Stanford Webinar - Artificial Intelligence Programs Informational Session

Stanford Webinar - Artificial Intelligence Programs Informational Session

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my name is ax haymeyer I am the director of academic programs here at the Stanford center for professional development so I oversee our credit bearing portfolio I also work with Petra my colleague who I'll introduce herself in a second with the AI and computer science programs so that Petra you want to introduce yourself yes great thank you so much Pax and also big welcome from me uh my name is Petra parikova I'm I'm the associate director for our computer science and artificial intelligence programs and courses at scpd and I see a bunch of questions are coming in please keep it coming we will try to get to as many as we can and as Pax mentioned we will be talking to you more closely today about kind of our artificial intelligence portfolio uh at Stanford center for professional development we will be focusing on two main programs tax will be covering a little bit more about the AI graduate program at scpd and I will be talking a little bit more about the AI professional program so we will cover more details how they work um differences all these kind of things but just for your information just for you to know those are not the only things we have within our portfolio on the subject of AI we have some other courses also on building an AI enabled organization and things like that um or Coursera machine learning specialization or if this is something like AI machine learning if it's subject that you are just starting with we also have a lot of free content available on YouTube and we also run um webinars quite frequently that we also try to post on YouTube so uh we will be talking mainly about the AI graduate program and professional program but just for you to know there are also some other things you could consider you can always find more information at Stanford online website site thanks Petra and we briefly wanted to mention a new course that we are offering it is really does not fit into either the professional graduate program it's a bit of an experiment for us it's on designing robust and reliable AI systems you should see a link in your resources it's the third one down it says new course just click on that if you want more information this program is being run by the executive director of the Stanford center for AI safety Anthony Corso he'll be going over these five topics around designing robust and reliable AI systems it's a one-week program and there will be assignments that go along with it but it'll basically be a a live lecture where you can watch a recording of the lecture in the morning it's completely online there'll be an opportunity to work on the assignments with the facilitator and then Anthony will be providing office hours later in the day so that's the current plan it's it's kind of a new model for us we're really excited about it it's obviously a very important um and although it's a concern that's been around for a long time it's very Timely right now this seems to be in the news a lot so we're excited to offer it we'd love to see you there we encourage you to click on that that link to find out more about it all right with that though I want to dive into more uh into more detail with with the uh the AI graduate program so this is one of the core parts of our portfolio so basically what the graduate program is is we offer credit bearing courses the same courses that are happening on campus we also offer to online students who do not need to be matriculated Stanford students in order to take the class this the certificate so the courses are the same course you're doing the same work you're in the course alongside the students uh the certificate itself that you would earn and I'll go into a little bit more detail about what it takes to earn that uh is uh is accredited by wasp so it is an accredited certificate program and the last thing I'll mention is just in terms of the cost of this program it's it's a less than say for instance pursuing a master's degree it still is an expensive program it is full tuition you're paying full tuition at Stanford this last year Academic Year 2223 the cost of the full program was between 18 000 and 22 000 in US Dollars it'll probably be a little bit more expensive this coming year as tuition Stanford raises his tuition uh so it is it is an intensive uh program it's it's four courses graduate level courses so let me give you a little bit more detail on what those courses are so what you're seeing now is kind of a list of the full courses that are part of that AI graduate certificate and you'll see that in order to earn the certificate you have to take at least one of the required core courses and at least three uh two to three of the electives if you did both the required courses you only need to do two electives so it's four courses in total outside of the core course you have a lot of freedom to choose what you want to take in order to earn that certificate I want to also emphasize that when we talk about the AI graduate program you do not need to pursue the certificate you can also take a single course or just two courses if you're interested and while what I have here are all the courses that are part of the AI certificate program there are a lot of other courses that are on topics related to or even about AI that are not part of that certificate program you do not need to restrict yourself to these programs you really can take any of those courses that you're qualified for and that you're admitted into um and through Stanford online so uh some of the courses for instance that are not listed here there are a few around robotics that that we also offer that are not listed here that might be of interest there's some statistics courses uh like statistical learning which is one of the you know foundational uh foundational ideas of of machine learning there's some prerequisite type courses that you could also take so you don't need to restrict yourself into it uh into this the course is in the certificate program and I'll go into this a little bit more detail in a second but I also want to emphasize that this is unlike say a master's degree or a bachelor's degree you don't it doesn't start in Fall quarter and follow you know a clear path you can start any quarter where a course you want to take is offered and assuming you're you're admitted into that course and you do not need to be continuously enrolled so for instance if you want to do this summer right now what's open for enrollment some of course on machine learning in the course on artificial intelligence principles and techniques you could apply if you got in you could take one of those courses this summer you could then take fall quarter and winter quarter off and take a quarter in the next spring all that's required is that you finish if you're if you're pursuing the certificate all that's required is that you take all four courses within three years so uh it's really a unique program I wanted to emphasize those things because it it really is designed for working professionals I mean the individual courses are are very intense and I'll go over that in a second uh in terms of the the work requirement I mean they're somewhere between 15 to 30 hours a week of work um but in terms of when you start and how you pursue it there's a lot of flexibility there so if you're working you know most of our students are working full-time so maybe your summers are lighter you take a course in the summer but fall is going to just be too busy so you don't have to take a course in the fall but maybe then in winter quarter you know things lighten up and you can take another course so there's a lot of flexibility about how you pursue that that the certificate and again I want to emphasize you don't need to pursue the certificate you can just take individual courses um all right uh so let me go in a little bit more detail about what these courses actually uh look like and how we do it so again these are the actual classes that are happening on Stanford's class campus what we do is we control a couple rooms on campus with camera systems and you know microphone systems built in we staff those lecture classes we record the lectures WE Post those lectures uh online and in the uh and and allow you to then watch the lectures at your convenience you can also live stream the lectures some of the lectures will have two-way communication most don't so you're really just watching the lecture and then most of the other things that are typical and of course are already being handled online so there will be you know a discussion board for instance the uh some of the office hours will be held online likely over something like zoom and so you'll be able to then submit your assignments online exams are a little bit different you'll still have to take exams in person but we have a monitor process that's set up to help you do that you'd work with either someone at your work to deliver that exam and person or you would go to a testing center in order to take the exams if there are exams so it's really it is the same course you're taking it alongside Stanford students in some of the project-based courses students pursue the projects uh with uh you know on campus students so it's it's a you know again it's there's nothing separate it's the same course as the appeal of it to a lot of of uh a lot of our students um you do need so again you're not admitted into the certificate program when you apply and I'll go over what's involved in that application towards the end of this when you apply you're admitted on a course by course basis so it's not like you're admitted into the program and then you you you know you have however long to finish it you are admitted on a course by course basis and so in order to keep taking classes you need to earn at least a b or better to keep taking those classes if they're computer science classes there can be slightly different requirements for different departments but if you're taking AI classes the majority are on the computer science department you are again earning a Stanford transcript so it is you you it's Stanford transcript with Stanford credits and if you were to be admitted into a master's program at Stanford you could transfer up to 18 of those units towards the master's degree so it is again you're earning Stanford Credit you're earning a Stanford transcript you know the key Point here is they are the same courses uh that you that the on-campus students are taking it's the same course you're alongside it I'm going to pause here to see if there are some questions uh I see there's some about the prerequisites so I'll get into those um and then I I see there are some questions about coming on campus so strictly speaking these are online only uh programs there can be opportunities to come onto campus if you're local these will require instructor permission they would sometimes require our permission as well uh a typical example would be something like um if you want to take the exam in person or if you want to come to the office hours in person usually you can't come to the lectures in person um and you should be expect to be able to take these programs fully online and I just say that because we just came off a year where campus was completely locked down due to covet and so no one who was taking these programs could come on campus but typical in a typical year when there isn't a global pandemic there is some opportunity for you to to come on campus for some parts of the program but the expectation should still be that you're completing the majority of it or all of it online um so you know you're not you can't take a seat of a you know an on-campus student from from the lecture hall basically that's a great question uh so I saw that there are some questions about you know what you know who who who uh who is this for so these are really these are all graduate level computer science classes for the most part some of them might be in other departments but they're graduate level engineering class uh class classes so they the expectation is that you are a student with a strong stem background uh and I'll go into prerequisite in a second but you do need at least a bachelor's degree and you need in order to get into the Cs classes you need a minimum of a 3.0 GPA um as an on your undergraduate degree uh and you know again these are a lot of these are very foundational classes so something like machine learning there's a lot of proof you know writing proofs mathematical proof so there is an expectation of mathematical maturity um and as I said these are classes that take 15 and they can take anywhere I think on average students report spending 15 to 20 hours a week on them so they are like part-time jobs they're intense classes is and some students spend a lot more time especially if it's a course where for instance you know linear algebra is I'll just jump ahead to the next slide where we talk a little bit more about the specific prerequisites but you know linear algebra is a very obviously very common uh prerequisite for almost all of these uh all of these AI classes if you haven't taken linear algebra in three or four or five years you might find that you have to do a lot of catch up while you're taking while you're taking the class so that can add some time to it they're they're intensive classes they're again the same classes that graduate students at Stanford are taking let me pause here and just take a look again at the some of the questions um uh and what's I see some good questions um so I will say that uh you know these are some really great questions about what you know what the the the the the topics of some of these courses are um what I will say is just uh and I see some good questions so let me just address a couple of these I see a good question about can we take the courses out of turn yeah uh yes and no so yes you can take the courses in any order that you would like except that some courses are prerequisites to other courses right so for instance uh I think cs229 is which is machine learning is a prerequisite for some of the other courses so obviously you can't take those other courses before you've taken the prerequisite so you do need to be sort of wary of of how these courses are related to each other and that's listed usually on the course uh on the course website if you go to a course you can see what its prerequisites are so you do need to make sure you're fulfilling the prerequisites in order to be able to take a course but after that there's no particular order that you need to take them in and again you don't need to take you don't need to pursue the certificate you can um just take an individual course and that relates to this other um uh a couple other interesting questions is is uh what's the difference between a graduate certificate and a master's degree I see that's being answered but I'll just address that briefly here so the difference of course is the total number of units that are required um you know a the most of our graduate certificates you can think of as um modeled on the depth areas that are part of the computer science master's degree so the AI certificate program generally speaking does not it's not perfect but generally speaking lines up with Stanford's computer science master's degree artificial intelligence depth area right so it's really like a targeted pursuit of a subset of the total master's degree right it's the same right you would take the same courses if you're pursuing the Master's Degree as if you're pursuing the certificate but you're just taking a smaller slice of those courses and so it allows Learners who don't need a master's degree and a lot of our Learners already have especially in AI already have master's degrees or already have a PhD but maybe they earned it five or ten years ago or they earned it at a at a university that didn't have a specialization in AI or they weren't ready to do the coursework in AI at that time and now they do feel ready and so they're plugging a sort of Gap in their knowledge that's one one good example of a typical student someone who's you know I I have a master's degree in computer science already I didn't do AI so I just need to take a few classes to really get up to speed on it that's a great example and where you don't want to pursue a whole another master's degree but you need to plug some some gaps the other uh other kind of students that often pursue this are ones who only have a bachelor's degree and are interested in potentially going on to get a master's degree and maybe they're interested in trying to get into the Stanford Masters program so they take these courses to one see if if they're ready for graduate level coursework and two in the event that you are admitted into the into the Stanford Masters program then you've already earned up to 18 units that you can transfer towards that master's degree and you're farther along in the program at that point um I'll address one other thing is um um is is that there's a question about uh how many students are are registered when the graduate program started so uh and that's a great question I probably should have said that beginning so you know Petra and I are both part of the Stanford center for professional development actually been around since the 50s it was started by Frederick Turman and I think 1954 and it started with the part-time and online well it wasn't online obviously at that time but part-time master's degrees it's obviously expanded and grown uh in the past 70 years and so it the program's been around for a long time this particular graduate certificate program it's a good question I don't actually remember when it was launched uh but I think it's been around for at least 10 years so it's been around and these courses have been offered for for quite a long period of time um so these are great questions please keep asking them uh let me I want to make sure that Petra has plenty of time to talk about the professional programs but I wanted to go into a a little bit more um information about the the courses themselves uh so again these are these are based on the graduate course and so if you want to find out information about a particular course you're going to want it's going to be based on the syllabus of the actual courses it's being offered and many of these courses are offered by different faculty in different quarters so what I'd recommend doing is if you go to Stanford online you look at our our course pages will have a description of the course there's often also a link out to the the course website and many of these courses have their own websites that are maintained you may not see the most up-to-date syllabus because uh you know but you'll probably see the syllabus from the last offering when you go into that syllabus you're going to you're going to see in detail uh usually what was involved in that class what the assignments were like uh you know what the readings were what the projects were you might even see examples of past projects I really encourage if you're thinking about it do a little bit of research and to look into those course syllabi because you can get a lot of information there about what's involved in those classes and that information will always be more up to date than anything we could provide on our website because those are generally being updated every time it's being offered by by The Faculty so that's a really great resource and place to kind of figure out more because again these will change based on who's teaching it and based on the quarter inch they changed a little bit every year because especially in this field as you know things are changing really fast when I first started working here one of my favorite and this has now happened many times is remember watching a lecture from one of the courses you know on the the second week and they were talking about unsolved problems or problems that hadn't been solved and then like in week eight they came back and were like oh that's been solved right so these things do change really quickly and they've been especially changing quickly in the last five or six years and perhaps that change of pace pace of change will maintain itself so these are constantly updated so that's why I'd recommend to go to learn a little bit more about these programs I do want to emphasize one thing here um and it relates to what I was saying about these being the same courses is you know the the the unique benefit of this program is that you are taking the same course there's no dumbing it down there's no changing it significantly it is the same course you're doing the same work um but that does mean that there are two essentially two audiences for these courses there are the on-campus students and they're the online students and although you're getting the same course of material right that that can create challenges and there will always be a little bit of a challenge as a fully online student or even if you're a student who's local who's primarily online but coming safer exams that is a challenge you can't just turn to the student next to you in the class and ask a question so it it really when you get ready if you're thinking about taking these courses think about that and think about how you can prepare yourself um to be an online student you're going to have to be a little bit more proactive right if there's an ed Forum or something like that a discussion forum where you can post questions you're going to want to be active there you're going to want to to take a look at and um you're going to want to take a look at the the syllabi very early on to make sure that you understand what the requirements are on that first week of classes so and all the deadlines and you're going to have to line it up with your work so there's just a lot that you have to do you have to be a little bit more proactive as an online student than you might be as an on-campus student so I wanted to emphasize it because these are really hard courses and they're not for everyone and there are some unique challenges and opportunities in this program all right I I should also yeah I skipped over this maybe I do want to emphasize that you will have you know largely the same support as on-campus students there will be faculty office hours that should be dedicated teaching assistants who are also holding office hours uh there's student messaging forums again a lot of what's happening in these courses anyway is happening online or happening through these message forms because many of the courses are quite large even on campus so uh you know the natural language processing course had 800 students I think enrolled in it this last winter uh so you know the difference between being an online student and an on-campus student is maybe not so great in an 800 person course where you know it's back of the lecture hall or just watching the recording online but you know again you are part of the course you can reach out to the Tas and the teaching team uh just as you would if you're an on-campus student let me see if there are any other what other I know a lot of questions are coming in and these are great um sometimes great question about I just see one at the top is their ta assigned for the online students there are Tas who will hold online office hours um in some of those courses have specific Tas who are specifically assigned to support the online students some of the some of the courses don't do that again it's very much up to the faculty and how they want to to run it um it's here let me just quickly um I I see uh you know how are these different from something like Corsair or mooc I mean this is you know it's the same thing as um you know I'd say is these are very intense courses I would just take a look at like the syllabus um although you'll be watching recordings of the course you are part of a cohort of students who are moving through it at the same time of both online students like yourself as well as uh on-campus students right so there is a much stronger social mechanism I guess there for support and for working through the material there are obviously also actual people who are responding to your questions and Grading your assignments uh Etc so it is it is you know it's it is a class it is just like a if you've taken a university level class it is a university level class that is being offered it's just that you uh and you're just doing it uh you're doing it online um I see some questions about access to other things you you do um I don't want to go into too much detail because I want to make sure petrol I've already like taken up too much time on this I'll go in a little bit more detail about some of the the resources that are available but briefly you do have access to all the Online Library resources you are given a Stanford login ID and Stanford email for the time that you're actively enrolled in courses that allows you to access most of the software and resources that are available to Stanford students if you wanted to come in person for the libraries you'd have to pay for Access there is a kind of visitor access pass I think it's a hundred dollars for for three months of of being able to get into libraries and look at books um let me uh jump ahead I think I have one more slide here uh all right and I'll just mention this before handing it over to to Petra so in terms of application for these for for taking graduate courses or pursuing The Graduate certificate you go to our Stanford online home home page you you will uh you you will create an account you'll fill out an application the application is it's not like applying for a master's degree right you will need a statement of purpose you'll need to upload uh information about your your transcripts so we can verify that you meet the prerequisites that you can verify what your minimum GPA is ETC you'll add some information about your professional experience and then you also do need to provide some information about your residency status here in the US or if you're abroad you know you there's just information on that kind of documentation and then your application is actually not complete until you enroll in your first course because as I said you're not admitted into a program you are your application is reviewed on a course by course basis and so you will enroll in a course and at that point the department will review your application say does this student meet the prerequisites for this program for this course excuse me for this course and then you'd be admitted in that course now when you take your next course they're going to review that application again and make sure you're meeting the prerequisites for that course as well um we'll have some more either a ton of questions and since uh since we're we're I've already eaten up so much time I want to pass it off to Petra and I'll try to answer some of these questions in the chat or save them for the end so um but I guess I'll again to emphasize here the application is there's no GRE or no test scores that are required you can apply anytime that there's a course that you're interested in taking is offered so if you wanted to take a course this summer you could apply right now and take a course this summer if you want to take it in the fall right you could apply in a couple months and take a course in the fall so you can apply at any time that of course is offered that you want to take all right uh and there's a little QR code if you want to find out more so I'll leave that here for just a second or two and then Petra I'm going to hand it off to you yes of course thank you so much Pax and it was a great introduction also as a starting point for the AI professional program and just to say currently I'm seeing 130 questions that came in and we are doing our best to address all of them if you don't get to yours ideally apologize but you should hopefully received an email address along with your kind of invitation so please don't hesitate to follow up after the call um so let me cover some details about the AI professional program so the AI professional program is basically a series of online courses that are kind of closely mimicking the graduate courses so if you if Pax talked about courses like cs221 artificial intelligence principles and techniques I will be talking about xcs221 artificial intelligence principles and techniques that is like based on the graduate class that is taught at Stanford University what we do though we try to make it more manageable for professional audiences what this means is that we are trying to lower the time commitment so just to kind of keep it straight we are not trying to make it simpler so if you join our professional class it doesn't mean it will be easier that you know the assignments will be much simpler none of this we are not coming across we might be trying to find some ways how to basic basically lower the time commitment so I think on average in the graduate class you would be spending let's say 15 to 20 hours a week on the course again an average some people spend much more some people spend less in the AI professional program we would be spending 10 to 15 hours a week again an average we see also some courses a little bit more challenging the others we do this basically by segmenting and editing the videos so you won't be getting kind of the full set of one and a half hour long videos you will be able to join our learning management system and be able to kind of follow up see videos segmented by topic and we see this already kind of reduces the time commitment I would say by like 10 percent um and then also we try to find some ways how to reduce the number of assignments or remove the project or do something else that would basically lower the time commitment this generally means that our courses don't include a project work with the exception of XCS to do for your natural language understanding and we don't have any final exams nothing like that we also try to include usually a little bit more hints and we also work a lot on the auto graders so while in the original graduate classes you might not have access to Auto graders always some classes do we always try to make sure that for recording assignments you have Auto creators so you kind of can keep resubmitting so this all kind of brings us to a little bit over time commitment while still keeping the difficulty level [Music] um per course yeah you can find a little bit more information over here in terms of which courses we are currently offering uh these are the events uh currently we are at seven if I'm counting correctly starting with artificial intelligence principles and techniques like all the way to our newest class deep multitask and metal learning I saw a bunch of questions coming in actually about a computer vision class or some other courses getting included in the professional program this decision is always made together with the faculty so I standardly can't make any promise that we will get this edit but standardly the kind of the courses you are asking for they are also on our radar and you know we always try to do our best but we can never make the promise right like this is the work together with the faculty and also the academic director uh out of these courses xcs224u natural language understanding is the only course with the project work um in terms of and we always get questions and I think I saw a bunch of them coming in also in the in kind of the Q a like if you don't know where to start like where do you start so the first course like up here artificial intelligence principles and techniques it's generally the course we recommended you starve it unless you already have something kind of specific in mind so is the same as in the graduate program you can take a single course you can take multiple courses you can take all of them it's really up to you like we don't require that you kind of take the whole program you can always kind of Join one course that you like if you do complete three courses out of this portfolio you will be getting AI professional certificate so that's what it basically means um when I talked about the time commitment I think it's important here to also say that our courses are pass fail so while in the graduate program packs was like talking about kind of the assignments you're getting the letter grade in our professional program you're getting uh kind of a professional certificate or like certificate in the particular course and the courses pass fail and generally it's 70 percent to pass the course which gives you again a little bit more flexibility into like you know how to succeed we obviously get a lot of high Achievers but we also know that some people just like can't make the hundred percent on everything um we run these courses as cohort so we try to also kind of uh kind of mimic The Graduate course experience and having 10 weeks courses uh so we run these as salt so-called cohort so you will be joining a group of students at around the same time so if the course is starting next Monday I believe access to 24w machine learning with grass is starting if you join that you will be joining like the other group of students you won't be alone you won't be starting on your own generally on average we have around 120 Learners in each particle cohort this number differs we standard don't have less than 100 uh sometimes we even have 200 but like 120 I think is the best guess we have mix of written and programming assignments and instead of kind of teaching assistance you will be getting support from industry experience course facilitators those are the people who took the original graduate class and they will be supporting the questions um you know you might be having about a subject uh they also often work in the industry directly in the field so they can talk to you about actually the industry applications uh we have and I will be talking about it more very vibrant like communities so you're able to ask your questions live and we always kind of encourage that for people to be asking on slack and as I mentioned if you complete and pastry courses you will be getting the professionals the target audience is fairly similar I would say but those are the people who don't need the letter grade so like if you're kind of like you just want to learn about the subject certificate is fine maybe you will be getting reimbursed from your employer and you just need to show your certificate uh but you want the same depth and breadth of the subject like this program is probably right for you prayer requisites are again fairly similar since the level of the content is again challenging we are trying to make it simpler we standardly talk about three main ones and in the applications the those are the kind of types of prerequisites we will be asking you about so we expect that you're proficient in Python we get a bunch of people who might know I don't know you know other languages this is totally fine but we do require that you kind of familiarize yourself with python before you start because the courses themselves they are quite quick so there will probably not be too much time to kind of catch up on python if you don't know it already so uh that's one of the product visits and then kind of The Graduate level uh math some people are fine with the undergrad level math if they kind of catch up on on some of the product visits uh using other resources but basically College calculus linear algebra probability Theory this is not kind of just for fun because we do in some courses have written assignments and there might be some derivations included I don't want to scare you off but uh you know like the math will be required for it uh on the other hand we have some courses where you might need a little bit of less math but at the same time our faculty strongly believe that this is like very important thing to know if you're if you want to be really good in debugging your own software if you want to delay not be restricted with off-the-shelf stuff available being creative like daily develop your own steps Etc uh lecture videos and I won't go to too much detail because I think we want to still kind of address as many questions as possible um so those are directly from The Graduate course lectures it might be a zoom video in case it happened during pandemic we are kind of moving away because the courses are obviously happening now in person segmented and edited for brevity and what is important to note and I know that there are people in this audience who are me maybe like might not have the resources to pay for these courses we try to always make the lecture videos available also via YouTube so I would encourage you to check out Stanford online uh YouTube uh portal and find them also there like if if you would like to kind of follow up on the subject I also recommend people who are interested in the classes but they can't make the decision is this class right for me what you are going to teach like just do a little bit of a quick Google search you will find lecture videos often on YouTube uh we try to regularly update them but the professional courses kind of take a take a priority in that and uh also like often the assignments and like a lot of the course materials is also available uh for free so I just want to mention that because I know like sometimes the cost might be high but you actually get by paying or like you know what's kind of the value is the support from the course facilitator you're able to ask your questions you get a community aspect right so there will be other 119 on average people who will be in some sort of a similar position you're able to kind of network connect of course if you want like some people don't like doing that you also get accountability like I Know Myself and I try to learn something you know on my own and I'm doing that it's sometimes hard to kind of keep the commitment to myself if I don't have any assignment deadline so in this case you will probably have some assignment deadline that kind of will keep you up to date and at the end you will be getting a certificate right so especially if you want to get reimbursed or like if you like to post it on LinkedIn would like to find a new job transition it might be helpful for your kind of future career steps won't go to Too Much details we are using basically a similar written assignments with a little bit more hints we have a bunch of programming assignments and we always develop the auto creators so you have some sort of a feedback so you're able to resubmit get some sort of a feedback talk to your course facilitator if you have any questions and as mentioned we do have very vibrant like Community where you can you can kind of use it as a forum for you to ask questions uh it's usually the fastest way how to get the response outside of kind of trying to schedule 101 with your course facilitator or if the course facilitator is running office hours like joining those you also have kind of like assignment check-ins and uh different sort of a call but I think the the spike comedy is very helpful in getting responses feedback uh we won't break too much people you know some people are happy some people are less happy we like people who are happy like if you find out this course is not for you we also have job transfer policy that is available if you find out that you can kind of make it at this time or maybe it wasn't what you were looking for and yeah I just went over it quite quickly because I know like we want to kind of allow enough time to at least address some of the questions that are coming in uh but I will pause while I'm looking and maybe packs if you could just give a little bit of a summary of this like comparison between the programs because it was a lot of information that we want to make sure it was somewhat understandable for you all on the call so this is kind of a summary slide comparison yeah so it's a good summary so again the uh the AI professional program is based on the AI graduate Court So based on the courses that are offered at Stanford um if you want to take the course that is being offered at Stanford for academic and you want to take it for academic credit you can take it through our AI graduate certificate through our our graduate programs um and so those are again you're taking the same class as everyone else uh you're taking it alongside students you're taking it as an online student versus the students who are taking it on campus and matriculated students who are taking on campus you would not be a a matriculated student you'd be what is called a non-degree student because you're not pursuing a degree um typically that it's a you know it's a quarter system so that's usually 10 weeks summer it's a little bit shorter it's eight weeks that's typically 10 weeks most students report spending 15 to 20 hours a week on those on a single course you earn again academic credit you can take up to 18 units of academic credit um I this was a great question that came in and it's not here but I should add you do need to take these courses for a grade so these are graded courses they're graded on the you know the the US system a through through f um and you do need to get a b or better to continue taking courses in terms of the support there are the T you know just like if you've taken a a course at a you know you know it well you know an American University you same thing with Tas with faculty there should there will be office hours some of those office hours not all of them but some of those office hours will be offered uh uh through online through Zoom there are usually um some kind of student form in addition to that we have a slack channel that is just for our students it's it's not a place to ask course specific questions but it's a place to ask logistical questions um You Follow The Graduate you know you follow the the academic calendar again 10 weeks um and uh you know I see we have a we have a typo I just see the price for the graduate program should be the four money signs for the professional program should be two so the AI graduate program is more expensive we got a really a lot of great questions about you know if there are any kind of fellowships or scholarships that are offered unfortunately there are not um in general actually Stanford does not provide those even for Master's programs so um you know a lot of our students who are taking either of these are being reimbursed by their organizations that's a common way that people fund it but unfortunately there are not um Fellowship programs for either of these the professional programs are based on that content right so usually they're taking recorded lectures from one of the more recent offerings of the of The Graduate course and again The Graduate lectures are the the lectures are being recorded that you know you you'll see them an hour after half an hour after they've they've been given the professional program is reusing the lecture content in the syllabi from the some of the graduate courses it has been modified slightly to make it little bit more manageable for for working professionals though both are directed at working professionals so usually it's about 10 to 15 hours a week try to maintain all the rigor of of the graduate programs but maybe making one module uh optional or something like that to give you more time and in order to work through the other stuff you do not earn academic credit you'll earn a professional certificate or continuing education units and there is support with industry experience course facilitators are usually people who have successfully completed The Graduate course and probably also the professional course and are very familiar with the material and they they support you through slack they support you through email and then in addition there's an online community of peers there's a slack Channel again for those courses and sort of allows you to network into to ask questions and to problem solve as you work through the material they're very similar I would say the other thing to note that is maybe worth with mentioning here is the graduate program as I said the the the material and the delivery is it's going to change every single time it's offered because the new faculty or different faculty are teaching it or the same faculty updates the course the professional program across all courses will have a much more consistent interface they'll have a much more consistent experience because we've been able to to sort of adjust it a little bit so you'll you'll you know once you start taking one AI professional course you'll have a very similar experience across others in terms of the the interface and the experience the graduate program there can be a lot more variety in between individual courses because a lot of the details are up to the teaching team um that's here there are a lot of other really good questions that I try to uh I tried to adjust some of them there uh let me just one question that keeps coming up for kind of the AI professional program since we are doing a little bit more work on the videos like editing segmenting and you know we need to kind of wait for the graduate course to happen before we are able to make updates if our courses are kind of up to date because they are not delivered live you're joining the platform and they are definitely are we always work with faculty on double checking what's changed what we might need to change uh especially I saw a number of questions coming about xcs224 and an LP with deep learning and xcs224u nlu because with the recent developments with all things GPT uh we we always make sure that the content is up to date I just wanted to mention that and one other uh thing to mention as well we we uh a lot of questions about going between the programs so there are two separate applications uh but for the professional program uh you can take a graduate course and have it count towards your your professional certificate so for instance if you wanted to take uh if you wanted to take the computer vision course and it were not it's not part of the AI professional program you can take two course in the professional program then take the one graduate course and you know assuming you're you're accepted into it and then you would you could earn the professional certificate you can't count toward professional courses towards the AI graduate program um there was a good question about whether if you like say completed CS so this is confusing xcs229 which is the professional version of machine learning if that would count as a prerequisite for the uh for the a graduate course that asks for cs229 um I don't have a definitive answer now we've been in conversation about allowing that making that an option so that you could take the prerequisite as a as in the professional program and then go into the graduate program and take more advanced courses so I don't have a definitive answer but we hope to be working towards that I did we also got some good questions about if you were going to take either of these courses where you do some of the refresher um refresher material I would say um we have a link of resources that we we provide if you go to The Graduate Pro certificate page and you click on um the I think it's a course materials I forget what we say maybe the planning document that the certificate planning document at the end of that we list some materials that you can use uh to to refresh your memory we do offer through the the credit bearing program so we do offer credit bearing programs that meet a lot of the prerequisites so you could take for instance um you know as part of the the computer science master's degree at Stanford they're kind of the core courses which include um things like probability for computer science um discrete math which is uh you know and and algorithms so you could take some of those courses as graduate courses for graduate credit to meet some of those prerequisites or to get up to speed if you're not up to speed on those topics um we do also offer math 51 which is basically multi-variable calculus the melting variable calculus and linear algebra that you need in order to take machine learning classes but we also point you to free resources if you say already met those prerequisites you just need to refresh them there are a ton of materials online that can help you do that we also there are some lectures that we have published on our YouTube channel on on linear algebra and introduction to machine learning on a lot of these courses that allow you to refresh refresh your memory most of these Pro courses themselves will also have optional Refreshers on probability theory on linear algebra on calculus on those kinds of things because you know all students will need to be up to speed and it's not just uh online students who need that refresher so again I recommend going to The Graduate certificate page clicking on the course plan the link at the top on the course planning document downloading that at the end you'll see some some links to resources um I think the professional program also can provide some links uh there and so yeah it's a great question Petra are there other questions I I see we're at we're Beyond time which is great there have been a lot of good questions um but are there any others you want to address um um I think just like I understand like again like there's so many questions and we'd really appreciate it if we couldn't get to yours uh I also posted the email address within the Q a box and hopefully you also have the access to the the kind of request the email scpd AI uh Team so please don't hesitate to reach out afterwards also you know like there's you know I see the questions coming up so I'm sure that you're curious about um about your question I I think that that said parks there wait so about some like we are trying to answer them as we as we go uh so yeah online our last slide is the question so I I'll leave actually the the uh the I think this summary is great um so really appreciate everyone for joining us today I know that was a ton of information um and we I know even when we answer those questions sometimes there's so much information it's hard to process at all again I encourage you going to the Stanford online website looking at those programs um is Petra said a lot of this stuff is online and available for free as well so let's say you wanted to you know think about Stanford's machine learning graduate course or even the professional course well we have lecture videos from 2018 I think from the summer I think we have three three years of lecture videos there available online on our YouTube channel so you can go watch the lectures online see what those lectures will look like see what the quality of the lecture recordings are and then I would search just Google search cs229 Stanford and it'll likely pull up the most recent offering of that course you look at the syllabus and you can go through and say you know what are the problems sometimes they just have everything there they have the problem sets they have you know they have uh you know what the assignment so you can get a good sense of what the rigor of and the topics of these classes are just by you know spending 10 15 minutes searching on our YouTube channel or searching on the um or searching on the uh you know on on their on their syllabus on their course websites it's a really great place to start and for many people also as Petra said that's the better option you know you you already have extensive experience um you just want to refresh it you can go through that material as well um what you're paying for here are the credits and you're paying for the support that it comes with taking it from a group of peers and having professionals whether those are Master students and PhD students and faculty who are supporting you or the experienced industry uh facilitators so it's a lot to think about we really appreciate you joining us here again please don't hesitate to email us with other questions and we hope you have a great great rest of your week thanks everyone thank you so much thank you

2023-06-06 19:04

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