The LLM Course is a systematic learning resource for Large Language Models (LLMs), offering a complete learning path from beginner to expert level. The course is divided into three major modules: fundamentals, scientist, and engineer tracks, covering a comprehensive knowledge system from theory to practice. The fundamentals module introduces basic knowledge in mathematics, Python, and neural networks; the scientist module delves deep into LLM architecture design, pre-training techniques, data processing, supervised fine-tuning, and model evaluation; while the engineer module focuses on practical application development, including model deployment, vector storage, RAG technology, and agent development.
Course Features
The course adopts a progressive teaching approach, catering to both beginners’ needs and advanced developers’ expectations. In the scientist section, it thoroughly analyzes the architectural evolution from traditional Transformers to modern LLMs, explaining in detail data preparation, distributed training, and model optimization techniques. The engineer section focuses on production practices, comprehensively covering model deployment, performance optimization, and security measures.
Supporting Resources
The course is equipped with a complete learning support system, including detailed engineering practice manuals, personalized learning assistants available on mainstream platforms, and practical tools covering model evaluation, fine-tuning, and deployment. Each topic comes with rich reference materials, including latest research papers, tutorials, and open-source projects, helping learners stay current with industry developments.
Learning Path
Learners are recommended to selectively study introductory content based on their personal foundation, then progressively delve into theoretical knowledge and practical applications. Through a step-by-step learning process, combined with supporting resources and tools, learners gradually master LLM development skills. Course content keeps pace with technological developments, regularly updating cutting-edge knowledge to ensure learners always stay current with the latest LLM technology trends.
Practice-Oriented
The course particularly emphasizes hands-on practice, providing numerous real-world cases in the engineer module. Through step-by-step guidance, it helps learners master various skills in LLM application development, enabling them to independently complete the entire development process from model selection and performance optimization to final deployment.
