Noah Gift is the founder of Pragmatic AI Labs and serves as an Executive in Residence at Duke University, where he lectures in the Master of Interdisciplinary Data Science (MIDS) program. He specializes in designing and teaching graduate-level courses on machine learning, MLOps, artificial intelligence, and data science, while also consulting on machine learning and cloud architecture for students and faculty. A recognized expert in the field, Gift is a Python Software Foundation Fellow and an AWS Machine Learning Hero, holding multiple AWS certifications, including AWS Certified Solutions Architect and AWS Certified Machine Learning Specialist. He has authored several influential books, such as Practical MLOps, Python for DevOps, and Pragmatic AI, and has published over 100 technical articles across various platforms, including Forbes and O'Reilly. His extensive industry experience includes roles as CTO and Chief Data Scientist for notable companies like Disney Feature Animation, Sony Imageworks, and AT&T, contributing to major films like Avatar and Spider-Man 3. Gift's work has generated millions in revenue through product development on a global scale. He actively consults startups on machine learning and cloud architecture while leading initiatives to enhance data science education.

Alfredo Deza is an Adjunct Assistant Professor at Duke University's Pratt School of Engineering, where he specializes in teaching courses related to machine learning, data engineering, and programming. He has a rich background in software engineering and DevOps, with nearly two decades of experience working with various organizations, including ABC, Caltech, and Disney. Alfredo is also a co-author of several influential books on Python and MLOps, including Python for DevOps and Practical MLOps.On Coursera, Alfredo offers a wide range of courses such as "Advanced Data Engineering," "Introduction to Generative AI," and "MLOps Platforms: Amazon SageMaker and Azure ML." His courses are designed to equip students with essential skills in data engineering and machine learning operations, preparing them for careers in these rapidly evolving fields. Through his teaching and extensive industry experience, Alfredo aims to bridge the gap between theoretical knowledge and practical application in technology.