IEEE Launches Online Training Course on Large Language Models
IEEE
PyTorch
IEEE has introduced a five-course online program, 'Large Language Models Demystified,' to help technical professionals master LLM engineering. The program covers transformer architectures, model optimization, RAG, RLHF, and deployment, aiming to bridge the gap between AI users and builders.
IEEE, through its Educational Activities and the IEEE Computer Society, has launched an online course program titled 'Large Language Models Demystified' on the IEEE Learning Network. The program consists of five courses that delve into the engineering behind generative AI, covering evolution from statistical methods to transformers, transformer architectures with self-attention and positional encoding implemented in NumPy and Python, advanced LLM design, training pipelines in PyTorch with parameter-efficient techniques like low-rank adaptation and quantization, and optimization, alignment, and deployment including RLHF and RAG. The program aims to address the growing demand for technical expertise as the LLM market is expected to grow 33% annually through 2030. Participants earn professional development credits and a digital badge from IEEE. The article also discusses four areas where LLMs are changing engineering work: moving beyond basic prompts via APIs, fixing hallucinations with RAG, prioritizing data security with private model instances, and enabling better collaboration by automating repetitive tasks.
- Сокращения
- LLM = Large Language Model — большая языковая модель
- API = Application Programming Interface — программный интерфейс приложения
- RAG = Retrieval-Augmented Generation — генерация с дополнением извлечением
- RLHF = Reinforcement Learning from Human Feedback — обучение с подкреплением на основе человеческой обратной связи
Source: IEEE Spectrum AI —
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