
Wall of love for Real-World ML by Pau Labarta Bajo
Participating in the RWML cohort was a transformative experience for me. The hands-on knowledge, real-world insights, and supportive community played a key role in helping me take the next step in my AI journey. Thanks to what I learned, I was recently accepted into AGI Club — a highly selective community in Brazil that connects AI professionals with global leaders like Anthropic, OpenAI, and Google. The RWML program didn’t just deepen my technical skills — it opened doors. I'm incredibly grateful for everything Pau Labarta Bajo and the team shared during the cohort. It was truly a game-changer for my career. 🙌
Participating in the RWML cohort was a transformative experience for me. The hands-on knowledge, real-world insights, and supportive community played a key role in helping me take the next step in my AI journey. Thanks to what I learned, I was recently accepted into AGI Club — a highly selective community in Brazil that connects AI professionals with global leaders like Anthropic, OpenAI, and Google. The RWML program didn’t just deepen my technical skills — it opened doors. I'm incredibly grateful for everything Pau Labarta Bajo and the team shared during the cohort. It was truly a game-changer for my career. 🙌
🤖 Senior Full Stack Machine Learning Engineer • MLOps • Contractor • Freelancer ~ Engineering production-ready machine learning systems.
Machine Learning Researcher | MSc. in AI Uni Freiburg
I am in the middle of the Building a Real-Time ML System Together course with Pau and I am loving it! The format is refreshing, it actually bolsters active learning and problem-solving as opposed to passively copying code and not thinking through the design. The live coding is one of my favourite parts; we get to code alongside Pau and understand not just what each script does but also how to think about the algorithms and system design. And, like any coding session, there’s bugs! I love the debugging, that's when you really get to learn how things work. Having bugs happen in the live coding sessions, going through error messages, and fixing them, teaches a lot about what one might encounter and how to solve it, while also providing insight into the workings of the system. I got to learn some Python syntax tricks and DevOps tricks I was not aware of. Finally, an invaluable thing is that we get hands-on experience with many tools - like docker, redpanda, cometML, etc - which, if you're not exposed to them through your work already, can seem like a gnarly mess to untangle. By building the system together we get to understand how these tools work together. I highly recommend this course to anyone wanting to break into ML engineering. I feel like after completing this course I will not only be able to built my first real-world ML service, but also have some neat new tools under my belt.
I am in the middle of the Building a Real-Time ML System Together course with Pau and I am loving it! The format is refreshing, it actually bolsters active learning and problem-solving as opposed to passively copying code and not thinking through the design. The live coding is one of my favourite parts; we get to code alongside Pau and understand not just what each script does but also how to think about the algorithms and system design. And, like any coding session, there’s bugs! I love the debugging, that's when you really get to learn how things work. Having bugs happen in the live coding sessions, going through error messages, and fixing them, teaches a lot about what one might encounter and how to solve it, while also providing insight into the workings of the system. I got to learn some Python syntax tricks and DevOps tricks I was not aware of. Finally, an invaluable thing is that we get hands-on experience with many tools - like docker, redpanda, cometML, etc - which, if you're not exposed to them through your work already, can seem like a gnarly mess to untangle. By building the system together we get to understand how these tools work together. I highly recommend this course to anyone wanting to break into ML engineering. I feel like after completing this course I will not only be able to built my first real-world ML service, but also have some neat new tools under my belt.
The Full-stack Freelancer
AI Research Engineer at DyCare
Lead AI Engineer at Nuevozen
Prime Therapeutics | Big Data cloud infrastructure MLOPS
ML/Data Engineering @ Kite Financial
Founder @ Onsanity, Innex, SmartDelphi & Associate Professor @ Universitat Politècnica de Catalunya
SVP Decision Sciences, Profitability and Strategic Analytics at Santander Consumer USA
Seeking Entry-Level Opportunity in Machine Learning / Data Science for Career Change
Aspiring Data Scientist/ML Professional | Pursuing MS in Data Science | Previously - Technology Agnostic Leader focussed on delivering Development and Infrastructure Projects using Agile | Mainframe | SAFe | Db2 for z/OS
