LLM-Beginner is an educational resource combining an electronic textbook with six progressive programming tasks that teach large language model fundamentals and agent development.
The resource addresses the challenge of learning LLM development from first principles through a structured curriculum. It progresses from implementing core components—attention mechanisms and Transformers—through building a small language model, then advances to fine-tuning techniques, retrieval-augmented generation, tool-calling agents, and finally a coding agent capable of modifying and testing code. Each task requires learners to implement key components from scratch before comparing their work against established frameworks, with self-checking scripts provided to validate results.
The material suits developers with Python and deep learning foundations who want hands-on understanding of LLM internals rather than just API usage. The six tasks are designed to be completed sequentially but can be approached selectively based on prior knowledge. The curriculum emphasizes implementation-first learning, where understanding principles through coding precedes exposure to production frameworks. The textbook covers neural networks, Transformer architecture, model training, human alignment, and agent construction across four conceptual sections. Tasks range from two to six weeks depending on learning pace and experimental scope, with resource requirements varying by task.
The project maintains active engagement with learners through issue tracking and provides self-contained task directories with implementation requirements, data scripts, and interface specifications. The curriculum uses the Qwen model series consistently throughout and prioritizes Chinese language content where appropriate, with English used only when English datasets offer significant advantages. Development activity shows ongoing refinement of task specifications and learning materials, with the textbook manuscript in preparation for publication and content updated as revisions are made.
