Driven to Learn: A Conversation with Pablo Marino
Some folks are just born to work in tech. Pablo Marino is one of those people. Growing up in Argentina, he developed an interest in digital technology at an early age, taking apart computers, video game systems, phones — you name it — to understand how they worked and how they might be improved.
The decision to study programming at university came naturally, but Pablo’s interests went beyond the material covered in his core classes. He supplemented his university curriculum with online courses, and it wasn’t long before Pablo began working on his own tech projects in his spare time: developing video games, building chatbots and creating mobile apps.
Pablo’s college career was cut short when financial constraints pushed him to join the workforce before graduation. After landing his first job as a software engineer in Buenos Aires, he focused on honing his tech chops and developing his own passion projects. When an opportunity to work in Silicon Valley came up, Pablo was ready to head north, taking a position with a San Francisco-based tech startup.
Throughout his entire academic and professional career, Pablo has been driven to seek new challenges as well as opportunities to learn about cutting-edge technologies. Artificial intelligence (AI) and machine learning, in particular, grabbed his attention.
Pablo’s thirst for knowledge would eventually lead him to Stanford’s online Artificial Intelligence professional program.
"Across the board, the AI program operated at a higher level than other online courses I’ve taken."
What motivated you to enroll in Stanford’s AI professional program?
I got my first taste of machine learning a couple of years ago when I enrolled in Andrew Ng’s machine learning MOOC. From then on, I took every chance I got to learn more about the technology. Then, about a year ago when the pandemic started, I started feeling a little restless in my job. I needed a change, and with my passion for all things related to machine learning, it made sense to shift my career in that direction.
It was kind of a leap of faith, but I decided to take a 6-month sabbatical to throw myself into AI and machine learning while also working to finish my undergraduate degree.
Stanford’s AI program didn’t really exist at that time — at least not in its current state. I had received an email the year before, announcing a new online course in natural language processing (NLP) and deep learning. When I took a closer look at the curriculum, it was everything I wanted to know. You couldn’t find those concepts covered anywhere else. It was so unique, and it fit my interests perfectly. So, I signed up.
What were your goals when you enrolled in the program?
Initially, I just wanted to learn more about AI and machine learning. It wasn’t until the first course started winding down that Steve Haraguchi, the program manager, announced that Stanford was developing a professional certificate program in AI. I had such a great experience with that first class, and I wanted to develop a deeper understanding of machine learning, so I decided to keep taking courses and earn the certificate.
What did you enjoy most about the AI program?
The material covered was important, of course, but I also really appreciated how concepts were incorporated into the coursework. Most of the information and online courses I had found before enrolling in the Stanford program talked about implementing algorithms, but not how you actually go about developing algorithms.
The Stanford courses looked under the hood of AI and machine learning to teach you how these concepts work at a mathematical level. You’re given the tools to understand state-of-the-art AI beyond use cases and applications and really get a sense of how this technology functions. It’s clear that program designers and instructors put a lot of thought into the curriculum. The lessons and projects we covered were so interesting and novel.
The instructors were amazing as well, especially Professor Christopher Potts. He taught the Natural Language Understanding course and was always really engaged with students, joining Slack groups and answering any questions we had. Those Slack sessions were a great way to collaborate with other students all over the world. I worked on projects with people from Latin America, Australia — all over the place.
How did your Stanford experience compare with other online courses?
Across the board, the AI program operated at a higher level than other online courses I’ve taken. For one, there’s no guarantee that you’re going to pass; you have to put in the work. With other courses, all you really need to do is pay the course fee. Stanford’s online program expects much more from its students. Every assignment is graded, and each course is conducted like an on-campus college class. If you don’t make the time to study and complete your assignments, you may not earn the certificate at the end of the course.
I certainly ran into my own trouble spots with the coursework. The Machine Learning course was especially difficult because of the heavy focus on mathematics. There were a lot of proofs and derivatives to go over. I’m an engineer at heart, not a mathematician, so I had to work extra hard to get projects done the right way. But it was totally worth it. I came out of the course with a deeper appreciation for that aspect of the technology and even felt like I had a better handle on how to read dense research materials.
How has the program helped you achieve your professional goals?
After my sabbatical, I had a clearer view of where I wanted to take my career. Instead of returning to my old job, I decided to become an independent consultant and data scientist focusing on NLP, AI and machine learning. The concepts I learned from Stanford’s program have been invaluable to my professional work. In fact, a lot of the technology we worked with in the courses are the same platforms my clients typically use.
I actually landed my first consulting gigs because of the knowledge I gained through the coursework. Having a professional certificate from Stanford really helped me sell myself to prospective clients, as well.
The program has been very helpful for networking too. A lot of the other students either worked for big tech companies like Apple, Google and Microsoft or were launching their own startups. I still keep in touch with people, and in my line of work, it’s great to have those connections.
What would you say to someone who was thinking about applying to the program?
Consider what your professional goals are beforehand. The program is designed for scientists, researchers and engineers who want to develop a deeper understanding of AI algorithms and their inner workings.
Also, be sure you can give yourself enough time to focus on your coursework. Depending on the difficulty of a particular lesson or assignment, I spent anywhere from 10 to 50 hours a week on my classes. If you want to take advantage of the program you will definitely need to work hard, but it’s totally worth the effort.
Pablo’s drive to learn has powered his career to new heights. If you share Pablo’s thirst for knowledge and are interested in a career in AI, consider Stanford’s professional AI program.