Hands-on path from your first local LLM to RAG, agents, evals, and deployment you can ship. Leave with systems hiring managers and clients love.
“Best educational investment in my ML/AI journey”
One of the best educational investments I've made in my ML/AI journey. The tutorials cover crucial topics with a perfect balance of theory and practical applications. The code examples are clean, well-documented, and immediately applicable to real-world scenarios.
The problem·why engineers get stuck
855 engineers are learning the missing layer: grounding, evals, traces, and deployment.
$299·$197 lifetime·or $39/month ↗
Audience·two clear signals
If someone asks "How do you know this works?", this curriculum gives you the answer
Curriculum·six modules
Start with local models. Add retrieval, agents, evals, deployment, and monitoring. Each module targets a real pain point in production.
Build a local-first AI assistant with streaming, memory, and a real backend
Ready to start building?
Build proof you can explain, test, and deploy.$39/mo·$197 lifetime ↗
“Highly enjoyable!”
Studying recent AI advancements can be overwhelming with knowledge scattered everywhere. ML Academy centralizes learning by teaching both the math and code behind the latest LLMs and agentic applications. It offers real-world projects, tutorials, notebooks, and an active Discord community ready to engage.
Instructor·venelin valkov·mlexpert.io
ID · 42I teach the engineering layer that makes AI usable.
I've deployed ML/AI systems serving millions of users. I've also seen promising prototypes collapse because nobody could prove the answer, trace the tool call, reproduce the failure, or monitor the service.
MLExpert focuses on that missing layer: source-grounded RAG, AI agents and workflows, scored evals, and deployments you can monitor.
FAQ·10 questions·common objections
Still have questions? Reach out directly: venelin@mlexpert.io
Prefer to explore first? Try the free lesson ↗
“Absolutely recommended!”
It covers core concepts to ramp up people who have some software engineering experience. The libraries and tools help students go further, build confidence, and thrive as AI/ML engineers or make a career shift.
Final call·the last step
Leave with grounded answers, traced tool calls, eval reports, deployment scripts, and monitoring dashboards.
Included
