Service Description

Unlock the power of large language models (LLMs) in this immersive one-day workshop designed for data analysts, data scientists, and Python enthusiasts. Through hands-on exercises you'll gain practical skills for building LLM powered apps using cutting edge tools like LangChain and Hugging Face. Students will learn best practices for prompt engineering and how to apply Retrieval Augmented Generation (RAG) for improving model performance. LEARNING OBJECTIVES - Understand the fundamentals of large language models and their practical applications - Apply prompt engineering techniques to tailor outputs from LLMs to meet your specific needs - Implement LLMs efficiently using Python and the LangChain library - Enhance model performance through the application of RAG (Retrieval-Augmented Generation) COURSE INFORMATION - This course is 6 hours with a 60-minute break for lunch - Classes will have a maximum of 20 students - Students should have basic python skills such as using Jupyter notebooks and importing libraries - Course will include lectures and hands-on exercises where students will practice writing code - Dual monitors are highly recommend - it's important for students to be able write code while watching the lectures (Note: Tablets/iPads can be used to view the lectures in lieu of a second monitor) - Class requires software installation prior to class, but optional troubleshooting help will be provided 15 mins before class starts. - Students will be using Jupyter notebooks and the software can be downloaded and installed for free (highly recommend installing Anaconda, which includes a collection of data analysis tools) - Both PCs and Mac computers are supported for this course - Video recording of the class will be provided to students as a reference for reviewing