Advanced Practical Data Science

In today's artificial intelligence (AI)-driven world, building a robust deep learning model is only half the journey. The real challenge often lies in bringing this model to life in the form of an application that is scalable, maintainable, and ready for real-world deployment. In this course, we traverse the complex landscape of machine learning operations, with a special focus on large language models (LLMs). This course has been meticulously curated to provide a holistic understanding of the complete deep learning workflow, from refining your models to deploying them in production environments. We dive deep into topics like containerization, cloud functions, data pipelines, and advanced training workflows, with specific emphasis on LLMs. Students learn how to utilize LLM application programming interfaces (APIs) effectively, host APIs, fine-tune LLMs for specific tasks, adapt them to various domains, and build applications around them. Our objective is not only to help students grasp these concepts but also to empower them to build and deploy scalable AI applications. We delve into the particular intricacies of LLMs and their applications in real-world scenarios. Whether students are AI enthusiasts wanting to understand the intricacies of machine learning operations or seasoned professionals aiming to fortify their knowledge, this course promises a comprehensive exploration of the production side of AI, with a spotlight on LLM applications and productionizing.