Original Post in LinkedIn Hello all, I have been reflecting a lot while preparing the next semester. AI skills are rising fast among students. But deep hands-on data engineering skills are decreasing. And that worries me. So I decided to change the way I teach Big Data. This year I will teach: • One program in English (39 students) • One program in Spanish (17 students) Same approach but evolving the structure significantly. As I mentioned before there is a clear trend: Students are becoming increasingly AI-proficient… but less hands-on in core data engineering and platform fundamentals. So I redesigned the course. The structure now includes: • 18 hours of theory • 14 hours of guided hands-on lab • 8 hours of stand-ups (individual Big Data topics + group final use case presentation) But the real shift is deeper. The lab is no longer tool-driven. It is architecture-driven. Students will learn by doing: – Agile SAFe methodology – GitHub & GitHub Organizations – Terraform (Infr...
Data Platform Architecture & AI Engineering
Essays, architecture insights and reflections on data, AI and society