E14 Breaking Into AI Without a Coding Background | UT Austin Certificate Experience

I saw how AIML was shaping the industries and transforming it not just through automation, but in enhancing customer experiences, optimizing business operations and fundamentally changing how products are being built today. So I knew I needed to get closer to that. The University of Austin, Texas AI ML postgraduate program offered the perfect blend of theoretical foundations and practical applications, which gave me the technical fluency to build and to bridge the gap between business and data science. Foreign.

Hi everyone. Welcome back to MBA Golden. BUZZER Today I'm joined by Ebby, a former client who's pursuing a certificate in artificial intelligence and machine learning. Tech is evolving at an insane pace and AI is at the center of it. But what is it really like to do a program in AI and machine learning? Who is it best for? How can it help you in your career? So if you've ever thought about diving deeper into AI or you're just curious about what, what this kind of program teaches you, you don't want to miss this episode. So, Evie, thank you so much for sitting down with me today.

It's an honor to be here. Thank you Ellen, for inviting me.

Maybe you could start by just telling us a little bit more about your background, a little more about you.

I'm a certified SCRUM Master and project management professional with almost a decade of experience in driving high impact projects and products while building self organized teams. I have a bachelor's degree in Information Resources Management. I have multiple certifications is Agile and Project Management and I'm currently expanding my skillset through a postgraduate program in artificial intelligence and machine learning for business applications, more or less to just complement my product and delivery expertise. So that's, that's kind of like the high level, I would say tech, my LinkedIn. To know more about my professional background, I predominantly worked in SaaS, companies, B2B and even the automotive company like Toyota. So yeah, that's, that's pretty much it.

I was always very impressed from the beginning with your background and how you're always staying up with trends, pursuing new certificates. So what made you decide to do this AI and machine learning course?

That's a really good question. So you know, choosing to pursue a postgraduate program in AIML was, was both a strategic and a personal decision. As you just heard, my background has always been rooted in product and agile delivery and I've always leaned towards data driven decision making. And over time I saw how AIML was shaping the industries and transforming it not just through automation, but in enhancing customer experiences, optimizing business operations and fundamentally changing how products are being built today. So I knew I needed to get closer to that. I initially explored an MBA with a focus on tech leadership. And Ellen, you were a huge part of that, considering you consulted me throughout the process. And I must say it was an amazing experience. I learned a lot about out myself right throughout the journey, figuring out my why and realizing just how much I had accomplished right in my career. So I was even admitted to NYU's Tech MBA program. But I ultimately decided to pivot towards a specialized AI ML program because I wanted to be closer to the technology itself, to not just understand it at a business level, but to actually work with the models, analyze data and apply machine learning concepts in real world scenarios. The University of Austin, Texas AI ML postgraduate program offered the perfect blend of theoretical foundations and practical applications, which gave me the technical fluency to build and to bridge the gap between business and data science.

Awesome. I'm glad you talked about that. Can you tell a little bit more about kind of practically speaking in your course, how does it look like learning AI in the certificate program? Because you mentioned. Exactly. In the Tech mba you it is more of this kind of business application. So what does it look like in terms of your courses? What do you study? What do projects look like?

Yeah, I would say that. Well, so I'm going to talk about two things, right? I'm going to talk about the reality of this particular program, right? Especially for anyone who's, who's trying to balance learning with work and family life. For me, I would say, you know, I didn't expect the program to be as technical as it was. I came in thinking it would be more about AI concepts, applications and like a high level strategy. But I quickly realized that to really understand it you have to get hands on with the models and the data and the algorithms, right? So at first it was a bit overwhelming because my background isn't in hardcore coding or data science. But what surprised me was how much I enjoyed the technical side once I got into it. Like, so I learned how to code with Python, I learned how to do data analysis, exploratory data analysis, machine learning, model building, and I worked on a range of machine learning models. Everything from, and I'm going to get a little bit technical here, but anything from linear and logistic regression, decision trees, random forest, to even more advanced algorithms like XGBOOST and artificial neural networks. We also explored supervised and unsupervised learning techniques like clustering and dimensionality reduction. And I recently just completed a deep learning project using neural network to predict customer churn. So gaining experience across both of these, you know, these, these both unsupervised and supervised model helped me build confidence in understanding how these techniques are used to solve real world problems. So overall, the program has given me a much deeper appreciation for AI and machine learning. Because what most people see is the front end. Right. You see the final product, you see the user experience, but behind the scenes there is a world of data preparation, model training, evaluation and iteration that powers those results. So being part of that process has completely changed how I see and engage with AI. It's very technical.

Wow, that's awesome. So with the programming, did you learn that in the course? Like are there classes that you took?

Wow.

So they got you up feed as well. It was okay that you just had that before.

It was okay. I didn't have the coding experience because the first course that you're going to do is Foundations in Python. So you're going to learn how to code. You do these things in Google, Collab and Jupyter. You're writing code literally. So you don't necessarily have to have a coding background, but you have to be open minded because you're going to get into it.

And would you say that the majority of your classmates came in with a coding background or were kind of in a similar situation where they had a great tech background like you, but maybe not on the technical side.

The individuals in my class, I can group them into three categories. So we have people from the business background, which are people like myself, people like, you know, project managers, business analysts, product managers. We also had people that were, you know, technical. Right. So software developers, people from those, you know, backgrounds. But then we also had another set of people, people in like the data and analytics world. People that, you know, come from heavy Excel background, they know math. You know, I wasn't really good at math, so it's like you have people who are really thinking technically from the numbers perspective. So that's how I would say the individuals in my class are grouped.

Yeah, that's awesome too. It must facilitate a lot of learning among those as well, right?

Yeah. When, when people ask questions, you, you understand why they're thinking that way because that's the background that they come from. When I ask questions, I'm thinking more from the business perspective, like, well, how does this benefit the business? How does this bring value? So that's the kind of mindset that I brought into this program. Yeah.

And is it mostly US based or there are there some international students mixed in there?

Yes, there are international students there as well.

Cool. Yeah. So then you get a really global view, which must be nice.

That's correct.

And you mentioned a lot of these concepts, which are a little over my head, so I don't remember exactly what they are. But what's been the most exciting thing among those that you've learned so far?

The most exciting part for me has been learning how to take those real world business problems and break them down into solvable data driven solutions. Right. So before the program, I understood the value of data, but now I know how to actually work with it. Right. So exploring data sets, asking the right questions, cleaning and transforming data, building models, and then interpreting the results to drive decisions. It's a completely different level of problem solving. So I worked on projects like Predicting Customer Churn. Right, Cool. Identifying factors that drive user behavior and being able to go from raw data to actionable insights has been incredibly rewarding. So it's also changed how I think. I now approach business problems with a data first mindset, asking, what does the data tell us? The model, you know, how can we model this to test our assumptions? So that shift in thinking has been one of the most exciting parts of the journey for me. It's not always about the technical skills. It's also about developing a new lens to problem solving.

Yeah, it's one of the things I always try to encourage clients to think about is the technical part. The classes are amazing. You know, that's obviously one of the best things. But one of the great things about programs too is they change the way that you think. Right. They change the way that we view the world. And yeah, it's really cool how this, this program combines the two so seamlessly.

Agreed, agreed.

And what's been the most challenging part of the program so far?

I would say the most challenging part has definitely been the pace. It's an accelerated program, so things move very quickly. And that requires a lot of discipline, especially when you're balancing work and in family life at the same time. For the past seven months, I've spent almost every weekend learning. On weekdays, I try to carve out at least an hour a day to stay on top of material and avoid falling back. It's been a real exercise, I must say, in time management and consistency. But that said, one thing that's really helped is having a dedicated program manager. So he's been incredibly supportive. Texting regularly helps me plan around my schedule and even a few times extending deadlines for project submissions when I needed it. Yeah, because, you know, I travel for work sometimes and I fall behind while it's been intense. It's also been manageable with the right structure, support and mindset.

And we have another episode, she mentioned family life where you're talking about what it's like to study while you're a parent. So make sure that you check that out because balancing all of those things is very impressive.

Take skill, great skill.

That's so cool that they have someone who's so willing to work with you and so willing to help you with your schedule. Because I know with a lot of other programs that's one of the main things people struggle with is burnout or how do I keep on top of everything.

Yeah, yeah, agreed.

And when you guys work on these projects, are you working on kind of real world applications for a specific company, a specific case? Is it more theoretical?

Yeah. So the program is very hands on, which is one of the things I've appreciated the most about it. From the beginning, we worked with real data sets for real companies, building models and applying what we've learned to solve practical, like real world business problems and not just studying it. We covered a solid foundational concept of Python, but every module ties directly into a project where you have to put that knowledge in actions. Like I said, I worked on projects like Predicting Customer Churn. I've analyzed loan default risks. So basically I can literally tell if you have a customer who will default on a loan that they get just by building a model to predict that and also building classification models with reward problems. These are not canned examples. They require data cleaning, feature engineering, model selection, and interpreting results in a way that business minded people can understand. So that's what I've loved the most. It wasn't just about learning how machine learning works, but also understanding how to use it to solve problems today. So that practical side of the program really helped me build confidence and connect the dots between the, the technology itself, machine learning, and then the value that it can bring.

Oh, that's so cool. With the fraud, was that for like a, a bank that they had you guys do that project for a startup?

Yeah, so it's for Therabank. But again, you know, they, we have access to these real data, real company data and we use it to build models. And not just a whole company data piece of it, but at the end of the day it's still considered big data because you're have data with over 50, 60,000 rows and maybe 25 columns of different information about customers and their behavior and their background. So yeah, it's amazing.

Oh, that's really cool.

Yeah.

And what kind of Career doors has this program opened for you?

I would say a lot right now. So considering that I'm still in the program and I haven't formally transitioned into a data science or AI specific role, I can already see how this is expanding my path. Right. It's giving me the technical fluency to collaborate more effectively with engineering and data teams. And it's also opened the door for roles that sits at the intersection of product, data and strategy. Roles like AI and data, product manager, AI and data, project manager, machine learning, project lead, or even a data analyst. Right. Or any role that requires a strong AI component. These are positions where a deep understanding of how AI works and how to apply responsibly really matters. Like I said, I can speak the language of AI machine learning, not just from a conceptual level, but through real experience. And I've already started applying some of these skills and how I approach problem solving, decision making, capacity, planning and experimentation in my current role. So while I haven't made a former career switch just yet, this program is definitely positioning me for opportunities that I wouldn't have had access to before and I'm excited to see where it leads.

And was that something in going into the program that you already thought like, these are the kind of roles that I'm looking at, or did the program shape your view of there's things out here that maybe I wasn't considering.

I would say what I had in mind was a fraction of the opportunities that are actually available or you know, that it opens the door for you once you get into this program, it's endless. Right. So I can decide to leave product and delivery and go straight into becoming a machine learning engineer. I can stay in the center of it all where I still get to have, you know, some of that product and delivery work in my day to day activities while still being hands on with those engineers. So it's endless. Right. And as I said, AI is transforming. I actually have plans to pursue another program, but now focusing on natural nlp, natural language processing. But it's definitely to go deeper and deeper and deeper. And my goal is to become a subject matter expert in anything artificial intelligence and machinery. Wow.

Well, I know you're going to get there because you're such a rock star. If anyone's going to do it, it's you.

So much.

Yeah, for sure. And you mentioned a little bit about the fact that you're able to apply what you're learning in the program. Are you able to tell us some kind of project where you've been able to do that in a little more detail.

Well, I was saying decision making. So like I said, a lot, a huge part of my role currently today involves a lot of decision making or even facilitating or driving individuals and teams to make the right decision. So being able to come in with that data mindset, like, okay, let's take a look at the data. Right. And I have, I would say I have like a high mcode relationship with data because sometimes you kind of have to put the number aside and just think from like an EQ perspective, kind of using your basic human knowledge to make decisions. Still having those sentiments, but like I said, being able to still come with data and say, okay, well, these are the patterns that I've observed based on the data that's available. You know, I've been able to apply that in my current role today. And it really, you know, it's giving me that example executive presence that, that I need to excel in my career.

And have you had to shift at all the way that you interact with your team to kind of translate these insights to them? Because you're, you have the advantage of doing the program, but probably your team is not right.

Yeah, yeah. So I would say you don't, you don't necessarily need to be able to translate things to people who are already technical. I think the benefit is now I get to speak and understand their language, but I'm also able to strategically translate it to business professionals who don't have that technical background. The last two projects that I did. So you can either do a high code version where you're just writing code, or you can do a low code version where you're actually writing code, but you're also creating a presentation. I have a work that you're doing and I have my last two already published on my LinkedIn page. And you will see the presentation that I did. If you're a business professional and you look through those presentations, you will be able to understand those technical things that I did with the code. So, so I think it benefits me more because now I can speak and understand the language.

And how has that impacted your relationship with your superiors?

Not at all. I think a lot of them are very excited to hear that. You know, I met someone who said you don't see, see project managers or scrum masters dabbling into the technical side. You do see software engineers switching to those business roles, but you don't see the reverse. And it's very remarkable. So those are the kind of feedback.

That I receive and what part of AI, what advancement in the field Are you most excited about?

Wow. Like I said, I want to become a subject matter expert for anything, machine learning and artificial intelligence. So I'm excited about seeing myself in that position because it's transforming the world today. Right. It's, it's just like cloud engineering. So it's there a lot of opportunities and as you know, not everyone will go with the wave and not everyone will evolve with that, you know, trend. It makes me very competitive, like. Right. So it puts me, it positions me for strength in the transformation that we're experiencing in the world today.

And is there anything that you feel in the program is missing or that you wish that they would add?

I think they definitely need to be more clear about how technical it is. Right. Because like I said, I didn't, I wasn't expecting it to be that technical. But you know, just because of. Challenge myself to, to step outside of my comfort zone and that's how I learned. But not everyone would be like that. Some people would actually come in and be like, no, I was not expecting this. So just more clarity about how technical it is. I think that's the only thing that I would change about this program. I also think this may be my own personal bias feedback. I also think it could be longer to give us time to breathe between the modules. It's like you're finishing with a project and you're starting another one and it's like, oh my God, Joe. It could be longer, you know, less, less, less accelerated.

I know it's an online program and sometimes one of the things that people ask me is in online programs, you know, do you get networking? Do you build community? What's that aspect of the program like?

Yes, I think there are so many opportunities for networking because they have their own platform where they have their alums. They even have on site courts where you, you know, like hackathons and things like that. I didn't opt for this piece of the piece of the program, but if I had paid some additional, some additional fee, I would have been, I would have had the opportunity to, you know, go over there to Texas and then, you know, do some simulation of an on site or in reality type of project. Yeah, those, those opportunities are there. Networking now, you know that networking is, is really dependent on you. Right? They no one's going to force you to network. You have to use the resources that are available to you. So all I can say is the resources are there. Haven't personally had time to do some of that networking because I want to pace myself. I want to Focus on the program. I want to excel. I've been able to maintain really high grades A's throughout. So I know that once I'm done with that, as I transition into the next program that I want to do after this, I'll take a break in between to do some networking with, you know, the folks that I met on this particular program.

Do you do any group work or is it mostly individual projects?

It's mostly individual, but there's opportunities to collaborate. You can work as a team and, you know, try to resolve some of these projects quickly than expected or you get the opportunity to work by yourself.

So, yeah, so now we'll get into the part of the podcast where we'll do our fast pass insights. I'll shoot you some questions. You can just say whatever's at the top of your mind. Okay, so what's one word that you would use to describe the program?

Transformative. Transformative, yeah.

And what's been the hardest AI ML concept to learn?

Say, neural networks, because it took some time for me to wrap my head around how they're structured in intune, so it took a little bit of time for me to. For it to click.

I don't even know what that is, so I'm going to Google it later.

Nice.

And what's one skill that you use that you didn't expect to need?

I would say my time management skills. I would say my business mindset skills. And when I say business, I don't mean entrepreneurial, I mean having that business background. Because having worked in an agile environment, the first thing that comes to mind is how can I add value? Or how does what I'm doing bring value? And because we're solving business problems, when I see a problem statement, I'm thinking, what's the one thing? Or what's the one model? What's the one strategy that will add the most value to the customers? And I think it really shaped the way that I did my project, all of my project. I scored 60 out of 60, maybe one. I scored 58 out of 60, and that was with Python. But that's just because I bring so much insights. Right. So the ability to have that mindset, adding value and being able to recommend solutions from just my experience has been one skill that I didn't expect to use in this. In this program.

What's the best career advice that you would give to people who are looking to make that unusual transition in their career that you're looking to make?

For anyone considering this type of program, I'll say the first thing to know is that it's going to challenge you, but in a good way. Right? So you don't need to come in as an expert, but you need to come in ready and willing to learn. It helps to have a basic understanding of Python, statistics, algebra, or at least be open to learning those as you go. It's also important to be honest with your bandwidth. These programs can be very intense, especially if you're working full time or have other responsibilities. Think about how you make time for it, whether that's carving out a few hours during the week or dedicating your weekends. So for me, like I said, you know, setting aside an hour a day and committing to weekends just helped me not feel overwhelmed. And finally be clear on your goals. Are you trying to switch into a technical role? Are you trying to become data savvy in your current role or you just exploring the space out of curiosity? I think like, like, like everything else, knowing your why will help you stay motivated and choose the right program that aligns with your needs. So, so it's not an easy journey, but it's incredibly rewarding if you're curious, committed and ready to stretch yourself, stretch, it's absolutely worth it.

Take the, take the leap. And I'm so glad you brought that up because a lot of clients we talk to, they say, you know, I want to use the program to figure out what I want to do. And of course there's, there's space to do that, I think, in certain cases. But it's a lot of commitment, it's a lot of time, it's a lot of money, of course. And in an accelerated program like this, it's over before you know it. So there's not as much time to go in and say, okay, you know, I'm going to just figure it out as I go. So I love that advice. And it helps you choose a better program, right?

Yeah. I mean, right now, the one that I'm going to do after this will likely be less technical than this one. But you know, it's, it's a niche that is really hot. Yeah, that's why I want to. It's an AI niche that's really hot. So that's why I want to explore it.

And what's your golden buzzer tip for anyone who is looking into multiple AI and ML programs at the moment?

I would say do it, I would say now is the right time to do it because, I mean, just gotta read articles, you gotta stay, stay with the industry trend this, there's going to be A lot of opportunities that will come out of artificial intelligence and machine learning over the next decade. You want to be on that wave. For sure. We're going to have robots eventually. You need to, if not for anything, understand how these things work and understand at least a little bit at a minimal level, the behind the scenes of how these models are built. So, yeah, yeah, that's what I'd say. There's. You can't go wrong. You can't go wrong exploring, you know, some programs in this. In this field.

Yeah. I have a hard time seeing a place in a career where knowing more about AI is going to be a bad thing. Can't see a boss who's going to be upset about that.

I know, right? I know. And companies now are using Copilot, they're using AI. Right. So I think companies that are leaning more towards that are the ones that are going to be successful over the next couple of years.

And to get to our final round, if someone is thinking about doing this certificate program that you're in right now, what's the one question that they should ask themselves before applying?

Why I'm doing it? Why are you doing it? Like I said, I'm doing mine to position myself as a competitive resource in this transformation. But again, you know that that's my why. Your why may be different. Another why was to challenge myself outside of the norm and outside of my comfort zone, do something that I never thought I would be able to understand. So just know your why. If you know your why, it will be your guiding your North Star right towards your achievements. So. Yeah.

Well, thank you so much. This has been so valuable, especially considering now how many of these programs are just starting. We're really kind of at the. The pioneering phase of these really specialized programs. So these have been amazing insights. Thank you so much.

Thanks, Ellen. Thank you. Of course.

And if you haven't already, check out that other episode that we did with Ebby about balancing all of those things, bouncing, being a parent, working, studying. So make sure that you check that out. We'll leave the link in the description below.

Awesome.

So. And if you're looking at applying to a program like this or to any other program, check out our website, Ellen Lawless.com to learn more about working with us.

Yeah, I do want to say that Ellen is such an amazing person. Like I said when I was on my MBA journey, it's just the strategies that she uses to help you navigate the process. To me, it was transformational. Like I said, I learned a lot about myself. I saw that I had truly really accomplished a lot in my career. I was underesting myself until I spoke to Ellen and she was like, what are your accomplishments? What are your goals and finding your why? And I think if anything, it's always worth it to have that support as you navigate. It's a huge decision. I ended up not going that route, but I do not, I have no regrets, have no regrets hiring your services for that, for that process. And definitely, you know, if, you know, I still do consider doing my mba, but one that fits my lifestyle, maybe an online mba. And you will be the first person that I will call when I'm ready for that.

Please do. It was such a pleasure to work with you and thank you so much. That means a lot to me to hear.

Awesome. Awesome. Thank you. Thanks. All right, bye.