It's a pleasure to be here. Thank U S. So I've been working in education for over 20 years on if we go back far enough. It started when I was in college and wanted to, uh wanted to teach and couldn't pursue teaching through the traditional channels of going to work for Department of Education or anything like that. So I got involved with a summer intensive program that really prove to me how much I loved teaching and education so that that planted the seeds. Um, from there, you know, I when I graduated from college, I started an educational nonprofit in New Orleans and that connected the schools with the community on brought support to those schools from there. I eventually got my MBA and then joined. I did a stint of management consulting with McKinsey. Then I joined the Scholastic, where I spent quite a number of years building products and doing, um, educational technology and marketing. I left there to go to Kaplan, which is, of course, the global education company thing I've been at since 2007. Medicine, which is a part of Kaplan that I run, was started from within Kaplan. So It's actually a brand that was birth by Kaplan in the end of 2013, and it was a way for a cap cling to start expanding into Cem other markets where they could have similar impact of what I mean by that is, I think what Kaplan is all about is helping people sort of achieved their career career goals, career objectives and proceeded by fun learning. And often for those who've taken a print course, they do that in a relatively intense environment. Uh, they do it with a dedicated student. Ah, great instructor, a strong curriculum. So you kind of take those pieces together and somebody who maybe wants to be a lawyer, you know, can can now get into law school of her choice on then can sort of achieve that dream. So he said, How do we take those same components and start extending it to other fields? Really high demand fields, new economy fields? And so it was really sort of that went to the genesis of medics back in the end of 2013

so at medicine. Our mission is to educate people to find value in data. We focus very Broadway on the whole field of data science and analytics training that can range from foundational skills, data literacy statistics. Uh huh. Two more data Analytics, data visualization, Python sequel. Things like that. Too much more advanced machine learning, natural language processing, deep learning, etcetera. And we we cover all of that. So to your first question, what training programs and courses do we offer are sort of Our flagship program has been a immersive, full time 12 week boot camp that is aimed at helping people get a career in data science and analytics. So this'll is something where people essentially quit whatever else they were doing, because it's a full time commitment and they're with us for those 12 weeks and then we work with them until they get employed. And today, you know, we have. We have graduates all over the world where, you know, at Google and Facebook and Disney and Apple and every place in between. Um so certainly one path is an immersive experience for somebody looking to change careers. That program is entirely offered live online um, but to my earlier point that we do much more. We also have shorter courses, courses that are more introductory in nature courses that are designed to help you if you're thinking about data science but want to just start doing beginning python and mathematics for data science or some of the introductory data sky and skills, so those courses can be shorter. Those could be 36 hours spread over six weeks. And again, all of those air also live online. So everything that we dio, whether it's at the foundational skill level and it's a 12 hour data literacy course or is a 12 week full time immersive boot camp, is 100% live online and the the amount of time it takes, it's just driven by the particular course.

Yeah, this is a great question, because certainly in our field, things changed quite rapidly, right? You know, a few years ago, just given the amount of data being created, the types of data, data structure, etcetera. There are new tools, new technologies on, you know, we our goal is to stay relevant to ensure that students are graduating with in demand skills are gonna help them to get hired. So we evaluate our curriculum constantly based on student feedback based on conversations with employers hiring partners, companies that are, um, practicing and doing data science every day to find out what is, You know, where we're hitting the mark and what skills are missing. We've, you know, as an example, you know, over the years, like we've started to do much more with certain tools in data engineering, Aziz, things like spark could become more, um, so and essentially, the processes that we take this feedback that we're getting from these different sources and we review it as a team, understand? Sort of, You know, where the trends are. We base that on our own understanding. So bear in mind that all of the data scientists who are full time employees with menace have been practicing data scientists. So this is This is not a program that sort of grown out of academia. It's one that's been sort of grown out of people working in industry and really have an appreciation for sort of what is used. Um, you know, in the real world in the wild. So we take all that feedback we call through it, we share it across the whole team and then say When you know, where do we need to make improvements? What do we need to take out? What do we need to put in Onda? We then, you know, work in smaller teams and we work on sprints and we develop MVPs were necessary. And that's how we continue to ensure, um, that our courses stay current. And you know now the truth is, is that some of the some of the changes that get a lot of that you're often read about, uh, are are things that are actually happening at a very small number of companies. So, for example, I just give one. You know, there's there's advances in computer vision that are really exciting. It's amazing what you can do today that you couldn't do 5 10 years ago, but also bear in mind that overwhelmingly, the large majority of companies that are holly using data science are not using something like computer vision. That tends to be something that is focused for a relatively sort of narrow subset of companies. So our goal is a training company is to make sure that we are me with those skills that are also most practical. So we want to teach you things like deep learning and computer vision and things like that. But we don't want to make that the focus, because you'll wind up with a bunch of skills that are not actually gonna be in demand at often the types of jobs that you're gonna get and the company you're gonna go thio following our program.