Overview
AI-Native Development
Product Engineering
Machine Learning
System Design
Overview
Our programme is built around weekly practical workshops where you'll work on real engineering challenges. Rather than following a fixed curriculum, sessions respond to the rapidly evolving AI landscape and what participants are actually building. You'll tackle problems like integrating semantic search into existing applications, building multi-agent workflows for production systems, and implementing RAG architectures that handle real-world constraints around cost and latency.
Each week combines hands-on implementation with collaborative problem-solving. You might spend one session building an MCP server to extend Claude's capabilities, another optimising vector search performance, and another fine-tuning open-source models for specific use cases. The focus is on shipping working features, not academic exercises.
The technical content spans the full stack of modern AI engineering: from using frontier models effectively through APIs, to understanding transformers well enough to customise them for production. You'll work with PyTorch to build neural networks from first principles, implement attention mechanisms, and gain the foundation needed to make informed decisions about model selection, fine-tuning, and deployment. When you need to containerise models, manage data pipelines, or handle GPU orchestration, you'll learn the MLOps practices that make systems reliable at scale.
Overview
Focus Areas
Our programme is built around weekly practical workshops where you'll work on real engineering challenges. Rather than following a fixed curriculum, sessions respond to the rapidly evolving AI landscape and what participants are actually building. You'll tackle problems like integrating semantic search into existing applications, building multi-agent workflows for production systems, and implementing RAG architectures that handle real-world constraints around cost and latency.
Each week combines hands-on implementation with collaborative problem-solving. You might spend one session building an MCP server to extend Claude's capabilities, another optimising vector search performance, and another fine-tuning open-source models for specific use cases. The focus is on shipping working features, not academic exercises.
The technical content spans the full stack of modern AI engineering: from using frontier models effectively through APIs, to understanding transformers well enough to customise them for production. You'll work with PyTorch to build neural networks from first principles, implement attention mechanisms, and gain the foundation needed to make informed decisions about model selection, fine-tuning, and deployment. When you need to containerise models, manage data pipelines, or handle GPU orchestration, you'll learn the MLOps practices that make systems reliable at scale.
Cost & Eligibility
Our Level 6 Machine Learning Engineer apprenticeship is fully funded through the apprenticeship levy, meaning there's no cost to eligible applicants. To qualify, you'll need to be employed (or have a confirmed job offer) with a UK company that can support your apprenticeship, be over 18, and have the right to work in the UK. You'll also need a strong foundation in programming.
Application process
Testimonials
The course delicately balances the academic theory with the practical implementation. Both are fundamentally important, and Founders and Coders has done a brilliant job honouring both aspects of the discipline in such a compressed time frame. I thoroughly enjoyed the course; the learning was invaluable, and being part of a buzzing collective energy of people learning together was even more so.
The content is innately challenging, but the hands-off, peer-led learning environment is super engaging and ultimately rewarding. I was very grateful to take part.
The Founders and Coders team put an extraordinary amount of effort into their programmes. I got a lot more than I expected out of it. The apprenticeship provided exactly what I needed to transition into AI product development. I run an agency and this apprenticeship led directly to us shipping our first in-house product. I couldn’t recommend it enough. The programme gave me time to absorb complex concepts and immediately apply them in my day-to-day work.
What distinguished this apprenticeship was the quality of the cohort and the hands-on approach. Rather than passive learning, we implemented models and frameworks from research papers, debugged real systems, and deployed working AI applications. The peer-led format meant I learned as much from other apprentices as from the instructors themselves.
The technical depth exceeded my expectations. We covered everything from, rapid prototyping to deployment transformers, always with an emphasis on understanding the fundamentals rather than just using libraries. This foundation has proven invaluable in my current role.
The apprenticeship structure worked well for developing practical skills while maintaining full-time employment. Each session built naturally on previous work, allowing concepts to solidify properly between sessions.
For anyone considering an AI apprenticeship, Founders and Coders offers a rigorous, practical programme. The skills you develop are immediately applicable, and the collaborative learning environment accelerates your progress considerably.
Get the right group of people together—curious, collaborative, and genuinely enthusiastic—and give them the challenge of figuring out machine learning's intricacies, and something remarkable happens. It demands focus, energy, and serious brainpower, but you come out the other side having genuinely mastered something difficult. That's exactly what the Founders and Coders apprenticeship is, and it's worth every second of it.
The Founders and Coders AI apprenticeship delivered what I needed without any unnecessary fluff. You learn by building things, working with other apprentices who are equally motivated, and having access to instructors who actually know their stuff.
The peer-led approach means you're constantly explaining concepts to others and having them explained back to you, which is surprisingly effective. When you can teach something, you know you've understood it properly.
What stood out was how practical everything felt. There's no busywork or arbitrary assignments, everything you do has a clear purpose and connects to real applications. The instructors trust you to take ownership of your learning, which makes the whole experience feel more professional.
The cohort matters more than I expected. You're learning alongside people from different backgrounds, which means you get exposed to various perspectives and approaches. It keeps things interesting and pushes you to think differently.
If you're considering it, just know it requires genuine commitment. But if you put the work in, you'll come out with skills that are immediately useful.
The Founders and Coders apprenticeship has been transformational. It enabled me to earn an extra qualification while working and jump start my research career in AI. Inspired by the programme, I'm now doing a PhD in a similar research area.
The peer-led, project-focused curriculum was by far the most effective and enjoyable way to learn deep learning theory and implementation. Being surrounded by a highly motivated cohort in a buzzing, collaborative environment massively accelerated my learning process.
I loved the project work; finding practical applications of AI within my workplace and deploying a full working prototype was such a valuable experience.
I can't recommend the apprenticeship highly enough to anyone looking to dive deep into machine learning!
The Founders and Coders apprenticeship turned out to be one of the best professional decisions I've made. I came in wanting to understand machine learning properly rather than just using pre-built tools, and that's exactly what I got.
What surprised me most was how much the peer learning aspect mattered. You're working alongside people who are genuinely invested in figuring things out, and that creates momentum you just don't get learning alone. When you're stuck on something, there's always someone who's approached the problem differently or spotted something you missed.
The technical content is serious—we built models from scratch, worked through the mathematics behind modern architectures, and deployed actual systems. But it never felt like box-ticking or following tutorials. You're solving real problems and understanding why things work the way they do.
The instructors know their stuff and are good at letting you struggle just enough before stepping in. That balance matters because it means you actually retain what you learn rather than just copying solutions.
If you're thinking about getting into AI properly and want something more substantial than online courses, this apprenticeship delivers. It's demanding, but that's the point.
The course delicately balances the academic theory with the practical implementation. Both are fundamentally important, and Founders and Coders has done a brilliant job honouring both aspects of the discipline in such a compressed time frame. I thoroughly enjoyed the course; the learning was invaluable, and being part of a buzzing collective energy of people learning together was even more so.
The content is innately challenging, but the hands-off, peer-led learning environment is super engaging and ultimately rewarding. I was very grateful to take part.
Read more
The Founders and Coders team put an extraordinary amount of effort into their programmes. I got a lot more than I expected out of it. The apprenticeship provided exactly what I needed to transition into AI product development. I run an agency and this apprenticeship led directly to us shipping our first in-house product. I couldn’t recommend it enough. The programme gave me time to absorb complex concepts and immediately apply them in my day-to-day work.
What distinguished this apprenticeship was the quality of the cohort and the hands-on approach. Rather than passive learning, we implemented models and frameworks from research papers, debugged real systems, and deployed working AI applications. The peer-led format meant I learned as much from other apprentices as from the instructors themselves.
The technical depth exceeded my expectations. We covered everything from, rapid prototyping to deployment transformers, always with an emphasis on understanding the fundamentals rather than just using libraries. This foundation has proven invaluable in my current role.
The apprenticeship structure worked well for developing practical skills while maintaining full-time employment. Each session built naturally on previous work, allowing concepts to solidify properly between sessions.
For anyone considering an AI apprenticeship, Founders and Coders offers a rigorous, practical programme. The skills you develop are immediately applicable, and the collaborative learning environment accelerates your progress considerably.
Read more
Get the right group of people together—curious, collaborative, and genuinely enthusiastic—and give them the challenge of figuring out machine learning's intricacies, and something remarkable happens. It demands focus, energy, and serious brainpower, but you come out the other side having genuinely mastered something difficult. That's exactly what the Founders and Coders apprenticeship is, and it's worth every second of it.
The Founders and Coders AI apprenticeship delivered what I needed without any unnecessary fluff. You learn by building things, working with other apprentices who are equally motivated, and having access to instructors who actually know their stuff.
The peer-led approach means you're constantly explaining concepts to others and having them explained back to you, which is surprisingly effective. When you can teach something, you know you've understood it properly.
What stood out was how practical everything felt. There's no busywork or arbitrary assignments, everything you do has a clear purpose and connects to real applications. The instructors trust you to take ownership of your learning, which makes the whole experience feel more professional.
The cohort matters more than I expected. You're learning alongside people from different backgrounds, which means you get exposed to various perspectives and approaches. It keeps things interesting and pushes you to think differently.
If you're considering it, just know it requires genuine commitment. But if you put the work in, you'll come out with skills that are immediately useful.
Read more
The Founders and Coders apprenticeship has been transformational. It enabled me to earn an extra qualification while working and jump start my research career in AI. Inspired by the programme, I'm now doing a PhD in a similar research area.
The peer-led, project-focused curriculum was by far the most effective and enjoyable way to learn deep learning theory and implementation. Being surrounded by a highly motivated cohort in a buzzing, collaborative environment massively accelerated my learning process.
I loved the project work; finding practical applications of AI within my workplace and deploying a full working prototype was such a valuable experience.
I can't recommend the apprenticeship highly enough to anyone looking to dive deep into machine learning!
Read more
The Founders and Coders apprenticeship turned out to be one of the best professional decisions I've made. I came in wanting to understand machine learning properly rather than just using pre-built tools, and that's exactly what I got.
What surprised me most was how much the peer learning aspect mattered. You're working alongside people who are genuinely invested in figuring things out, and that creates momentum you just don't get learning alone. When you're stuck on something, there's always someone who's approached the problem differently or spotted something you missed.
The technical content is serious—we built models from scratch, worked through the mathematics behind modern architectures, and deployed actual systems. But it never felt like box-ticking or following tutorials. You're solving real problems and understanding why things work the way they do.
The instructors know their stuff and are good at letting you struggle just enough before stepping in. That balance matters because it means you actually retain what you learn rather than just copying solutions.
If you're thinking about getting into AI properly and want something more substantial than online courses, this apprenticeship delivers. It's demanding, but that's the point.
Read more