Advanced Practical Data Science

APCOMP 215 Subject & Catalog Number

Description

The primary objective of this course is to provide a comprehensive understanding of the Deep Learning process in a practical, real-world context. With a strong emphasis on Machine Learning Operations (MLOps), this course not only reviews existing Deep Learning flows, but also enables students to build, deploy, and manage applications that leverage these models effectively. In the rapidly evolving field of data science, merely creating powerful predictive models is not enough. Efficiently deploying and managing these models in production environments - a practice often referred to as MLOps - has become an essential skill. MLOps bridges the gap between the development of Machine Learning (ML) models and their operation in production settings, combining practices from data science, data engineering and software engineering. This course is built upon the model of balancing conceptual understanding, theoretical knowledge, and hands-on implementation. It introduces students to the iterative process of model development, testing, deployment, monitoring, and updating, ensuring they acquire a strong foundation in MLOps principles.