially because the price difference can be substantial, they'll take a couple courses in the professional and take others that aren't available in the professional through the graduate certificate. Um Sierra for the professional program. I also saw some questions about um kind of the maximum number of enrollments or when the applications close or anything something like that. So um if you go to kind of the AI professional program website you will see the cohort dates. This is when the classes are actually running. The enrollments close on the day when the class is starting. though I would always encourage you to kind of enroll a little bit earlier to be able to join our orientation session and kind of being able to join and kind of maybe ask questions in the beginning um before the class even starts and we don't have kind of the maximum number of enrollments. Sometimes it happens that a lot of people enroll very last minute and maybe we were not like 100% ready or there are some other reasons kind of related to something else kind of organization wise that kind of require us to put a kind of like a weight list on but it I would say standardly doesn't happen. I think the last time this happened was for the generative models which like so many people enrolled that we were kind of like able to get as many course facilitators as we could but at some point we basically had to like put a weight list on but this happened kind of maybe a day before the class actually started. So I definitely encourage you to still like apply and try to enroll early. the applications are reviewed on an ongoing basis but like we ask you to give us few days to kind of review because we still review those manually. Um but yeah like I would say like no specific kind of limit or anything to be aware of that there is like you need to apply I don't know a week before or something like that. I just still encourage you to do it as early as possible. On the credit bearing side the courses can fill up uh and some of them have a pretty limited uh enrollment for non-deree students or for any students for that matter. Uh so usually the enrollment period is about six weeks long and we do encourage you especially for some of the bigger classes and those would be things like machine learning, artificial intelligence, principles and technique um natural language processing to enroll in those um you know in the beginning of that enrollment period. They're not going to fill up on the first day, but they might fill up by week three or week four. Uh so if you wait till the end of the enrollment period, then you may find that you're you're on a wait list. So those can fill up. Um and again the the the caps on those courses can vary a lot. It's going to be a conversation usually with the department and the faculty member and us. Most of them don't have you know we'll take we could take a lot of students and they never they never hit their cap but for some of them they'll have you know very limited enrollment. Uh and we we usually will say that if it's a limited enrollment class on the uh on the uh on the course website. We had a question that I wanted to address about the credit bearing program. So, if you take a credit bearing course as a non-deree student, uh you you uh there's a question about access to campus. You're you're expected to be an online student. You do get a Stanford email and Stanford login credentials for the period of time when you're actively enrolled in the course. You get access to the stanford's libraries online materials, but you don't get access to the the actual physical library. That said, anybody in the community can go in and buy a library card at the at the Stanford library. So, if that's important and that's something you can do without even uh you know enrolling through us, I think you can go to the library and ask about library cards. There's information on their on their website as well. Uh we're nearing the end of the time, but you see some other questions. Uh good answer, I guess, about the differences between the professional courses and and edex and Corsera. Again, a major difference is is the two major differences, of course, the level of the material. These are graduate level, you know, these are based on the graduate courses at Stanford. Um they're they're graduate level material. They're going to be very foundational. They're going to be very technical. Um, you know, a lot of lot of math and programming. And then two, of course, is that there are, you know, we run these with facilitators, right? So, you're not just on your own. You're working with a cohort of other students and you're being supported by by facilitators. Um, see, other questions, Petra, that we missed. Um, I see a question kind of about the other side of the portfolio, maybe the business side or the health care side and kind of being able then to kind of apply it and maybe develop your own LLM or something like that. So I would say that part of the portfolio is more specifically geared towards business professionals or the healthcare professionals that might have less prerequisites meaning that um you know you you don't have uh the level of college math or like maybe you're not interested in this depth and bread of the subject but it's also what then you can expect a little bit from the content right like we will start more from more from basics and kind of like cover um the basics with you. So in terms of kind of going and applying it and developing your own code uh and being able to develop your LLM that might be harder. So I think this is what we are talking about with PAX in the graduate and professional certificate which then gets a little bit easier. We can't really promise you will be able to do that. I think specifically we had a class just recently that is just opened up now CS336 which is like building LLM from scratch but had very very hard also prerequisites. So it's definitely a kind of hard thing to do, right? So we will try to teach you a lot of the kind of the background concepts that go into that. But I think in terms of application, I would always encourage you to kind of take a look at the page like trying to get familiar with the syllabus and kind of the learning objectives. And if you have any follow-up questions, you can let us know. Um if you are interested in more kind of the business or the healthcare side of the portfolio, we definitely have some applicable content depending on what you are focused on. So maybe if we do have the product managers, the class kind of focus on um uh kind of like using AI in uh developing and like product innovations. Uh that will definitely teach you kind of like how to understand the market and kind of apply it in your product management job. But like here in the graduate and professional program, we are talking more about the technical concepts of the coding, right? And kind of like the the uh the technical aspects of AI. So hopefully that answered some of those questions about um kind of the objectives or like kind of what you are able to do uh with each of these and just in terms of the length and again the yeah as Petra said these the programs we're talking about now are very technical um they are very time inensive. So for the graduate certificate you have up to three years to complete the coursework. Each course is going to be roughly 10 you know will be 10 weeks long and you know you should expect to spend probably between you know 150 to 200 hours to maybe 250 hours working on that course. So you can think of it as a as a somewhere around a thousand hours that's a very rough estimate um but of work right and across maybe three years and the professional certificate again looking at those it's going to be three courses between 100 150 hours per course. So you're looking at 300 to 500 hours uh of course work for those three courses. So they're they're both very there's a lot of time commitment that's involved in them. There's some flexibility about the cadence or the kind of speed at which you you you fulfill that time commitment, but they're they're hard programs and once you're enrolled in one of the classes, it is a lot of that time commitment is, you know, some of that time commitment is concentrated in those 10 weeks that you're pursuing the course. So yeah, I think that's it, Pax. I don't see anything else. If any of you have any other questions or if we missed something, hopefully you did find that email as part of the invitation to this session. Um, and let us know if you have any follow-up so we have a team that can kind of get back to you. Uh, but we hope we covered at least kind of the major uh questions uh that you were curious about. Um, maybe I will summarize for the professional program. If you are interested in taking the class, we are kind of having classes on an ongoing basis. And the next one coming up would be machine learning with graphs on April 7th. And again, if you are a little bit more new to the subject, I would probably kind of direct you to the August 4th and artificial intelligence principles and techniques depending again like on your background, experience and interest. And maybe Pax, if you can tell them uh next steps or if they're interested in kind of knowing more or enrolling in the graduate program, what should they do? That might help. Yeah. So again, our enrollment for the graduate programs will open April 7th. I encourage you, we just did aformational session that went over the the whole uh graduate portfolio. You should be able to find that on Stanford online the YouTube channel to be able to watch some of those uh sessions as well. In general, again, encourage you to go uh take a look at our at at um you know, at the YouTube channel as well as this Stanford online. And once enrollment opens on April 7th, you'll be able to go into our catalog and just look at the courses that are available for enrollment. Now you can select credit bearing or academic credit Stanford I think it's actually Stanford transcript is the filter and that'll pull up all the courses that are available for enrollment through the uh graduate program and again uh a lot of those are for the AI graduate certificate I think this summer only machine learning is available we have smaller course offering in the summer uh but there are a lot of computer science courses that are available especially if you're someone who's maybe looking to brush up or to build up that programming background and with that thank you so much. Have a nice morning, afternoon, evening, day uh wherever you are joining us from and hope to hear from you and see you in our classes.