Become an LLM Engineer in 8 weeks: Build and deploy 8 LLM apps, mastering Generative AI, RAG, LoRA and AI Agents.
InstructorLigency Comidoc has tracked 6 coupons for this course since 2025, last checked 30d ago. On average, a new coupon appears roughly every 68 days.
| Coupon code | Discount | Added | Status | Lifetime |
|---|---|---|---|---|
| AI_SEPTEMBER_26 | 13% off | Expired | 3d 5h | |
| AI_AUGUST_26 | 13% off | Expired | 22d 6h | |
| AI_JULY_26 | 13% off | Expired | 24d 4h | |
| AI_APR26 | 17% off | Expired | 26d 7h | |
| AI_CORE_TRACK_12_25 | 28% off | Expired | 9d 5h | |
| LLM_SEPTEMBER | 25% off | Expired | 30d |
Editorial course preview
These 3 complementary views highlight concrete, legible examples from the course presentation.
This slide outlines an eight-week curriculum focused on leveling up AI skills through topics like RAG, fine-tuning, and agents, utilizing tools such as HuggingFace, Gradio, and LangChain.
This interface demonstrates a code conversion tool comparing Python and C++ implementations of a Linear Congruential Generator algorithm with execution controls.
This screenshot shows a Jupyter Notebook visualization of a 3D Chroma vector store, illustrating how high-dimensional embeddings are clustered and distributed across spatial axes.
Instruction covers a wide range of essential engineering tasks including RAG lifecycle management, model evaluation via benchmarks like MMLU-Pro, and fine-tuning using QLoRA techniques.
The curriculum emphasizes hands-on learning through diverse projects, such as building multi-modal agents and implementing RAG systems from scratch.
Some learners report excessive verbal filler and repetitive recaps that can slow the learning momentum.
As the course progresses into complex Python classes, some learners find the lack of step-by-step code walkthroughs challenging. Note that several such signals were recorded before the displayed update date; while an update label is present, it does not prove these specific issues were corrected.
Selected from the course's public promotional preview. These images document visible presentation material only; they do not represent the complete paid curriculum.
Aligns well with the goal of becoming an AI engineer through practical Python-based instruction.