Vanderbilt Data Science’s AI Summer workshop is now in its second week. This free course is specially designed to provide researchers, educators, and students with a comprehensive understanding of the latest AI technologies and techniques, focusing on deep learning and transformers and their applications in solving diverse problems.
Those unable to participate in the workshops live can follow along with the lessons by watching the videos we upload to our YouTube page, specifically the AI Summer Playlist. Each lesson will be available on the same day it takes place, ensuring that you can conveniently access the content whenever and wherever you prefer.
The primary objective of the AI Summer workshop is to foster the development of new research and teaching resources related to AI on the Vanderbilt University campus. To ensure widespread access to the knowledge shared during the workshops, all session recordings and resources will be made available to everyone interested. The workshop encompasses various aspects of AI model fundamentals, including training and deployment, catering to individuals at different levels of expertise.
During the first week, participants were introduced to AI models, with a special focus on transformer models, which form the foundation of modern AI models. Subsequently, the sessions delved into the application of generative models, such as ChatGPT, utilizing the technique of prompt engineering. As we enter Week 2 of the AI Summer workshop, we are exploring the intriguing concept of AI-assisted programming for AI applications. In this session, we will demonstrate the profound implications of AI in the coding process itself. We will utilize AI frameworks to create new AI models, making this session a meta-experience in itself.
Looking ahead, Weeks 3 and 4 will offer participants the opportunity to delve deeper into building AI solutions and training and fine-tuning models. The Building AI Solution track will equip you with the skills to create comprehensive solutions using AI models and tools like plugins and LangChain. The Training Track will provide hands-on experience in training foundation models using domain-specific data, including text, audio, and image. Additionally, participants will learn how to train models from scratch, expanding the possibilities of AI applications.