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. 🙌

This course delivered everything it promised, a hands-on, real-time project build where you can learn many details about how to develop real-world machine learning projects. Right now, I feel much more confident about the technologies and techniques I need to use to build my own project. One of the things Pau always tells us is to try building our own projects and not to be afraid of failure. That’s when real learning happens. I would 100% recommend this course to anyone wanting to learn how to build real-world machine learning projects

The most under-priced Cohort I ever took part in ;-) And also the one i learned the most of the things new to me (DevOps, MLOps) The practical approach and real life experience of Pau and Marius were invaluable.

I have taken three Cohorts of Real-time Building ML with Pau and I think the content is terrific. I happened to have current working knowledge on many technologies he covers like microservices, pipelines tooling but with Pau one learns new things every single time. I love his zest for integrating AI ways of working with code bases. White many courses on the subject matter stick to Notebooks and some framework, Pau's "real time ML.for real engineering" approach is the best way to learn.

This has been the second time I took the Real Time ML System course taught by Pau. It has been an absolute pleasure (again!). Pau, and this time also Marius, keep improving the course and I must say that I learned sooo much during the past two cohorts. Given the completion of the previous cohort, I could really focus on learning Kubernetes and learn more about production-ready setups this time. I am more than certain that following Pau's teaching provided me with that extra bit of skills to land my new job as a Quantitative Developer.

Prior to starting the course I was skeptical whether the money would be worth it. I reached out to Pau and he immediately replied, explaining the course and answering my questions (without pushing me to buy the course!!). I decided to get the course and I am more than happy that I did. It's very fun to follow the course and Pau's teaching. Also, it immediately helped me with my work. I was able to apply it to a new project working with LLMs. Thanks Pau. Note: Over the holidays I had a look at the Rust course and I am seriously considering following that course, as well!

Pau courses are the best learning experiences I have ever had. He shares everything, no tricks, real-world machine learning, up to date and beyond, professional level, with great humour and hard work. Be prepared to type and learn more than you ever imagined. I will do it again and again! No joking; just do it!

This course contains a real-world example with clean code and explanations to help you build and get experience with real-world, end-to-end ML applications. The teacher is confident and knows how to explain complex concepts, so I recommend this course!

After learning from Pau, my ML skills improved dramatically. Truly, it feels like the BEST course I’ve ever taken. We learned together as Pau guided us step by step. Plus, with a one-time payment, we can continue learning—it’s incredibly helpful!

The RWML course by Pau is an excellent, no-nonsense, hands-on program that emphasizes a pragmatic, pipeline-driven approach to building real-world machine learning systems from the ground up. The course covers the entire lifecycle, from raw data processing to model training and serving predictions. Throughout the journey, Pau skillfully demonstrates the application of modern tools to create fast, reliable, and efficient systems.

This course covers all aspects of an ML project, following the FTI (Feature, Training, and Inference) pipeline architecture. Pau guides you through live coding sessions to build a project from scratch, progressing all the way to deployment and monitoring. You'll work with streaming platforms like Redpanda and Quix, create various containerized microservices, push them to a centralized Hopsworks feature store, train and register your model in Comet ML for inference, and monitor it on ElasticSearch/Kibana. Additionally, during the cohort, an LLM model is fine-tuned using project data to enhance the features. All of this is done following the best DevOps practices. Developing a project while gaining expert insights and learning best practices from industry leaders like Pau is an invaluable experience, regardless of your expertise level in deploying models to production. Highly recommended!

As someone who has been in the analytics profession for the last five years, this course exceeded my expectations in so many ways. Throughout the five week course, we were able to (1) create feature, training, and inference pipelines (2) Docker-ize those pipelines and deploy them locally as microservices, and (3) push and run those microservices on cloud. We got our hands dirty with realtime data (websockets, Kafka, Redpandas), feature stores (Hopsworks), model registries (Comet ML), dashboards (Streamlit), and deployment (REST API, Quix Cloud). Pau is an expert engineer and an even better teacher. The course was conducted completely live so we got to see what goes on behind the scenes in a professional machine learning environment, including debugging and going through documentation. As an analytics professional used to Jupyter Notebooks, this course was an eye-opener. It encouraged me to rethink my coding practices, especially how I organize, package, and deploy my code. I've already begun to apply some of my learnings to my work. After going through the course, I'm confident that I can build an end-to-end ML product. Could not recommend this more.

I walked into this course thinking I'd just pick up a few practical skills, but came out with so much more. I found a community, levelled up my toolkit and left with that 'Hey, I actually know what I'm doing' kind of confidence. Pau's hands-on approach to building a real-time ML project with MLOps best practices? Total game-changer. Not only is Pau actively involved, but he makes even the most complex topics easy to understand, thanks to his clear diagrams and real-world insights that make everything click. And let's be honest, those live debugging sessions? They felt like epic co-op missions. There’s nothing that brings a group together quite like staring at your screen, questioning reality, and collectively wondering if the code has developed a sense of humour just to mess with us. This isn't just a course; it's a shared adventure where everyone is committed to helping each other succeed. If you're ready to embark on your ML journey, push your limits and be part of a growing community that's all about learning and levelling up together—then this is exactly where your ML journey should begin.

Great training, intense but "Nothing is so painful to the human mind as a great and sudden change.” (Mary Shelley)

After completing the Building a Real-Time ML System Together course with Pau, I feel fully equipped to build my first real-world ML service! The hands-on experience of designing data processing pipelines, fine-tuning a LightGBM regressor, and leveraging tools like Hopsworks, Comet ML, and GitHub Actions was invaluable. The course covered all aspects of MLOps, from automated data pipelines to real-time model performance monitoring, giving me the confidence to apply these skills in real-world scenarios. I would definitely recommend this course to any aspiring Machine Learning Engineer or any data scientist who wants to take their skills to the next level.

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 course is amazing and every concept is explained clearly. It makes one ready for the real world problem, one can feel how actually production ready ML is done. Worth the money.

I have attended many online and in-class courses and academies for the last 6 years but none come close to the Pau's work. His lectures are on the edge of ML system development and are based on industry's best practices. In terms of pedagogy, he is no less than a Gold Standard. I recommend his courses to all ambitious learners. You'll never regret it.

I like the course for the practical application of real world machine learning in the course. Pau, does a great job on teaching through a real example, that you can use in production., to teach the concepts, the methods and the real world troubleshooting that any engineer needs to learn. I like Pau's generosity in sharing his knowledge and his tenacity and motivation to surmount the issues and obstacles in learning. He is very balanced in taking short-cuts where needed and where an elaborate deep-dive is needed. Loving every moment of the interactions in the sessions and in discord. The community is really international, very vibrant and diverse. The course is more than worth the tuition fee and the time one invests in learning from the course.