Well, it's a long story, so I'll try to give you the short version. Let's see. Like I actually got my degree in electrical engineering but had a hard time finding a job in that field when I graduated. So I ended up actually getting a job doing videogame development as a software engineer when I graduated college. So I moved out to California, worked in some bold adventure games. If you're old enough, you might remember like King's Quest and Leisure Suit Larry and stuff like that. So that's where I worked. Sierra Online and I stay in the video game industry for a few years between there and a place called Looking Glass Studios and in Massachusetts. After that moved down to Florida, where I started getting involved in dot com startup that was doing some three-D virtual avatar stuff and ultimately into the military training industry. So in that space, I was working on virtual reality training simulators for the Army and Navy and Air Force and various military branches, so that kind of got me Maur into some more professional aspects of three-D rendering technology and things like that And after a few years of that I decided it was time for something new throughout my resume, and ended up at amazon.com, which is kind of high point of my career, I suppose. And that was going back almost 12 years or so when I started there, so moved out to Seattle. I started there as a senior software engineer, and I was working on what they called recommend her system. So now we're starting to get into the world of data science in machine learning. So from there I work my way up into a senior manager position over the course of about nine years. By the time I left, I was actually running the engineering department of IMDb.com, which is one of their subsidiaries. So spent most of my career in Amazon doing machine learning related stuff. Recommended systems in particular. And eventually, you know, again, it was time for something new. So we packed up and moved to Florida, and I became self employed. So today I run Sun Dogs software, which consists of both software that I wrote individual simulation arena and also education, online education in the field of data science, machine learning. So that's actually my main focus right now, that online education piece. And today I have over 300,000 students across the world online that are learning big data in machine learning stuff from me, so that's been very rewarding.

I guess I'll take that in reverse order. So, you know, before you start to create a course, it's very important to, you know, figure out what you're gonna create a course in, right. So, there's a lot of tools out there to help you figure out what students are looking for so on, you know, me in particular, they have a very good, tool for, like, measuring, interest-based on search terms on the enemy platform. And it can also let you see if there's actually existing courses in that topic space or not. So that's a good way to figure out. Is there an unmet need for a new topic? For example, to this day, that's not a whole lot of courses on Apache Spark for some reason, so that's kind of one needs that I feel there, and it's first entering the relevance. The thing is, these technologies change very, very quickly, right? So it's almost a full-time job, just keeping these courses updated as new versions of the technology come out. So that's how we keep it relevant. Going forward and the exercises, in particular, change a lot. You know, for example, we have some courses on Amazon. Web service is certification preparation, and we have a lot of hands-on activities to show you how to use the service is. But Amazon is always changing how it all works and changing what the dashboards look like with the consul looks like. So we're always going back and updating those hands-on exercises. For the first part of the question, that process we follow typically, you know, once I've identified a topic for a new course, I'll spend about a month just researching that top again depth because no matter how much of an expert I might claim to be, nobody's really an expert in technology because things change so quickly. You know, you really have to be constantly educating yourself. So that's the first step. Educate myself as to the current state of the art. The current developments in whatever topic I'm going to teach at that. After that, I'll start to put together the course materials, and you should they'll start with the hands-on activities. The exercises spend a few weeks on that spend another couple of weeks putting together the slides for the course. And then comes the easy part, actually, recording the course itself. So just going through all those activities and slides and actually recording the actual video content, and that that can also take two or three weeks because these courses tend to be about 10 hours or so in length.

You know it's hard to say. I mean it's tough to generalize. I mean, I see from you to me that there's about a 50 50 split between students from the United States and students that are in India. So there's a huge demand for these topics in India. Rightfully so. You know, these are very lucrative skills to have, right? You know, if you understand machine learning and big data, you know, you can pretty much write your ticket. So as far as career growth in jobs, I mean, I don't want to give the impression that just taking an online course is enough to get a job. It's not, You know, you need to actually built to demonstrate that you can apply what you've learned to real-world situations. But for people who have taken the next step in, like done some freelance work or maybe want some cattle challenges or things like that, Yeah. I mean, you can get your foot in the door doing you know, either a data scientist role Or, you know, sometimes these roles are more described a software engineering positions, because at the end of the day, you know you're writing python code. You're writing scallop code, and employers want people that can, you know, learn new skills and apply new technologies in general, you know, they're looking more for general skills in this field as opposed to a very specific. Do you understand how to use this version of this specific technology, right?