Mentorship in LLMs &
AI Systems Engineering

Most courses teach from polished slides — great for introductions, but not for real engineering depth. This program is built from 8+ years of shipping AI systems in production. You'll learn by reading technical books (the way real engineers learn), writing actual code, and understanding the tradeoffs that matter in real projects. No shortcuts, no surface-level content.

You'll be able to design, build, and deploy production-ready LLM systems — RAG pipelines, fine-tuned models, AI agents, evaluation frameworks, and deployment architectures. More importantly, you'll develop the engineering mindset to learn any new AI technology on your own, without needing another course — if you follow the practice, read the resources, and apply what you learn.

Yes. Wael went from Solution Architect to Principal AI Engineer at a US company. Reema went from Software Engineer to AI Engineer leading a team. Muhammad built his own AI product that's now in production. The key is that you don't just learn AI — you build proof of what you can do.

Yes. Ehab was already an AI Engineer, but what changed was how he thinks — how he researches, organizes work, reads papers, and stays current. Even experienced engineers find gaps in their fundamentals or miss the engineering mindset that makes the difference between demos and production systems.

The sessions are recorded from the live program — complete and ready to watch at your own pace. For the Full Path plan, you also get a WhatsApp group, preparatory session with Bahgat, progress tracking via Google Sheet, and monthly check-ins to ensure you complete all content.

Plan for 5-10 hours per week. This includes watching sessions, running code, working through exercises, and working on a project. With the Full Path, your progress is tracked via Google Sheet and monthly check-ins to ensure you complete all content within 6 months.

This isn't a course you passively watch and forget. It's a system that teaches you how to learn — so after 6 months, you won't need another course if you commit to the practice and apply what you learn. The time you invest here replaces years of scattered learning. Most people who "don't have time" are spending that time on tutorials that don't stick.

You should be comfortable with Python and have basic ML familiarity (linear algebra, calculus, basic ML concepts). This is an engineering program for people who want to be ready to build production systems, not an introduction to programming or machine learning.

No. This program is for committed engineers. If you want to test the teaching style first, start with a single month for $55 — that's your low-risk entry point. But based on everyone who came before you, those who truly commit and want to succeed find this program is exactly what they needed.

The next cohort is expected in about 6 months. Full Path members get priority access and a special discount for the next cohort where you work on a real project.