Noah Gift is a lecturer and consultant at MSDS, at Northwestern and the Graduate Data Science program at UC Berkeley and the UC Davis Graduate School of Management MSBA program as well as Duke MIDS and UNC Charlotte Data Science Initiative. He is teaching and designing graduate machine learning, AI, Data Science courses and consulting on Machine Learning and Cloud Architecture for students and faculty. These responsibilities including leading a multi-cloud certification initiative for students. He has published 100’s of technical publications including multiple books on subjects ranging from Cloud Machine Learning to DevOps. Gift received an MBA from UC Davis, an M.S. in Computer Information Systems from Cal State Los Angeles, and a B.S. in Nutritional Science from Cal Poly San Luis Obispo.
Noah is a Python Software Foundation Fellow, AWS Subject Matter Expert (SME) on Machine Learning, AWS Certified Solutions Architect, and AWS Certified Machine Learning Specialist, AWS Certified Big Data Specialist, AWS Academy Accredited Instructor, Google Certified Professional Cloud Architect, Microsoft MTA on Python, He has published books, videos, and courses on cloud machine learning, DevOps, Python, Data Science, Machine Learning, and Computer Vision. He writes and publishes content for publications including Forbes, IBM, Red Hat, Microsoft, O’Reilly, and Pearson. Workshops and Talks have been given around the world for organizations including NASA, PayPal, PyCon, Strata, and FooCamp. As an SME on Machine Learning for AWS, he helped created the AWS Machine Learning certification as well as serve as an AWS Faculty Cloud Ambassador.
He has worked in roles ranging from CTO, General Manager, Consulting CTO, Consulting Chief Data Scientists and Cloud Architect. This experience has been with a wide variety of companies including ABC, Caltech, Sony Imageworks, Disney Feature Animation, Weta Digital, AT&T, Turner Studios and Linden Lab. In the last ten years, he has been responsible for shipping many new products at multiple companies that generated millions of dollars of revenue and had global scale. Currently he is consulting startups and other companies, on Machine Learning, Cloud Architecture and CTO level consulting as the founder of Pragmatic AI Labs.
His most recent books are:
Pragmatic A.I.: An introduction to Cloud-Based Machine Learning (Pearson, 2018)
Python for DevOps (O’Reilly, 2020)
Cloud Computing for Data Analysis (Pragmatic AI Labs, 2020)
Testing in Python (Pragmatic AI Labs, 2020)