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.

Quickly after completing this tutorial I was able to build my own ML system a "stock price prediction service". Prior to this course I was wondering how i can take my ML projects to the next level, I was looking to create a more professional project for my resume but I had no vision on how to start. This course forced to look outside the scope of the standard train a model on a dataset. It expanded my thinking to see how I can use ML to make a meaningful impact on a business in the real world. My favorite thing about the course is the diagrams and how it makes it easy to understand a process. Coming into this course I only had technical knowledge on ML models and not how to use them in the real-world, this course aided me to leverage my skills to impact in the real-world. Whether you are new to ML or have some expertise this course has something we can all learn from.

Second course I'm taking with Pau and it's absolutely another gem! The real-time ML course guides you from opening the code editor for the first time to literally building an end to end serverless real-time project. Alongside the course you learn a wealth of skills related to real time serverless machine learning, and a lot of other "secondary skills" such as: debugging code, polishing your python skills, and some DevOps best practices among the others. Pau is also always available to answer students' questions about the course and every week he offers office hours to make sure he's leaving noone behind. After the first course with Pau, the expectations were high for this one, and he didn't disappoint, but rather surprised me with a lot of new knowledge and his expertise in the field. Don't bother if you can't make it to the live sessions, since both coding sessions and office hours are always recorded! I would definitely recommend the course to everyone looking to level up their ML game, since I'm now more than confident in building real-time ML projects and had previously little to no knowledge about managing thousands of incoming data points every minute. Can't wait for the next course!

This was no doubt one of the finest course I've ever enrolled to. Understand, as a graduate student in University, this course was a blessing to attend. I am able to dirty my hands in this process of building a "real-time" ML system which till now I have just read in books/blogs. Plus, given a fact that this is a way things are implemented in the industry is a massive add-on. Masterclass!

I recently completed the-real-world-ml-tutorial by Pau Labarta Bajo, and it was an outstanding experience from start to finish. The course was exactly what I needed to get hands-on experience on building end-to-end Machine Learning systems. The Course walks you every step of the way, from creating to testing and final deployment of your application. The live code sessions made a huge difference. Being able to code and debug in real-time alongside Pau was invaluable. Furthermore, the additional resources and support offered by Pau went above and beyond my expectations. Whether it was through prompt responses to questions, detailed explanations, or additional study materials, Pau ensured that every student was well-supported. I highly recommend this course to anyone looking to deepen their ML expertise with real-time applications.

Pau's course is the real deal. I have taken part in numerous courses and training sessions in the past, including 2 degrees (computer science and data science) and Pau is easily chilling with the best ones out there at the top. Not only are the sessions designed to take the student through the whole end-to-end journey to deliver a working product, but the training style closely mirrors an actual development journey with all the highlights and pitfalls. Unlike many trainers and content creators, Pau' doesn't hide behind pristinely prepared copy and paste code, he shows you the actual process when it often feels like you take two steps forward and one step back each time you move. The learnings from the troubleshooting and debugging are perhaps even more valuable than the ones you get from the code that works from the get go. Having a template that you can copy and paste in your own project at the end of the course is sure nice, but learning what to do when things don't go as planned and how to think on your feet - that's the real gold!

I recently completed a comprehensive Machine Learning development class, which provided me with invaluable knowledge and hands-on experience in the entire process of developing one Machine Learning model. This included integrating the model locally with Kafka broker, Hopsworks Feature-Store, and Comet ML, and deploying it seamlessly into Quix Cloud. The course was meticulously designed to cover all aspects of the development process, and the practical sessions helped me solidify my understanding of these advanced tools and techniques. I particularly appreciate and respect Pau's integrity and commitment to delivering on the course scope. His dedication was evident as he went above and beyond, creating additional sessions to ensure all promises were fulfilled and all concepts were thoroughly covered. Overall, this class has enhanced my skills and confidence in Machine Learning development and deployment. I highly recommend it to anyone looking to deepen their expertise in this field.

This course by Pau Bajo is unique in its nature, providing the kind of content that is not found on other platforms. Pau basically creates an end-to-end ML system live, showing you the best MLOps practices, little tips & tricks, and clarifying your queries there and then as he codes. I learnt to use a lot of new Python libraries and frameworks in this course, what it takes to build a production-ready ML system, plus had all my queries big and small answered by an experienced ML engineer like Pau. Last but not the least, Pau is an individual with a lot of personal integrity, which reflected in how he conducted the course. It was not about just finishing the course, but about ensuring that he showed real-world ML concepts in the course, even if it meant him spending extra time over the weeks. I recommend this course whole-heartedly.

Like many people, I started by doing data preprocessing and model building in Jupyter notebooks. I had never attempted to use live, real-world data that is subject to updates. I had a surface level understanding of what good code looked like from my basic knowledge of Python, but I had very little exposure to machine learning code of a professional standard. I started following Pau's work 6 months ago. I took his Real World ML course, joined his Discord server, and followed his projects on Github. I along with several others in his Discord community, also benefited from Pau's help with issues that we encountered while working on our own machine learning projects. All of this assistance that I have received from Pau (both direct, and indirect) has culminated in the following significant improvements to my work: - I have adopted an interest in the whole machine learning lifecycle, including model deployment and monitoring. - I have gained the confidence to get to work on my own projects independently. - I have made the crucial transition from relying on jupyter notebooks to being able to write clean, maintainable, and scalable code in the form of scripts which execute each stage of the machine learning development process. I would thoroughly recommend Pau as a major source of help, guidance, and inspiration to any aspiring machine learning engineer or data scientist.

The tutorial goes into great depth of how to build a real-world ML system. Pau's breakdowns of complex topics made it extremely easy to follow along, and it was totally worth the money. Extremely great course, I totally recommend it for anyone who wants a hands-on approach to learn how to build a real-world ML application.

Very rarely do you come across an online tutorial that gives you a flavor of what it takes to build a productionized ML model. I highly recommend this course to anyone who is remotely interested in implementing an ML project right from business problem formulation all the way to deploying it as a WebApp and understand the careful decision making which goes into making this a reliable, effective and efficient system. I look forward to more such tutorials from Pau in the future. Great Job!

This course offers a solid foundation for an end-to-end ML project that you can reuse in your personal portfolio It teaches MLOps best practices and modular architecture, providing you the skillset to facilitate a good collaboration with the engineering team. For example, you'll utilize feature stores, structure your project with maintainable code, and more.

Hands down, this has been on of the best course I've taken. It's the closet you'll get to a real world project and navigating throught the different phases of MLOPs.

The course is amazing, and Pau is such a great teacher. Everything is covered in detail, and knowledge is gradually distilled to ensure that the student never feels left behind at any point during the course. Another excellent aspect of the course is that it teaches technical topics in a practical-oriented way, making the learning curve more gradual and concrete. As a result, students will feel more than ready and confident in building their first project right after completing the course. I would highly recommend this course to anyone looking to take a step further in their machine learning journey and acquire skills that truly stand out in the job market.

This program not only introduces key concepts in a seamless and coherent manner but also provides pragmatic insights and hands-on experience, making the journey from understanding the theories to implementing them an enlightening one. The tutorial meticulously covers various aspects of ML, ensuring that the participants are well-equipped with the knowledge and skills required to deploy ML services adeptly in the real world. This tutorial acts as a beacon, illuminating the path for those embarking on their machine learning journey. It aligns perfectly with the aspirations of budding ML engineers, providing a balanced blend of theoretical knowledge and practical experience. The all-encompassing approach adopted by this tutorial makes it an indispensable tool for learning and mastering machine learning, allowing aspirants to transition smoothly into the field with a solid foundation.

I've been on the data scientist path for over a year. I watched so many different tutorials and followed so many courses which I learned from the basics. however, none of them taught me how to use my knowledge in the real-world. Pau, via his course teaches how to use data science and Machine learning knowledge in an effective way and with a business purpose. the whole point of machine learning is to get the business to make thoughtful decisions and drive revenue. I highly recommend working with Pau and also following him on social media to learn the REAL tips about how to be a machine learning engineer.

Awesome tutorial by pau! Includes the core concepts of taking a business challenge and resolve it by ML. The course walk you through the steps of understanding the problem, building the right model, optimize it and most importantly making it production ready! Love it!

Indeed, even before completing the tutorial you'll acquire the necessary confidence to construct real-world machine learning services. This tutorial is a valuable investment of both time and money. Its worth extends beyond the exceptional content it provides, as it also grants you access to a community of machine learning engineers. This community is a platform where you can seek assistance, share insights, and further your learning journey. I enthusiastically recommend this tutorial to all aspiring machine learning engineers. The benefits are dual: not only will you gain practical tooling skills, but you'll also delve into demand prediction, a topic of significant relevance in today's data-centric world.

If you want to start with ML this is your course. pau delivers a comprehensive step by step amazingly explained.

Testimonial for my Incredible Machine Learning Mentor I feel incredibly fortunate to have had the privilege of learning from an exceptional mentor like Pau. His course on Machine Learning has been a transformative journey that has enriched both my professional path and personal growth. Pau's unwavering dedication and genuine passion for the subject have left an indelible mark on my learning experience. From the very start, Pau exhibited an extraordinary commitment to teaching, creating an inclusive environment where each student's unique needs were met. His approachability and patience made it comfortable for me to seek guidance and clarification whenever I encountered challenges. One of the most valuable lessons I gained from Pau was the significance of establishing a robust development environment. His meticulous guidance and step-by-step instructions helped me overcome initial hurdles and laid a solid foundation for my journey in Machine Learning. I now confidently navigate complex coding environments, all thanks to his guidance. Pau's emphasis on understanding the business problem became a cornerstone of my learning. Through real-world examples and practical exercises, he ensured that we grasped the essence of aligning Machine Learning solutions with business goals. His fervor while explaining how Machine Learning can revolutionize industries and address intricate problems was truly inspiring. The heart of any Machine Learning endeavor, model training, was demystified by Pau. He adeptly broke down complex algorithms into digestible concepts, ensuring we comprehended the underlying principles. Under his guidance, I gained hands-on experience in model training and explored various techniques, significantly deepening my understanding. Pau's commitment transcended theoretical concepts as he delved into Model Operationalization - MLOps, a critical facet of Machine Learning deployment. His expertise shone through as he shared best practices, practical insights, and real-world scenarios. His mentorship equipped me with the skills to effectively deploy models, optimize performance, and navigate challenges in a production environment. The significance of monitoring Machine Learning models was underscored by Pau. He highlighted the need for continuous monitoring to ensure model reliability over time. His guidance on implementing robust monitoring systems was enlightening and empowered me to construct durable and sustainable Machine Learning solutions. Beyond his exceptional teaching skills, Pau emerged as a role model and a true inspiration. His genuine concern for students' success and well-being was palpable in every interaction. He fostered a sense of camaraderie among us, encouraging collaboration and mutual support. Learning from someone so dedicated and passionate was an honor. Thanks to Pau's mentorship and his course, I am elated to share that I have secured a position as an AI engineer. The knowledge and skills imparted by Pau played a pivotal role in preparing me for this exciting career milestone. I am profoundly grateful for his unwavering support and expertise, which not only enabled me to acquire essential skills but also instilled in me the confidence to excel. Pau, your guidance has been a guiding light in my journey. I am determined to carry the lessons and values you've instilled in me throughout my career, striving to make a positive impact in the realm of Machine Learning, just as you have. Thank you for everything.

Really enjoyed Pau's course on deploying an End to End ML Model. Having been working in the field of Data Science for the past 3 years, but never really gotten the chance to build an End to End ML Model, this course has definitely been a great value add for me. Looking to build more such projects on my own moving forward.

So much more is expected of Data Scientists (DS) today than, say 3 years ago. On top of the traidtional skillsets of statistical acumen, linear algebra, machine learning and programming skills (which is already a lot to deal with), DS today are also expected to handle end-to-end deployments and monitoring of model performance, participate in data engineering tasks and more. This tutorial from Pau teaches you exactly that. The initial part covers ingestion and pre-processing of a time-series data, which then leads naturally to building the various pipelines revolving around a feature store and configuration of Github actions. Even better, all of these features can be integrated free! I strongly recommend this tutorial regardless if you are just starting out, or already have some experience under your belt and want to have another perspective of doing things. Pau really knows his stuff.

I'd like to express my gratitude and commend the excellent delivery of the course content. The step-by-step approach you adopted made complex concepts digestible and enjoyable to learn. The depth and breadth of the course content were impressive. I particularly appreciated the real-world case studies and hands-on projects seamlessly integrating theory and practice. The guidance on building end-to-end machine learning pipelines was clear, well-structured, and immensely valuable. Moreover, the course offered a unique opportunity to understand the technical and business side of machine learning. From data preprocessing and model training to inference, insights on navigating the common challenges faced while deploying machine learning models in a production environment were enlightening.

The tutorial on building a real-world ML service was incredibly valuable. It provided step-by-step instructions, practical examples, and hands-on exercises that boosted my confidence as an ML engineer. It was definitely worth the money and time invested. I highly recommend this tutorial to aspiring ML engineers. It's a comprehensive resource that prepares you to build your first real-world ML service and beyond.

Working with Pau as a mentor was super helpful for me, as I got a clear picture of all the bits and pieces of an AI product in a business. It was a game changer for my career choices. I'd totally suggest him if you wanna learn how to make a difference as a ML engineer in a company.

The Real-World Machine Learning Tutorial is an invaluable experience of learning the skills required on the way to mastering ML in production. Pau does a wonderful job of guiding you through the ins and outs of developing an ML production system, right from conceptualization to deployment and monitoring. A must for all who aim to be ML engineers!

Pau Labarta Bajo has an extraordinary teaching style. The explanations are short, concise and to the point. What I liked most is the fact I get prompt assistance form Pau as well as other students, and learning together as a group is fun.

I am thrilled to share my experience with the ML course that I recently completed. It has been an incredible learning journey, and I can confidently say that this course is one of the best I have ever taken to learn Machine Learning systematically, from scratch to a pro-level. Pau, the instructor, has been extremely supportive and insightful, providing invaluable guidance and mentoring throughout the course. With Pau's help, I was able to take on new ML projects and delve into the world of ML and MLOPS with ease. The course structure and content were well-thought-out and presented in an intuitive and easy-to-follow manner, making the learning experience both enjoyable and effective. I highly recommend this course to anyone looking to transform their knowledge of Machine Learning and take their skills to the next level. Trust me; you won't regret it!

As you know, a #machinelearning model without production is a model with no value or revenue. If you're looking to cover subtle grounds of technical debt involved in end-to-end Machine Learning in a real application, I'd highly guarantee that this simple course by Pau Labarta Bajo would take you strides further whether you're an expert or just starting out your #career in #ml. I haven't gotten a better boost in confidence before stumbling across this Tut!! 🔥

This course has exceeded my expectations. From the first video I felt very comfortable and I was able to follow all the steps thanks to Pau's explanations and the resources provided. I have solved weak points that I had in the whole process since you find a problem until you implement it in the real world. Once you finish the course you have the feeling of having in your hands a tool capable of solving any real problem thanks to ML. I recommend it 100%.

An excellent compilation of content necessary to develop skills as ML/DS professional. Taking this course not only elevates one’s technical skills but also helps understand various concepts to turn a business problem into a deployable solution. The teaching style is crisp and keeps one engaged while explaining everything in detail. I can’t wait for more content from Pau!

I have learned a lot from Pau, especially in ML deployment and OPs. I think being familiar with how it all works together will really help you plan out your projects better and make you more efficient from the beginning. This will definitely help prepare you for building real-world services. It was definitely worth the time and money.

I have really enjoyed the real world scenario that Pau wants all aspiring Data Scientists to go thru, so that they get out of their Master’s course or YouTube videos and working with simple datasets. Through this course, Pau works on a process, that intends to bring us aspirers, as close to real world when it comes to what we might have to do once you have a model. You may have learnt Linear Regression, Boosting models and others in your Master’s course but this course tries to connect you to how really a Data Scientists goes about looking at a problem, visualise it, clean it, prep it for training, build a model and then deploy it, so that it actually drives value for the business. He didn’t waste time going around the bush and was to the point thru out. I am aspiring Data Scientist, I have some Industry experience in different IT technologies and I like this kind of teaching and I really appreciate Pau for putting together this collection of videos. The course is not to teach you all about Machine Learning. If you have the basics and you want to now know what to do with the basics and how an employed Data Scientist works, this might be your thing. - Vatsal

This tutorial was extremely useful. I am eager to continue working on ml modeling. I will surely recommend this course to fellow ml engineers

I’m a data scientist aspiring to get a job in ML industry. I’ve been following Pau for a while on Twitter and the content he shares helped me understand the bigger picture. With the Real World ML tutorial, I could finally get hands on experience and see what it means to transform a business problem into a ML model, AND deploy it. The tutorial is definitely worth your time and money and you can ask Pau and the community anything you are not sure about. I highly recommend it!

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