Udemy - Build a Mini llama.cpp in Pure C - LLM Inference Engine

Build a Mini llama.cpp in Pure C: LLM Inference Engine

https://WebToolTip.com

Published 7/2026
Created by James Jiang
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English | Duration: 11 Lectures ( 2h 36m ) | Size: 1.1 GB

LLM Inference Engine & Interactive Chat

What you'll learn
⚡ Build a complete Mini llama.cpp inference engine from scratch in pure C
⚡ Understand and parse the GGUF model format used by all local LLMs
⚡ Master mmap zero-copy model loading for fast LLM startup
⚡ Implement RMSNorm, SwiGLU, and RoPE rotary positional encoding
⚡ Code causal multi-head self-attention for LLM inference
⚡ Learn how KV Cache works and why it speeds up generation by 10–100x
⚡ Implement INT4 quantization and dequantization for model compression
⚡ Build custom tensor and matrix multiplication systems from zero
⚡ Write autoregressive token generation & greedy sampling logic
⚡ Develop a fully interactive LLM terminal chat
⚡ Gain real low-level C system programming skills for AI deployment
⚡ Read and understand official llama.cpp & GGML source code

Requirements
❗ Basic C programming knowledge (structs, pointers, file IO, functions)
❗ Basic understanding of Makefile compilation
❗ Fundamental knowledge of Transformer / LLM concepts
❗ A Mac, Linux, or Windows (WSL2) computer
❗ No prior llama.cpp or inference engine experience required