Academy Course
Generative AI & LLM Architectures
Master Transformers from the ground up. Fine-tune local open-weight models (Llama 3, Mistral), deploy embedding vectors, and scale GPU inference endpoints.
Course Syllabus
Syllabus 1: LLM Core
Transformers architecture, tokenizers, self-attention mechanisms, and parameters scaling.
Syllabus 2: Fine-Tuning
Supervised Fine-Tuning (SFT), LoRA, QLoRA, and optimization loops on GPUs.
Syllabus 3: Embeddings
Generating vector representations, cosine similarity metrics, and dimensional reductions.
Syllabus 4: LLMOps
Model serving endpoints, Docker containerization, cloud resource management, and model quantizations.