UDUdemy
AI Engineer Core Track: LLM Engineering, RAG, QLoRA, Agents
Intermediate 33.5 hours English Completion Certificate
What you'll learn
Build LLM apps with frontier and open-source models
Implement RAG with vector embeddings from scratch
Fine-tune open-source models with QLoRA
Design and run autonomous multi-agent systems
Deploy models serverlessly on Modal
Select and evaluate the right model for a task
This course includes
33.5h
On-demand video
Yes
Certificate
Yes
Mobile access
English
Language
Comparison · LBS
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Instructor
ED
Ed Donner
Udemy instructor
— learners— courses — instructor rating
Taught by Ed Donner, an entrepreneur and AI leader with 20+ years of experience who has co-founded and sold an AI startup and led technology teams at major financial institutions.
Requirements
- Python familiarity required
- ~$5 for frontier API calls (optional)
Who this course is for
- Developers becoming AI/LLM engineers
- Data scientists moving into GenAI
- Engineers building production AI apps
About this provider
UD
Udemy
The world's largest online learning marketplace. 65M+ students, 210,000+ courses.
4.3 trust score
Frequently asked questions
Yes — the course assumes Python familiarity and doesn't cover the basics. It's intermediate, with some advanced sections in the fine-tuning and agent weeks.
A small amount — about $5 in frontier-model API credits is recommended, though you can complete much of it with free open-source models.
DataCamp's are shorter, interactive, single-topic modules. This is one comprehensive bootcamp that goes end-to-end and far deeper on QLoRA fine-tuning and production deployment.
Yes — Udemy issues a shareable certificate of completion (not an accredited qualification).
Usually no — Udemy runs frequent sales below list price, with a 30-day refund and lifetime access.