How AWS Educates Learners on Cloud Computing with Valerie Singer

Episode Summary

Valerie Singer, GM of Global Education at AWS, joins Corey on Screaming in the Cloud to discuss the vast array of cloud computing education programs AWS offers to people of all skill levels and backgrounds. Valerie explains how she manages such a large undertaking, and also sheds light on what AWS is doing to ensure their programs are truly valuable both to learners and to the broader market. Corey and Valerie discuss how generative AI is applicable to education, and Valerie explains how AWS’s education programs fit into a K-12 curriculum as well as job seekers looking to up-skill.

Episode Show Notes & Transcript

About Valerie

As General Manager for AWS’s Global Education team, Valerie is responsible for
leading strategy and initiatives for higher education, K-12, EdTechs, and outcome-
based education worldwide. Her Skills to Jobs team enables governments, education
systems, and collaborating organizations to deliver skills-based pathways to meet
the acute needs of employers around the globe, match skilled job seekers to good
paying jobs, and advance the adoption of cloud-based technology.

In her ten-year tenure at AWS, Valerie has held numerous leadership positions,
including driving strategic customer engagement within AWS’s Worldwide Public
Sector and Industries. Valerie established and led the AWS’s public sector global
partner team, AWS’s North American commercial partner team, was the leader for
teams managing AWS’s largest worldwide partnerships, and incubated AWS’s
Aerospace & Satellite Business Group. Valerie established AWS’s national systems
integrator program and promoted partner competency development and practice
expansion to migrate enterprise-class, large-scale workloads to AWS.

Valerie currently serves on the board of AFCEA DC where, as the Vice President of
Education, she oversees a yearly grant of $250,000 in annual STEM scholarships to
high school students with acute financial need.

Prior to joining AWS, Valerie held senior positions at Quest Software, Adobe
Systems, Oracle Corporation, BEA Systems, and Cisco Systems. She holds a B.S. in
Microbiology from the University of Maryland and a Master in Public Administration
from the George Washington University.

Links Referenced:


Announcer: Hello, and welcome to Screaming in the Cloud with your host, Chief Cloud Economist at The Duckbill Group, Corey Quinn. This weekly show features conversations with people doing interesting work in the world of cloud, thoughtful commentary on the state of the technical world, and ridiculous titles for which Corey refuses to apologize. This is Screaming in the Cloud.

Corey: Welcome to Screaming in the Cloud. I’m Corey Quinn. A recurring theme of this show in the, what is it, 500 some-odd episodes since we started doing this many years ago, has been around where does the next generation come from. And ‘next generation’ doesn’t always mean young folks graduating school or whatnot. It’s people transitioning in, it’s career changers, it’s folks whose existing jobs evolve into embracing the cloud industry a lot more readily than they have in previous years. My guest today arguably knows that better than most. Valerie Singer is the GM of Global Education at AWS. Valerie, thank you for agreeing to suffer my slings and arrows. I appreciate it.

Valerie: And thank you for having me, Corey. I’m looking forward to the conversation.

Corey: So, let’s begin. GM, General Manager is generally a term of art which means you are, to my understanding, the buck-stops-here person for a particular division within AWS. And Global Education sounds like one of those, quite frankly, impossibly large-scoped type of organizations. What do you folks do? Where do you start? Where do you stop?

Valerie: So, my organization actually focuses on five key areas, and it really does take a look at the global strategy for Amazon Web Services in higher education, research, our K through 12 community, our community of ed-tech providers, which are software providers that are specifically focused on the education sector, and the last plinth of the Global Education Team is around skills to jobs. And we care about that a lot because as we’re talking to education providers about how they can innovate in the cloud, we also want to make sure that they’re thinking about the outcomes of their students, and as their students become more digitally skilled, that there is placement for them and opportunities for them with employers so that they can continue to grow in their careers.

Corey: Early on, when I was starting out my career, I had an absolutely massive chip on my shoulder when it came to formal education. I was never a great student for many of the same reasons I was never a great employee. And I always found that learning for me took the form of doing something and kicking the tires on it, and I had to care. And doing rote assignments in a ritualized way never really worked out. So, I never fit in in academia. On paper, I still have an eighth-grade education. One of these days, I might get the GED.

But I really had problems with degree requirements in jobs. And it’s humorous because my first tech job that was a breakthrough was as a network administrator at Chapman University. And that honestly didn’t necessarily help improve my opinion of academia for a while, when you’re basically the final tier escalation for support desk for a bunch of PhDs who are troubled with some of the things that they’re working on because they’re very smart in one particular area, but have challenges with broad tech. So, all of which is to say that I’ve had problems with the way that education historically maps to me personally, and it took a little bit of growth for me to realize that I might not be the common, typical case that represents everyone. So, I’ve really come around on that. What is the current state of how AWS views educating folks? You talk about working with higher ed; you also talk about K through 12. Where does this, I guess, pipeline start for you folks?

Valerie: So, Amazon Web Services offers a host of education programs at the K-12 level where we can start to capture learners and capture their imagination for digital skills and cloud-based learning early on, programs like GetIT and Spark make sure that our learners have a trajectory forward and continue to stay engaged.

Amazon Future Engineers also provides experiential learning and data center-based experiences for K through 12 learners, too, so that we can start to gravitate these learners towards skills that they can use later in life and that they’ll be able to leverage. That said—and going back to what you said—we want to capture learners where they learn and how they learn. And so, that often happens not in a K through 12 environment and not in a higher education environment. It can happen organically, it can happen through online learning, it can happen through mentoring, and through other types of sponsorship.

And so, we want to make sure that our learners have the opportunities to micro-badge, to credential, and to experience learning in the cloud particularly, and also develop digital skills wherever and however they learn, not just in a prescriptive environment like a higher education environment.

Corey: During the Great Recession, I found that as a systems administrator—which is what we called ourselves in the style of the time—I was relatively weak when it came to networking. So, I took a class at the local community college where they built the entire curriculum around getting some Cisco certifications by the time that the year ended. And half of that class was awesome. It was effectively networking fundamentals in an approachable, constructive way, and that was great. The other half of the class—at least at the time—felt like it was extraordinarily beholden to, effectively—there’s no nice way to say this—Cisco marketing.

It envisioned a world where all networking equipment was Cisco-driven, using proprietary Cisco protocols, and it left a bad smell for a number of students in the class. Now, I’ve talked to an awful lot of folks who have gone through the various AWS educational programs in a variety of different ways and I’ve yet to hear significant volume of complaint around, “Oh, it’s all vendor captured and it just feels like we’re being indoctrinated into the cult of AWS.” Which honestly is to your credit. How did you avoid that?

Valerie: It’s a great question, and how we avoid it is by starting with the skills that are needed for jobs. And so, we actually went back to employers and said, “What are your, you know, biggest and most urgent needs to fill in early-career talent?” And we categorized 12 different job categories, the four that were most predominant were cloud support engineer, software development engineer, cyber analyst, and data analyst. And we took that mapping and developed the skills behind those four different job categories that we know are saleable and that our learners can get employed in, and then made modifications as our employers took a look at what the skills maps needed to be. We then took the skills maps—in one case—into City University of New York and into their computer science department, and mapped those skills back to the curriculum that the computer science teams have been providing to students.

And so, what you have is, your half-awesome becomes full-awesome because we’re providing them the materials through AWS Academy to be able to proffer the right set of curriculum and right set of training that gets provided to the students, and provides them with the opportunity to then become AWS Certified. But we do it in a way that isn’t all marketecture; it’s really pragmatic. It’s how do I automate a sequence? How do I do things that are really saleable and marketable and really point towards the skills that our employers need? And so, when you have this book-end of employers telling the educational teams what they need in terms of skills, and you have the education teams willing to pull in that curriculum that we provide—that is, by the way, current and it maintains its currency—we have a better throughway for early-career talent to find the jobs that they need, and the guarantee that the employers are getting the skills that they’ve asked for. And so, you’re not getting that half of the beholden that you had in your experience; you’re getting a full-on awesome experience for a learner who can then go and excite himself and herself or theirself into a new position and career opportunity.

Corey: One thing that caught me a little bit by surprise, and I think this is an industry-wide phenomenon is, whenever folks who are working with educational programs—as you are—talk about, effectively, public education and the grade school system, you refer to it as ‘K through 12.’ Well, last year, my eldest daughter started kindergarten and it turns out that when you start asking questions about cloud computing curricula to a kindergarten teacher, they look at you like you are deranged and possibly unsafe. And yeah, it turns out that for almost any reasonable measure, exposing—in my case—a now six-year-old to cloud computing concepts feels like it’s close cousins to child abuse. So—

Valerie: [laugh].

Corey: So far, I’m mostly keeping the kids away from that for now. When does that start? You mentioned middle school a few minutes ago. I’m curious as to—is that the real entry point or are there other ways that you find people starting to engage at earlier and earlier ages?

Valerie: We are seeing people engage it earlier and earlier ages with programs like Spark, as I mentioned, which is more of a gamified approach to K through 12 learning around digital skills in the cloud. also has a tremendous body of work that they offer K through 12 learners. That’s more modularized and building block-based so that you’re not asking a six-year-old to master the art of cloud computing, but you’re providing young learners with the foundations to understand how the building blocks of technology sit on top of each other to actually do something meaningful.

And so, gears and pulleys and all kinds of different artifacts that learners can play with to understand how the inner workings of a computer program come together, for instance, are really experientially important and foundationally important so that they understand the concepts on which that’s built later. So, we can introduce these concepts very early, Corey, and kids really enjoy playing with those models because they can make things happen, right? They can make things turn and they can make things—they can actually, you know, modify behaviors of different programming elements and really have a great experience working in those different programs and environments like and Spark.

Corey: There are, of course, always exceptions to this. I remember the, I think, it’s the 2019 public sector summit that you folks put on, you had a speaker, Karthick Arun, who at the time was ten years old and have the youngest person to pass the certification test to become a cloud practitioner. I mean, power to him. Obviously, that is the sort of thing that happens when a kid has passion and is excited about a particular direction. I have not inflicted that on my kids.

I’m not trying to basically raise whatever the cloud computing sad version is of an Olympian by getting them into whatever it is that I want them to focus on before they have any agency in the matter. But I definitely remember when I was a kid, I was always frustrated by the fact that it felt like there were guardrails keeping me from working with any of these things that I found interesting and wanted to get exposure to. It feels like in many ways the barriers are coming down.

Valerie: They are. In that particular example, actually, Andy Jassy interceded because we did have age requirements at that time for taking the exam.

Corey: You still do, by the way. It’s even to attend summits and whatnot. So, you have to be 18, but at some point, I will be looking into what exceptions have to happen for that because I’m not there to basically sign them up for the bar crawl or have them get exposure to, like, all the marketing stuff, but if they’re interested in this, it seems like the sort of thing that should be made more accessible.

Valerie: We do bring learners on, you know, into re:Invent and into our summits. We definitely invite our learners in. I mean I think you mentioned, there are a lot of other places our learners are not going to go, like bar crawls, but our learners under the age of 18 can definitely take advantage of the programs that we have on offer. AWS Academy is available to 16 and up.

And again, you know, GetIT and Spark and Educate is all available to learners as well. We also have programs like Skill Builder, with an enormous free tier of learning modules that teams can take advantage of as well. And then Labs for subscription and fee-based access. But there’s over 500 courses in that free tier currently, and so there’s plenty of places for our, you know, early learners to play and to experiment and to learn.

Corey: This is a great microcosm of some career advice I recently had caused to revisit, which is, make friends in different parts of the organization you work within and get to know people in other companies who do different things because you can’t reason with policy; you can have conversations productively with human beings. And I was basing my entire, “You must be 18 or you’re not allowed in, full stop,” based solely on a sign that I saw when I was attending a summit at the entrance: “You must be 18 to enter.” Ah. Clearly, there’s no wiggle room here, and no—it’s across the board, absolute hard-and-fast rule. Very few things are. This is a perfect example of that. So today, I learned. Thank you.

Valerie: Yeah. You’re very welcome. We want to make sure that we get the information, we get materials, we get experiences out to as many people as possible. One thing I would also note, and I had the opportunity to spend time in our skill centers, and these are really great places, too, for early learners to get experience and exposure to different models. And so earlier, when we were talking, you held up a DeepRacer car, which is a very, very cool, smaller-scale car that learners can use AI tools to help to drive.

And learners can go into the skill centers in Seattle and in the DC area, now in Cape Town and in other places where they’re going to be opening, and really have that, like, direct-line experience with AWS technology and see the value of it tangibly, and what happens when you for instance, model to move a car faster or in the right direction or not hitting the side of a wall. So, there’s lots of ways that early learners can get exposure in just a few ways and those centers are actually a really great way for learners to just walk in and just have an experience.

Corey: Switching gears a little bit, one of my personal favorite hobby horses is to go on Twitter—you know, back when that was more of a thing—and mock companies for saying things that I perceived to be patently ridiculous. I was gentle about it because I think it’s a noble cause, but one of the more ridiculous things that I’ve heard from Amazon was in 2020, you folks announced a plan to help 29 million people around the world grow their tech skills by 2025. And the reason that I thought that was ridiculous is because it sounded like it was such an over-the-top, grandiose vision, I didn’t see a way that you could possibly get anywhere even close. But again, I was gentle about this because even if you’re half-wrong, it means that you’re going to be putting significant energy, resourcing, et cetera, into educating people about how this stuff works to help lowering bar to entry, about lowering gates that get kept. I have to ask, though, now that we are, at the time of this recording, coming up in the second half of 2023, how closely are you tracking to that?

Valerie: We’re tracking. So, as of October, which is the last time I saw the tracking on this data, we had already provided skills-based learning to 13-and-a-half million learners worldwide and are very much on track to exceed the 2025 goal of 29 million. But I got to tell you, like, there’s a couple of things in there that I’m sure you’re going to ask as a follow-up, so I’ll go ahead and talk about it practically, and that is, what are people doing with the learning? And then how are they using that learning and applying it to get jobs? And so, you know, 29 million is a big number, but what does it mean in terms of what they’re doing with that information and what they’re doing to apply it?

So, we do have on my team an employer engagement team that actually goes out and works with local employers around the world, builds virtual job fairs and on-prem job fairs, sponsors things like DeepRacer League and Cloud Quests and Jam days so that early-career learners can come in and get hands-on and employers can look at what the potential employees are doing so that they can make sure that they have the experience that they actually say they have. And so, since the beginning of this year, we have already now recruited 323 what we call talent shapers, which are the employer community who are actually consuming the talent that we are proffering to them and that we’re bringing into these job fairs. We have 35,000 learners who have come through our job fairs since the beginning of the year. And then we also rely—as you know, like, we’re very security conscious, so we rely on self-reported data, but we have over 3500 employed early-career talent self-reported job hires. And so, for us, the 29 million is important, but how it then portrays itself into AWS-focused employment—that’s not just to AWS; these are by the way those 3500 learners who are employed went to other companies outside of AWS—but we want to make sure that the 29 million actually results in something. It’s not just, you know, kind of an academic exercise. And so, that’s what we’re doing on our site to make sure that employers are actually engaged in this process as well.

Corey: I want to bring up a topic that has been top-of-mind in relation to this, where there has been an awful lot of hue and cry about generative AI lately, and to the point where I’m a believer in this. I think it is awesome, I think it is fantastic. And even for me, the hype is getting to be a little over the top. When everyone’s talking about it transforming every business and that entire industries seem to be pivoting hard to rebrand themselves with the generative AI brush, it is of some concern. But I’m still excited by the magic inherent to aspects of what this is.

It is, on some level—at least the way I see it—a way of solving the cloud education problem that I see, which is that, today if I want to start a company and maybe I just got out of business school, maybe I dropped out of high school, doesn’t really matter. If it involves software, as most businesses seem to these days, I would have to do a whole lot of groundwork first. I have to go and take a boot camp class somewhere for six months and learn just enough code to build something horrible enough to get funding so that then I can hire actual professional engineers who will make fun of what I’ve written behind my back and then tear it all out and replace it. On some level, it really feels like the way to teach people cloud skills is to lower the bar for those cloud skills themselves, to help reduce the you must be at least this smart to ride this amusement park ride style of metering stick.

And generative AI seems like it has strong potential for doing some of these things. I’ve used it that way myself, if we can get past some of the hallucination problems where it’s very confident and also wrong—just like, you know, many of the white engineers I’ve worked with who are of course, men, in the course of my career—it will be even better. But I feel like this is the interface to an awful lot of cloud, if it’s done right. How are you folks thinking about generative AI in the context of education, given the that field seems to be changing every day?

Valerie: It’s an interesting question and I see a lot of forward movement and positive movement in education. I’ll give you an example. One company in the Bay Area, Khan Academy is using Khanmigo, which is one of their ChatGPT and generative AI-based products to be able to tutor students in a way that’s directive without giving them the answers. And so, you know, when you look at the Bloom’s sigma problem, which is if you have an intervention with a student who’s kind of on the fence, you can move them one standard deviation to the right by giving them, sort of, community support. You can move them two standard deviations to the right if you give them one-to-one mentoring.

And so, the idea is that these interventions through generative AI are actually moving that Bloom’s sigma model for students to the right, right? So, you’re getting students who might fall through the cracks not falling through the cracks anymore. Groups like Houston Community College are using generative AI to make sure that they are tracking their students in a way that they’re going into the classes that they need to go into and they’re using the prerequisites so that they can then benefit themselves through the community college system and have the most efficient path towards graduation. There’s other models that we’re using generative AI for to be able to do better data analysis in educational institutions, not just for outcomes, but also for, you know, funding mechanisms and for ways in which educational institutions [even operationalized 00:21:21]. And so, I think there’s a huge power in generative AI that is being used at all levels within education.

Now, there’s a couple of other things, too, that I think that you touched on, and one is how do we train on generative AI, right? It goes so fast. And how are we doing? So, I’ll tell you one thing that I think is super interesting, and that’s that generative AI does hold the promise of actually offering us greater diversity, equity, and inclusion of the people who are studying generative AI. And what we’re seeing early on is that the distribution in the mix of men and women is far better for studying of generative AI and AI-based learning modules for that particular outcome than we have seen in computer science in the past.

And so, that’s super encouraging, that we’re going to have more people from more diverse backgrounds participating with skills for generative AI. And what that will also mean, of course, is that models will likely be less biased, we’ll be able to have better fidelity in generative AI models, and more applicability in different areas when we have more diverse learners with that experience. So, the second piece is, what is AWS doing to make sure that these modules are being integrated into curriculum? And that’s something that our training and certification team is launching as we speak, both through our AWS Academy modules, but also through Skill Builder so those can be accessed by people today. So, I’m with you. I think there’s more promise than hue and cry and this is going to be a super interesting way that our early-career learners are going to be able to interact with new learning models and new ways of just thinking about how to apply it.

Corey: My excitement is almost entirely on the user side of this as opposed to the machine-learning side of it. It feels like an implementation detail from the things that I care about. I asked the magic robot in a box how to do a thing and it tells me, or ideally does it for me. One of the moments in which I felt the dumbest in recent memory has been when I first started down the DeepRacer, “Oh, you just got one. Now, here’s how to do it. Step one, open up this console. Good. Nice job. Step two”—and it was, basically get a PhD in machine learning concepts from Berkeley and then come back. Which is a slight exaggeration, but not by much.

It feels it is, on some level—it’s a daunting field, where there’s an awful lot of terms of art being bandied around, there’s a lot that needs to be explained in particular ways, and it’s very different—at least from my perspective—on virtually any other cloud service offering. And that might very well be a result of my own background. But using the magic thing, like, CodeWhisperer that suggests code that I want to complete is great. Build something like CodeWhisperer, I’m tapping out by the end of that sentence.

Valerie: Yeah. I mean, the question in there is, you know, how do we make sure that our learners know how to leverage CodeWhisperer, how to leverage Bedrock, how to leverage SageMaker, and how to leverage Greengrass, right, to build models that I think are going to be really experientially sound but also super innovative? And so, us getting that learning into education early and making sure that learners who are being educated, whether they are currently in jobs and are being re-skilled or they’re coming up through traditional or non-traditional educational institutions, have access to all of these services that can help them do innovative things is something that we’re really committed to doing. And we’ve been doing it for a long time. I may think you know that, right?

So, Greengrass and SageMaker and all of the AI and ML tools have been around for a long period of time. Bedrock, CodeWhisperer, other services that AWS will continue to launch to support generative AI models, of course, are going to be completely available not just to users, but also for learners who want to re-skill, up-skill, and to skill on generative AI models.

Corey: One last area I want to get into is a criticism, or at least an observation I’ve been making for a while about Kubernetes, but it could easily be extended to cloud in general, which is that, at least today, as things stand—this is starting to change, finally—running Kubernetes in production is challenging and fraught and requires a variety of skills and a fair bit of experience having done this previously. Before the last year or so of weird market behavior, if you had Kubernetes in production experience, you could relatively easily command a couple $100,000 a year in terms of salary. Now, as companies are embracing modern technologies and the rest, I’m wondering how they’re approaching the problem of up-leveling their existing staff from two sides. The first is that no matter how much training and how much you wind up giving a lot of those folks, some of them either will not be capable or will not have the desire to learn the new thing. And secondly, once you get those people there, how do you keep them from effectively going down the street with that brand new shiny skill set for, effectively, three times what they were making previously, now that they have those skills that are in wild demand across the board?

Because that’s simply not sustainable for a huge swath of companies out there for whom they’re not technology companies, they just use technology to do the thing that their business does. It feels like everything is becoming very expensive in a personnel perspective if you’re not careful. You obviously talk to governments who are famously not known for paying absolute top-of-market figures for basically any sort of talent—for obvious reasons—but also companies for whom the bottom line matters incredibly. How do you square that circle?

Valerie: There’s a lot in that circle, so I’ll talk about a specific, and then I’ll talk about what we’re also doing to help learners get that experience. So, you talked specifically about Kubernetes, but that could be extracted, as you said, to a lot of other different areas, including cyber, right? So, when we talk about somebody with an expertise in cybersecurity, it’s very unlikely that a new learner coming out of university is going to be as appealing to an employer than somebody who has two to three years of experience. And so, how do we close that gap of experience—in either of those two examples—to make sure that learners have an on-ramp to new positions and new career opportunities? So, the first answer I’ll give you is with some of our largest systems integrators, one of which is Tata Consulting Services, who is actually using AWS education programs to upskill its employees internally and has upskilled 19,000 of its employees using education programs including AWS Educate, to make sure that their group of consultants has absolutely the latest set of skills.

And so, we’re seeing that across the board; most of our, if not all of our customers, are looking at training to make sure that they can train not only their internal tech teams and their early-career talent coming in, but they can also train back office to understand what the next generation of technology is going to mean. And so, for instance, one of our largest customers, a telco provider, has asked us to provide modules for their HR teams because without understanding what AI and ML is, what it does, and what how to look for it, they might not be able to then, you know, extract the right sets of talent that they need to bring into the organization. So, we’re seeing this training requirement across the business and not just in technical requirements. But you know, bridging that gap with early-career learners, I think is really important too. And so, we are experimenting, especially at places like Miami Dade College and City University of New York with virtual internships so that we can provide early-career learners with experiential learning that then they can bring to employers as proof that they have actually done the thing that they’ve said that they can demonstrate that they can do.

And so, companies like Parker Dewey and Riipen and Forage and virtual internships are offering those experiences online so that our learners have the opportunity to then prove what they say that they can do. So, there’s lots of ways that we can go about making sure learners have that broad base of learning and that they can apply it. And I’ll tell you one more thing, and that’s retention. And we find that when learners approach their employer with an internship or an apprenticeship, that their stickiness with that employer because they understand the culture, they understand the project work, they’ve been mentored, they’ve been sponsored, that they’re stickiness within those employers it’s actually far greater than if they came and went. And so, it’s important and incumbent on employers, I think, to build that strong connective tissue with their early-skilled learners—and their upskilled learners—to make sure that the skills don’t leave the house, right? And that is all about making sure that the culture aligns with the skills aligns, with the project work, and that it continues to be interesting, whether you’re a new learner or you’re a re-skilled learner, to stay in-house.

Corey: My last question for you—and I understand that this might be fairly loaded—but I can’t even come up with a partial list that does it any justice to encapsulate the sheer number of educational programs that you have in flight for a variety of different folks. The details and nuances of these are not something that I store in RAM, so I find that it’s very easy to talk about one of these things and wind up bleeding into another. How do you folks keep it all straight? And how should people think about it? Not to say that you are not people. How should people who do not work for AWS? There we go. We are all humans here. Please, go [laugh] ahead.

Valerie: It’s a good question. So, the way that I break it down—and by the way, you know, AWS is also part of Amazon, so you know, I understand the question. And we have a lot of offerings across Amazon and AWS. AWS education programs specifically, are five. And those five programs, I’ve mentioned a few today: AWS Academy, AWS Educate, AWS re/Start, GetIT, and Spark are free, no-fee programs that we offer both the community and our education providers to build curriculum to offer digitally, and cloud-based skills curriculum to learners.

We have another product that I’m a huge fan of called Skill Builder. And Skill Builder is, as I mentioned before, an online educational platform that anybody can take advantage of the over 500 classes in the free tier. There’s learning plans for a lot of different things, and some I think you’d be interested in, like cost optimization and, you know, financial modeling for cloud, and all kinds of other more technically-oriented free courses. And then if learners want to get more experience in a lab environment, or more detailed learning that would lead to, for instance a, you know, certification in solutions architecture, they can use the subscription model, which is very affordable and provides learners an opportunity to work within that platform. So, if I’m breaking it down, it really is, am I being educated and in a way that is more formalized or am I going to go and take these courses when I want them and when I need them, both in the free tier and the subscription tier.

So, that’s basically the differences between education programs and Skill Builder. But I would say that if people are working with AWS teams, they can also ask teams where is the best place to be able to avail themselves of education curriculum. And we’re all passionate about this topic and all of us can point users in the right direction as well.

Corey: I really want to thank you for taking the time to go through all the things that you folks are up to these days. If people want to learn more, where should they go?

Valerie: So, the first destination, if they want cloud-based learning, is really to take a look at AWS training and certification programs, and so, easily to find on I would also point our teams—if they’re interested in the tech alliances and how we’re formulating the tech alliances—towards a recent announcement between City University of New York, the New York Jobs CEO Council, and the New York Mayor’s Office for more details about how we can help teams in the US and outside the US—we also have tech alliances underway in Egypt and Spain and other countries coming on board as well—to really, you know, earmark how government and educational institutions and employers can work together.

And then lastly, if employers are listening to this, the one output to all of this is that you pointed out, and that’s that our learners need hands-on learning and they need the on-ramp to internships, to apprenticeships, and jobs that really are promotional for, like, career talent. And so, it’s incumbent, I think, on all of us to start looking at the next generation of learners, whether they come out of traditional or non-traditional means, and recognize that talent can live in a lot of different places. And we’re very happy to help and happy to do that matchup. But I encourage employers to dig deeper there too.

Corey: And we will, of course, put links to that in the show notes. Thank you so much for taking the time out of your day to speak with me about all this. I really appreciate it.

Valerie: Thank you, Corey. It’s always fun to talk to you.

Corey: [laugh]. Valerie Singer, GM of Global Education at AWS. I’m Cloud Economist Corey Quinn, and this is Screaming in the Cloud. If you’ve enjoyed this podcast, please leave a five-star review on your podcast platform of choice, whereas if you’ve hated this podcast, please leave a five-star review on your podcast platform of choice, along with a comment telling me exactly which AWS service I should make my six-year-old learn about as my next step in punishing her.

Corey: If your AWS bill keeps rising and your blood pressure is doing the same, then you need The Duckbill Group. We help companies fix their AWS bill by making it smaller and less horrifying. The Duckbill Group works for you, not AWS. We tailor recommendations to your business and we get to the point. Visit to get started.

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