Earn While You Learn AI: Nick’s Experience in Flatiron School’s Apprenticeship Program

When Nick Driver decided to pivot into AI and data science, he didn’t want to just learn theory – he wanted real experience. That’s what drew him to Flatiron School’s Work-Integrated Immersive, where students split their time between coursework and a paid apprenticeship. In this interview, Nick walks us through what it’s actually like to “earn while you learn,” from working on an education app to building practical AI skills each week.

What made you want to move into tech, specifically AI & data science?

I graduated with a computer science degree in 2021 from the University of South Carolina. After that, I started a mobile laser tag business and ran that for a few years, along with doing some freelance work on the side, such as building websites for local businesses.

For as long as I can remember, I've always had a love for tech and specifically software.  From about the age of seven, I started playing around with HTML and making small games in Game Maker. As for AI and data science, I think like most people, it was the initial release of ChatGPT that made me realize that that was the direction the whole industry would be heading in.

What stood out about Flatiron School's work-study apprenticeship model?

At the time, I was applying to other positions, but I learned about Flatiron School's apprenticeship program through a neighbor. The apprenticeship seemed like the perfect fit. I loved that this model would allow me to work using existing skills while I’m also learning new, in-demand skills, such as data science and AI.

Are you in the Accelerated track? How were you placed? 

Yes, I'm in the accelerated track because I have some software engineering experience. The accelerated track is 14-months long. There’s also a track for beginners that includes four additional months in Flatiron School's software engineering certificate program first to get you up to speed. Then in Month 5, you start the paid apprenticeship.

The program is marketed as “earn while you learn with net-zero tuition.” So how does that work?

Yes, the program is split into 20 hours of learning and 20 hours of work weekly. The work portion covers the cost of learning, resulting in net-zero tuition. 

What’s your goal at the end of the 14 months?

I'm nearing month four of the 14-month program. So I'm really just getting started, even though it feels like I've already learned more in this short amount of time than I did going through years of undergrad.

I'm most excited about being placed with an employer partner. I have not started working with an employer partner yet, but that's in motion and the transition should happen very soon. After hearing several names of potential employers, I am very excited for it to get underway. 

And I’m excited to dive deep into a lot of the AI topics in the curriculum – machine learning, LLMs, natural language processing, etc. 

To me, success would be graduating and feeling prepared to land a full-time position in data science and AI.

What does a typical week look like for you right now? Does it actually feel manageable to balance 20 hours of learning and 20 hours of work each week?

On the learning side, I typically work my way through the course modules, which include reading material, video lectures, practice exercises, quizzes, and labs, and meet with my mentor once a week. On the work side, I collaborate with my team to plan tasks, work on those tasks, code review, and meet twice a week with my entire apprenticeship cohort. 

I am also fortunate to be able to go in-person to the nearby office several times a week, where I meet up with a few of the other apprentices and volunteer at the free coding classes hosted by Bletchley. They are open to the public, primarily designed to introduce coding to high school students. 

It does feel manageable to balance. There was certainly an adjustment period at first, but after a couple of weeks, it didn't feel difficult at all to manage.

What technical skills are you learning right now? How is this different from just taking an online course on your own?

The biggest difference from just taking an online course is that as I learn a new skill, I am then able to go and immediately apply that skill in real world applications. Some of the skills I've been learning include contributing to production code bases, collaborating with teams to complete user stories, the code review process, analyzing, cleaning, visualizing, and discovering patterns in large data sets. 

From day one, I was working on an application that interfaces with large language models. And thus far, I've learned foundational data science concepts and skills, such as Python programming, working with data sets, and SQL. The upcoming months will cover AI concepts, including generative AI, regression, machine learning, and neural networks.

Can you share an example of a real problem you've worked on during the apprenticeship at Agreeable Data? 

Flatiron connected me with John from Agreeable Data. We're doing consulting work for an orthodontist office and figuring out how to automate more of their scheduling. Right now, it's all over the phone for every single appointment. The other day, they got over 130 calls in a single day. I was there yesterday for a couple hours just shadowing the people that take the phone calls. Their scheduling is very complicated. They have at least 50 different appointment types, and there's a different code for each one with its own set duration. I think John's plan is to set up Codex (OpenAI’s Codex) on a machine in one of their offices. Codex now has computer vision use built into it, so we're going to try to have it physically do all the scheduling that a person would normally do. That will be a basic prototype to see what's possible.

How closely related is your apprenticeship work to what you're learning in the Flatiron curriculum?

My coursework is focused on cleaning data sets, like finding duplicates and then extracting out important information from them and business objectives. I would say that applies most directly to some part-time work I'm doing as an IT Lead at a bike park and climbing gym. They'll frequently want to run sales on different products. In order to push those sales, they want me to pull out a data set of customers (e.g. only customers that have purchased something bike-related like a bike-only membership or bike gear). So, we pull out all of that raw data and then run some Python scripts against it to check for duplicates and missing values, stuff like that. That's a lot of what the coursework has focused on so far, so that's coming in handy!

Do you feel this experience gives you a competitive edge over someone who only completed a traditional certificate program?

Yes, well I think it already has! I've gotten so many opportunities in the past few months. 

I would say that if you are someone that is passionate about software, data science, and AI, then this is a program that really sets you up for success in a career and field that is evolving faster than ever.

Find out more and read Flatiron School reviews on Course Report. This interview was produced by the Course Report team in partnership with Flatiron School.