UMBC Mic'd Up

Primed to Pivot Professionally | UMBC Stories of Success

August 16, 2021 UMBC Mic'd Up with Michael Schlitzer and Dennise Cardona Season 1 Episode 14
UMBC Mic'd Up
Primed to Pivot Professionally | UMBC Stories of Success
Show Notes Transcript

When it comes to career success, an agile mindset can take a professional to new levels. Michael Schlitzer '21, M.P.S. Data Science, understands this and is primed to pivot in his career journey into Data Science as a result.

"Studying in the Data Science graduate program at UMBC at Shady Grove has changed the way I approach problems. The program has given me a whole new set of tools that have enabled me to transition in my way of looking at challenges."

Tune in to hear about Michael's journey and learn new ways of approaching challenges in career and life.

About UMBC's Data Science Graduate Programs
The Data Science graduate program at UMBC prepares students to respond to the growing demand for professionals with data science knowledge, skills, and abilities. Our program brings together faculty from a wide range of fields who have a deep understanding of the real-world applications of data analytics. UMBC’s Data Science programs prepare students to excel in data science roles through hands-on experience, rigorous academics, and access to a robust network of knowledgeable industry professionals. 

These programs were designed with working professionals in mind and offer courses in the evening and online to accommodate students with full-time jobs. With two campuses in Baltimore and Rockville, students can choose the location that best suits their needs. UMBC offers a 10-course Data Science Master’s program (M.P.S. in Data Science) as well as a 4-course post-baccalaureate certificate in Data Science.

Dennise Cardona  0:00  
Welcome to UMBC's Mic'd Up podcast. My name is Dennise Cardona from the Office of Professional Programs. I am joined here with my guest, Michael Schlitzer. He is a recent graduate of our data science graduate program. And he attended UMBC at the Universities at Shady Grove. Welcome, Michael. It's so great to have you here with me today. 

Michael Schlitzer  0:22  
Thanks, Dennise, it's nice to be here. 

Dennise Cardona  0:25  
Let's talk a little bit about you, Michael, and about yourself in terms of your professional endeavors and educational journey that took you to UMBC to study in the data science graduate program.

Michael Schlitzer  0:37  
Sure, my career has largely been in audio visual audio visual design, audio visual operations, a lot of operations, and then also sales. And I was working in audio visual, and really network operations. And I started there, so I it was it was it was a, it was a good effort and a good contract that I was working on. But I got about a year into it. And I said to my boss, I'd really like to do something different. I'd like to, to move in a different direction. And that had to do more with with programming. And he said, Well, go ahead and study stuff, I'll just go ahead and get learn what you want to learn. And so I started off, just kind of casting about on Coursera of all things. And through Coursera. I had grown up really, of course before the internet. And I had never taken computer science classes at at UMBC when I was an undergraduate back in the 80s. Mostly because I was I was not very good at math. And I was afraid of that. But I was pretty good at languages. And so I started taking these classes on Coursera, I took no HTML, I took a little bit of PHP back end web development, learned about SQL, and then took a Python class. So I always want to give credit to the great Dr. Chuck Charles Severance from the University of Michigan, whose class Python for everybody or pi four, he really opened my eyes and changed my life. So I took this Python class. And I really, really enjoyed the Python class, I finished that specialization in Coursera. And look for something else. And they had a specialization on Coursera and data science. So I started to take that and I that was writing a lot of code and working with data and, and I really, really enjoyed that. And as I got got into that a little bit more, you know, over the couple of weeks, those specializations tend to run in little modules and projects. But as I went through, it just really devoured it. And I got towards the end of it. And so you know, I really liked this, I think I'd like to do this. And most of the classes were through the University of Michigan and Michigan had had released or created a program called was a master's degree in applied data science or Mads. And so I had applied to that. And it was obviously Michigan, so it was all going to be virtual. And I really, I would really like to doubt a person to touch right a professor that I create, reach out to classmates that I could sit next to and know personally and say, I have a problem with this. I don't understand, can you help me? You get it right, personal touch. So one day, I was driving in around the DC area near Shady Grove. And I heard an ad on National Public Radio on our local radio station, WAMU, and they said UMBC has graduate programs in Data Science at the University Shady Grove. So literally, I'm driving down there and on the Beltway, and I go, UMBC, I love UMBC. That's where I got my undergraduate degree I love UMBC. Data science, hey, I want to do data science at Shady Grove, where in the world is Shady Grove, I have no idea where USG is or what USG is or how to get there. So I looked it up, found where it was, and then I applied through UMBC. And I was accepted into that program. And I said, this is this is it for me. And the first time that I went to USG, I drove with my with my son who I think was like 14 at the time. And I drove there and I pulled into the parking lot and I got out and I just looked at the campus and I said to my son, this is going to be good. And for the next two years, even though we were broken up with COVID it was at And so that's how I wound up at UMBC at Shady Grove, largely because of the marketing efforts of the UMBC professional programs team by advertising on the radio.

Dennise Cardona  5:13  
Yes, that is part of my job part of my team's job and so in worked. Yay!

Unknown Speaker  5:20  
Everytime I hear that ad on the radio. I say, I love UMBC. I love data science. And I love USG. So

Dennise Cardona  5:29  
that's like a marketing team's dream. 

Michael Schlitzer  5:32  
Okay, well, you know, marketing works, it really does work. It does. 

Dennise Cardona  5:36  
It does work to bring awareness. And that's so important that awareness, it's funny, I want to go back to something you said that made me chuckle a little bit because I grew up with I may be the same age range as you and I grew up where we didn't have computers and such like that. And when I went to college, I remember taking my first computer class was on a DOS system, we didn't even have a Windows back then. And I remember just feeling very lost in the whole computer world. And the idea of studying computer science at that point on mathematics, for me would have just been the, like the scariest thing in the world. And just interesting how life turns out. And I am in audio visual, I mean, that's what I do for the, for the university, video production. So it's just an interesting, it's just interesting that I listening to your story was for know,

Michael Schlitzer  6:28  
there's a lot of a lot of commonality and connection,

Dennise Cardona  6:32  
I'm really happy to hear that. It's, oh, this is what I'm happy to hear that it's really hard to find some to find a pathway. Sometimes in life, it's really hard to be able to make that connection and feel like yes, that's exactly what I need to be doing. Very few people have that privilege. And it sounds like you had that, that spark that went off. And so it's so wonderful to hear, when somebody has that spark go off, I too have experienced that. And it's a really wonderful feeling to be on the path that you were meant to be on. And you can tell you when you light up when you talk about it. And so that's really important. And I feel like that is when we can really dig in and do the important work in the world. It's when we're passionate about it.

Unknown Speaker  7:14  
It is you know, so many times, I have children, and you know, they started out, you start off in college, and you're not sure what you want to do. And I think it's, you know, I have a nephew in the military, and, you know, and then kids in college and other other relatives in college, you know, and at 18 years old, you're supposed to pick the thing that you want to do for the rest of your life. And get it right. And and I remember saying to my daughter, you there's no shame in going, Hey, I like this better and changing. And if you run into difficulty at the beginning, and then you change and you find something you like, you can let that go. And that's just a piece of general encouragement, kind of fatherly advice. Don't Don't let past troubles weigh you down, like an anchor, cut that rope and be happy in what you've moved into, and soar as far as you can. Without thinking yeah, but I, I screwed up at the beginning, and then I wasn't good at this. Hey, let that go. And, and I think that that's good advice, you know, you can get a degree in one thing and, and in later on in life, like like me is what they euphemistically call an adult learner. as a as a as an adult, go back and and find new things. Very little in life is wasted. And so what I found was, as I was in these classes, which were relatively new to me, right, it's old technology is SQL databases, whatever. All that stuff has been around for a long time. And I've worked with it, used it without ever really understanding it in the past. But then, as I walk, walk through the classes that I took in the data science program, of course, data science is multifaceted. I sit in class, they talk about things, and in my notes would be like, Oh, that's what that project that I worked on back in this time at this place. That's what we talked about. That's that's how that worked. And so I found again, that even though my current my academic path at UMBC would seem to have very little relationship to my background, either in sales or in audio visual or in video, video networks and video conferencing. Work is work and it was all related and I was able to pull from my past experiences and use it in class to deepen my understanding. That's not unique to me or my background at all. You know if you work in an office type setting or in any kind of technology, we all use computers these days, most likely, there's something in the subject matter that you're going to be able to pull from that's going to explain your make make the subject more valuable. And to you just more like Velcro, right, more

Dennise Cardona  10:19  
Absolutely. It's really important. And so here's my next question. And you kind of segued into it a little bit, is what challenged or maybe surprised you, once you started in the data science program at UMBC. 

Michael Schlitzer  10:32  
The one thing that that I really enjoyed about the graduate the data science graduate program at UMBC was that it was multifaceted. Even though it was very intense, right? at UMBC, we had extremely good professors. So there were classes in machine learning. There were classes in data management, really dealing with databases, there were classes in, quote, big data, I made little air quotes. And I said that which dealt with Spark, and all sorts of issues related to data management, on the web, when you're dealing with live data streams, like from Twitter or from things like that. What I really valued about the data science program at UMBC was that we touched on all of those things. And of course, you were required to know those things and work through the class. But it was not just a machine learning program. And if you don't like machine learning, well, you better go someplace else, right. So it was as much an exploration and then fairly deep dive into each of these different facets. But then, when we got to the capstone project, which was the last thing we had to do in the in the data science program at UMBC, you could really pick a project that fit your interests. And so some people did, I focused on really a machine learning, project, and other people whose projects were most interesting to me focused on machine learning projects, but other people did, like visual classification, where you're doing visual imagery, and then making real time learning and sort of a machine learning project. But they were dealing specifically with camera images, and other people did Big Data projects. And so that diversity came out in those capstone projects. And it was not cookie cutter, it was really, you know, make your Make Your Own Adventure, based on what you learned, make your own adventure. And I thought that was really, really valuable.

Dennise Cardona  12:54  
Yeah, it sounds like it was very relatable to what you're doing, you could make it applicable to what you're doing. So what you're learning on Wednesday night in the class, you can go to work on Thursday and apply it. And I love the idea that you had a variety of different perspectives from the students in your class. To me, that's one of the most powerful things about being in a graduate program is that diversity of thought of learners have perspectives of experiences, you have people who just graduated from people who have been out in the working world for a number of years and pulling that information is really a rich experience.

Unknown Speaker  13:33  
And I think the professional programs amplify that even even more, because as you just said, there, there are plenty of people in there who graduated two years ago, graduated from their undergraduate degree in the last two years or whatever. But there were plenty of people who would one gentleman in my class who had been a math teacher for 20, some years in, I think, Prince George's County Public Schools, and then wanted to do something different. And so he was there in any way of finding work in data science, you know, while he was still in the program, so that was really encouraging, and really good. Absolutely. But you do have that, why diversity. The other thing that I really enjoyed about the data science, the professional program and data science at UMBC, was, there was a big international component. So I was in class with people from, you know, I think, from Central Africa, from Iran, from China, from other people from Russia in the class. And so, not only do you have all these age, differences and experience differences, background differences, language differences, cultural differences, all of those things to me We're incredibly valuable and incredibly enriching. And so those the first time that we were on campus, you know, I enjoyed that more than, really than anything else just getting to know, people in that context. To me that was that, again, that's what I really wanted to seek out. And the reason that I chose you UMBC, at Shady Grove was because I could I could meet and touch other people,

Dennise Cardona  15:30  
it's like being a, you know, I'm gonna use an analogy here, I've been gardening gardening a lot lately. So I'm gonna use that. It's like putting a garden together, right. And the more variety you have, the more variety of flowers, wild flowers, possibly that you have, you're going to attract more and more pollinators. And it's going to be an enriching environment for a lot of different reasons. And when I think of education, especially at the higher level graduate program, when you have that kind of an environment where you have all that diversity, it just, it really is it levels it up, it brings you to a different level. And it brings that perspective and real world application to the forefront because well, we are out in the real world. That's what it is. It's rich in diversity. Right. should be. And yeah, so that's fantastic. Michael, can you tell us a little bit about what you're doing right now? What is your current role?

Unknown Speaker  16:27  
Sure. So so one of the things that so that's relatively complicated, just because it's it's a little bit in transition. So I'm still working in network operations. But at the same time, what I have learned at UMBC UMBC, at Shady Grove, in this data science program, what I've learned has enabled me to transition into more where I wanted to go in my work career. So I'm able to pivot into Control System Programming, because now I understand fundamentals of programming, object oriented design, and things like that. So professionally, it's allowed me to move into a new direction. And I've added some value to the company that I work for, largely through Python, which which which I had learned in which we used extensively, and really exclusively at the program at UMBC. And then, so there's that piece of it. And that's still growing, right? That's, that's, that's not done and dusted, it is still moving on. It takes a while, I also did the cybersecurity specialization at UMBC, that was the second part of my program, because you have to have just like as an undergraduate, you have to have, you have to, they want you to be a little bit broader. So you could do they have I don't even remember, but there's quite a few, like health informatics and management, there are quite a few other things that you need to take in order to get this degree. And I chose to take on cybersecurity classes. So I'm also working towards my CISSP certification as a result of all that I've learned at Shady Grove in the cybersecurity program. The other thing is that through the research that I had done for my capstone project, and largely throughout, throughout my time at the program, I've gotten more involved with kind of that that community. And so my real goal is to continue working as a postgraduate student to continue to work with one of my professors to turn this into a paper for publication on the research that I've done. And so, you know, it's a machine learning project. And that's what really has got me interested. So there's a lot of things balls in the air, and my brain has, you know, is working on multiple levels. But my wife, my lovely wife of 27 years or whatever, a UMBC graduate I would add, who says to me, you needed this, this? You are, I just haven't. It's been a long time since I've seen you so excited. And just really firing on all cylinders, you know, just with ideas and thoughts, and it's very exciting. So it's personally satisfying, but it's it even though it took a lot of work. And a lot of time, free time away from the family. Course In COVID we were all here anyway. It's been really good.

Dennise Cardona  19:52  
That sounds so amazing. I'm so happy for you because there's nothing like that feeling of having sparking on all different levels. So And being enthusiastic and passionate about getting up out of bed in the morning and doing some great things and using your mind in capacities that maybe you didn't even think were possible before you actually studied in this program. And now you've got all those fancy things going on.

Unknown Speaker  20:15  
That's exactly what it is, it definitely has changed the way I approach problems. You know, because when really, when you think about it, you know, I'm not sure who said it, I think I've heard it attributed to Albert Einstein, but I would not swear to that, when he said, you know, if the only tool you have in your toolbox is a hammer, then every, every problem begins to look like a nail, you know, and so, you know, if you have a screw, and you hit it with a hammer doesn't really do much good, except, you know, do a lot of damage. So what what the data science program at UMBC has given me is a whole host of new tools. And so now, when I run it, when I, when I'm presented with a problem, I look and go, I can do it this way, or I can do it this way. This is the better way, and then, you know, come up with a solution that two years ago, I would never have been able to come up with, I probably still have gotten an answer. Right. And, you know, the plumbing might have worked, but it's much more elegant, this way, and much more reproducible. And, and so I really value that. And so I have been able to turn that into where my current job, just turn that into code, basically, that can be reproduced it, you know, it's very satisfying, personally satisfying to do that. And, you know, nobody knows it. But it's all done with stuff I've learned from school.

Dennise Cardona  21:49  
Yeah, oh, my gosh, that's such a great, great, great statement. And I love the idea of a toolbox. Because, really, when you think about it, as we develop and grow as professionals, we might start off with a rudimentary toolbox with a few little things in there that could work on some things. But you use the word elegant. And I love that, because when you think about maybe the toolbox might work for a small scale project. But then when you move to a larger scale project, and you start filling that toolbox, along the along the journey to that big project, now, when you get there, when you've arrived, there, you have an Intel, you have a plethora of tools to use, and the outcomes will be a lot more elegant that way.

Michael Schlitzer  22:34  
That's right. And the other thing that I just to your to your point is you're probably come across problems, different problems, everyday things you've never seen before. And so I do I really like tape toolbox. The other analogy or the other, you know, thing that I think about a lot is a framework, you know, when you think about like, people who have been burned, they'll they'll sometimes use a skin grafts without using graph and then grow new skin on that framework to create sheets of skin, right that can heal people that have been badly injured. So when I think of is, when I'm presented with problems that I've never seen, you know, you can use the great Internet, and you can find things that may work. Two years ago, three years ago, whatever it was, you can't even appreciate the solution, because you have nothing to hang them on. Now, when I say hey, how can I solve this problem using this framework, something comes up, something pops up, and they go, Oh, this, this I understand. And then you can go through it and it winds up, you find out something that you can operationalize. And then you can turn from concept into into action or into product. And one of the examples of that, in my project, we were I was using a software tool, an application or package inside of, of Python, and every example didn't fit what I was doing. And so I was quite frustrated because I couldn't find any other examples that fit the way I wanted to use this tool to optimize some of my hyper parameters, you know, pulling my hair out, you know, going gray or, you know, stressing over this and you know, I had frustrated emails or frustration to my professor who I think just just eventually just started deleting the emails, you know, and then go to bed wake up the next day. Let's try this. So then the next email to my professors, nevermind, I figured it out, you know, but it's all because the work has brought me here, you know, up this ramp. So it's it's again, going back to physics, right the steps. You can't go from the Zero meters, 200 meters, but you can go up a ramp, and you can get there and you look back down, you're like, gosh, I came a long way. You know, and actually one big step. But it's it's a three meter jump versus 100 meter jump.

Dennise Cardona  25:15  
That is a very strong way to look at it. Very strong way. Michael, as we close out this podcast episode is here, what would you say was your biggest takeaway from studying at UMBC?

Unknown Speaker  25:32  
I think I think, Well, my biggest takeaway from UMBC, from from studying in the data science program at UMBC is that, gosh, I love UMBC. And you can do it. You can do it. You can do it. If you're sitting there. You know, I'm an encourager at heart. And I know a lot of times I sit down Go, people say to me, I don't know if I can. No, you can. You can do it. You can do it. Is it hard work? Yes, it's hard work. But you can do this. UMBC, and in my case, UMBC at Shady Grove, it really puts the world within arm's reach of where you are. And so we're all filled with self doubt we all struggle with, with with doubt. We struggle with issues of, you know, finances, and we struggle with issues and what if I'm not smart enough? take the leap bet on yourself. Because at UMBC, you can do it.

Dennise Cardona  26:44  
take the leap. I love that. Yes, you can do it. Michael, I can't think of a better statement to end this podcast episode. I want to thank you so much for being here with me. You've totally inspired me. I am thinking of the world in a whole new light today. And although I knew a lot of these things on the surface, below the surface, you've just brought them to the surface to me today. And I feel as though I could go out there and conquer the world after listening to you. I'm really Yeah, why don't we go get it? I'm really glad that you NBC Shady Grove the data science program has instilled in you this passion and the knowledge for you to go out there and make your world amazing and make the world for others amazing through the work that you do. So thank you. Thanks, Dennise. I appreciate the opportunity to talk with you. I thoroughly enjoyed it. Thank you, everyone for taking the time to listen to this episode of UMBC's Mic'd Up. We hope you enjoyed it. If you'd like to learn more about UMBC's graduate programs in data science, please visit us at data

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