Back to University: Applied AI Engineering
Why I decided to return to university after 13 years of tech experience to study Applied Artificial Intelligence Engineering.
For some of you this might be news, but for me it's been over a month already. Am I late to share it?
The big news is: I am back at university! 🎓
For over a year, I have been asking myself deep career questions: How do I elevate my professional baseline? What is the best way to showcase my technical capabilities and engineering maturity to the market?
As I shared in this post, sharing more on networks like LinkedIn to showcase real-world projects and daily workflows is great for showing "who I am". But what about technical foundations? How do I validate and deepen the foundation built over the years?
The New Challenge: Postgraduate Degree
I decided to pursue a new academic degree to consolidate over 13 years of practical experience in technology.
Currently, I am pursuing a postgraduate degree in Applied AI Engineering at UNIPDS. I am dedicating myself fully, not just for a title, but with the genuine goal of contributing to an active learning community that goes far beyond a traditional course.
Over the coming year, my focus will be on building deep practical skills in Artificial Intelligence. And best of all: I am actively participating as a Student Ambassador, helping peers, answering technical questions, and fostering rich knowledge sharing among students.
💡 Insight: Returning to formal academic education doesn't replace real-world experience, but it provides a structured foundation for mastering complex domain areas like Artificial Intelligence.
Academic Degree vs. Online Courses?
This is one of those topics that always sparks debate. What holds more value: a formal academic degree or five certificates from quick online courses?
| Criterion | Academic Degree (Postgraduate) | Short Online Courses |
|---|---|---|
| Depth | Structured, deep theoretical and practical immersion | Direct focus on fast skills and specific tools |
| Networking | Strong (continuous interaction with professors, community, and peers) | Generally limited or asynchronous |
| Validation | Formal recognition endorsed by educational institutions | Fast validation, ideal for short-term trends |
⚠️ Reflection: In my view, both are valid and essential. However, for those who believe software engineering no longer requires academic updating, or that degrees carry no weight... the question remains: is that really true?
Who are your technical role models today? Do they rely solely on quick tutorials, or do they also possess a solid formal grounding? I believe combining both — true Lifelong Learning — is the real differentiator for long-lasting engineering careers.
Food for thought 🤔