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Graduating from a Nanodegree program is no small feat and definitely an accomplishment worth celebrating. One of our students, David Hundley, has recently graduated from his 10th Nanodegree program, and is now working on his 11th!

Machine Learning Engineer Student Story

In just over a year, he was able to use the skills he learned across different Nanodegree Programs to transition into a Machine Learning Engineer role. Here’s David’s story:

Tell us a little about yourself.

I’m David Hundley, and I live in Illinois. I had been working in business-oriented roles for about 8 years, but I always had an inclination towards technical learning. My wife happened to put me in contact with a friend who was the Head of Data Science at my company. He gave me a good curriculum to work through, but a lot of it was just books and random MOOCs. While he gave me a good starting base of things to consider learning for a Data Science path, it didn’t best suit my learning style. So, I did a little research online and found Udacity Nanodegree Programs. I started about 18 months ago, and they’ve helped me to increase my skills over time. The projects helped me to grow my portfolio, and in January of this year, I entered a Machine Learning Engineer role at my company as a result of the Nanodegree Programs I’ve taken.

What made you decide to learn with Udacity?

I’ve tried some one-off courses from other platforms, but the main reason I stuck with Udacity is the structure and consistency it provided. Other platforms can be really nice if you just want a one-off course. However, they typically don’t provide a good sequence in which you should take the courses for a certain goal. With Udacity, I can explore different learning paths and get an idea of which programs are beginner, intermediate, and advanced, which was very helpful. 

In addition, compared to other platforms, Udacity’s content seemed nicely tailored. Other platforms offered way too many videos and no projects, or way too many projects and no videos. Udacity has struck the right balance where there’s a good amount of projects and videos that don’t go any longer than 3-5 minutes.

How would you describe your background experience before taking your first Nanodegree Program?

I started with AI Programming with Python. I didn’t necessarily have a prior background before I started this Nanodegree Program. I came right out of undergrad to work at my current company. I was a help desk specialist at my university, where I did general hardware debugging. I also worked as an audiovisual specialist for some time. As far as programming goes, I had some Java experience way back when, but coming into my first Nanodegree Program, I would say I didn’t have prior experience at all. 

You started with AI Programming with Python but also ended up taking the Machine Learning Nanodegree later to become a Machine Learning Engineer. What made you decide to make the switch from the Data Science learning path to Artificial Intelligence?

I personally don’t see the two as being all that different. I’ve taken Nanodegree Programs under both Data Science and Machine Learning, and though they have differences in content, I find the two fields to have a lot of overlap. The Machine Learning Engineer role is a new one for many companies, including for my own company. When I started my learning track, the Machine Learning Engineer role didn’t exist. Now that it does, we have distinct responsibilities from data scientists but partner very closely together on the same projects. It’ll be interesting to see how this role across every industry will continue to evolve!

“As technology continues to evolve, I’m certain that Udacity will help me continue to learn new, relevant skills I can apply in my current position.”

When did you feel comfortable enough to switch to a Machine Learning Engineer role?

I switched over to this Machine Learning Engineer role in January 2020. I probably would say I felt comfortable with my skills to make the switch one year after I started taking Udacity Nanodegree Programs, after I graduated from the Data Analyst and the Introduction to Machine Learning with PyTorch. By that point, I had also completed about five Nanodegree Programs in total, but I would say Data Analyst and Intro to Machine Learning propelled me the most to pursue the role that I have today and were the two most pivotal for my own personal knowledge.

When transitioning from a business role to a technical role, how well did the Udacity Nanodegree programs prepare you for the work that you’re doing in your current job?

That’s tough to answer because I do think Udacity did prepare me in a big way in both Data Science and Machine Learning. The struggle for me personally came when I had to start applying these concepts in a real business capacity. Every company is going to apply these concepts in their own way. A start up, for example, is most likely going to have a very different infrastructure than a well-established company. 

Fortunately, it wasn’t an overly difficult integration as Udacity taught me most of the skills I apply on a day-to-day basis. As technology continues to evolve, I’m certain that Udacity will help me continue to learn new, relevant skills I can apply in my current position.

What’s your strategy? 

I’m a very regimented person. I wake up at the same time every morning, work out, go to work, come home. I have two little girls, and I play with them until they go to bed at about 7 pm. Then, I’ll work on my Nanodegree Program until I go to bed at about 9 pm. Every day isn’t the same, of course. I’m a little bit crazy in that I probably do more than what anyone else would expect me to. Part of that is just because it’s a lot of fun for me. 

The latest Nanodegree Program I completed was Deep Learning. Especially in this time when we have quarantine and bad weather in Illinois, there’s nothing to do outside, so it’s either video games or Nanodegree Program!

How do you stay motivated?

For me, paying for these Nanodegree Programs out of pocket gives me an incentive, because if I don’t complete them within a certain timeframe, then it’s my money on the line. I’m motivated because I’m investing in my learning, and all the Nanodegree Programs I’ve taken have already paid themselves off. Of course, there are some days that I’m not motivated. When that happens, I don’t try to fight it. I will just accept that I will lose a few days here and there, and I’ll start fresh and ready to learn the next day. 

Do you have a favorite Nanodegree Program, or a project that you’re particularly proud of?

My favorite is probably the Data Analyst Nanodegree Program. It pushed me the furthest. It covered a lot of ground really well, too. It really helped to serve as a great foundation for other subsequent Data Science, Machine Learning, and Artificial Intelligence Nanodegree Programs I’ve taken since.

The project I’m most proud of is the Dog Breed Classifier from Machine Learning Engineer. It was really cool to build your own neural network, and use transfer learning to apply these other architectures that have already been built out. It asks you to toss in pictures of both dogs and humans. I tossed in pictures of my daughters to see what kind of dog they would most look like. That was a fun project; that’s probably my favorite. 

Are you currently enrolled in any Nanodegree Programs?

Yes, I’m taking advantage of the one-month free access offer. I’m enrolled in Programming for Data Science with R. To date, I haven’t had to work with R, but I know my company has a couple of data scientists working with R. I want to make sure that I’m prepared if I get an assignment where I have to use it. Even though I’m now a Machine Learning Engineer because of Udacity, my studies definitely aren’t done. I plan to continue to pursue other Nanodegree Programs from Udacity. 

Congratulations on your achievement, David, and best of luck in your Programming for Data Science with R Nanodegree Program.

If you’re a lifelong learner who wants to gain the skills you need to land the job you want and build the career you deserve, check out our Nanodegree Programs!

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