Large Language Models for Business with Python

Large Language Models (LLMs) help people with the everyday aspects of their lives, including writing content, increasing personal productivity, and simplifying daily tasks. By examining GPT-4, BERT, and other models, this transformative course offers an expansive and detailed understanding of LLMs and how they can be applied to create a competitive business advantage. The curriculum delves into the fundamental concepts, architectures, and training techniques required to create real-world applications, emphasizing hands-on experience using prominent platforms such as Python, LangChain, OpenAI, and Hugging Face. The course also teaches students the practical skills to create large language model applications such as automatic text generators, language translators, and models that gauge consumer sentiment toward products and brands. Additionally, students will learn the following:The differences between various model architectures and how to select which architecture is best suited for a particular use caseTechniques for efficient training and fine-tuning of modelsSelecting and interpreting metrics that communicate how accurately the model makes predictions on new data it wasn’t trained onThe course features guest speakers from the field, interactive coding sessions, and a final project, allowing students to apply their knowledge in a real-world context. By the end of the course, students will have a robust understanding of large language models and hands-on experience with various tools and libraries. They will have the skills to use these models responsibly and effectively in future work or research.

Charlie Flanagan
Head of Data Science, Balyasny Asset Management


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Online, instructor-led
Jan 31 - Mar 20, 2024
Stanford Continuing Studies