Noah Gift


Adjunct Associate Professor in the Pratt School of Engineering

Noah Gift lectures at MSDS, at Northwestern, Duke MIDS Graduate Data Science Program, and the Graduate Data Science program at UC Berkeley and the UC Davis Graduate School of Management MSBA program, and UNC Charlotte Data Science Initiative. He is teaching and designing graduate machine learning, A.I., Data Science courses, and consulting on Machine Learning and Cloud Architecture for students and faculty. These responsibilities include leading a multi-cloud certification initiative for students. 

Noah is a Python Software Foundation Fellow.  He currently holds the following industry certifications for AWS:  AWS Subject Matter Expert (SME) on Machine LearningAWS Certified Solutions Architect, and AWS Certified Machine Learning SpecialistAWS Certified Big Data Specialist, AWS Academy Accredited Instructor, AWS Faculty Ambassador.  He also is certified on both the Google and Azure platform: Google Certified Professional Cloud ArchitectCertified Microsoft MTA on Python. He has published over 100 technical publications including multiple books on subjects ranging from Cloud Machine Learning to DevOps.  Publications appear in Forbes, IBM, Red Hat, Microsoft, O'Reilly, Pearson, Udacity, Coursera,, and DataCamp.  Workshops and Talks around the world for organizations including NASA, PayPal, PyCon, Strata, O'Reilly Software Architecture Conference, and FooCamp. As an SME on Machine Learning for AWS, he helped created the AWS Machine Learning certification.

He has worked in roles ranging from CTO, General Manager, Consulting CTO, Consulting Chief Data Scientist, and Cloud Architect. This experience has been with a wide variety of companies: ABC, Caltech, Sony Imageworks, Disney Feature Animation, Weta Digital, AT&T, Turner Studios, and Linden Lab, and industries:  Television, Film, Games, SaaS, Sports, Telecommunications. He has film credits in many major motion pictures for technical work, including Avatar, Spider-Man 3, and Superman Returns.

He has been responsible for shipping many new products at multiple companies that generated millions of dollars of revenue and had a global scale. Currently, he is consulting startups and other companies, on Machine Learning, Cloud Architecture, and CTO level consulting as the founder of Pragmatic A.I. Labs.

His most recent books are:

Practical MLOps

Getting your models into production is the fundamental challenge of machine learning. MLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way.

Publisher O'Reilly
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Cloud Computing for Data Analysis

A practical guide to Data Science, Machine Learning Engineering and Data Engineering

Publisher: Pragmatic AI LabsRelease Date: (Early 2021)


This book is designed to give you a comprehensive view of cloud computing including Big Data and Machine Learning. A variety of learning resources will be used including interactive labs on Cloud Platforms (Google, AWS, Azure) using Python. This is a project-based book with extensive hands-on assignments.

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Minimal PythonPublisher: Pragmatic AI LabsRelease Date: 2020


Even books that have “learn” in the title introduce readers to hopelessly complex topics like object-oriented programming or concurrency. It turns out YAGNI (You Ain’t Gonna Need It). Why teach students topics they won’t use either ever, or not for a few years?

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Python Command Line Tools: Design powerful apps with ClickPublisher: Pragmatic AI LabsRelease Date: 2020

Testing in PythonPublisher: Pragmatic AI LabsRelease Date: 2020


Getting started with testing can be hard, and this book aims make it all very easy by using examples and straightforwardly explaining the process. Testing is a core principle of robust software implementations and should be a prime skill to master that can be applied to any project.

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Python For DevOps: Learn Ruthlessly Effective Automation
Publisher: O’Reilly MediaRelease Date: December 31st, 2019

Much has changed in technology over the past decade. Data is hot, the cloud is ubiquitous, and many organizations need some form of automation. Throughout these transformations, Python has become one of the most popular languages in the world. This practical resource shows you how to use Python for everyday Linux systems administration tasks with today’s most useful DevOps tools, including Docker, Kubernetes, and Terraform.

Learning how to interact and automate with Linux is essential for millions of professionals. Python makes it much easier. With this book, you’ll learn how to develop software and solve problems using containers, as well as how to monitor, instrument, load-test, and operationalize your software. Looking for effective ways to “get stuff done” in Python? This is your guide.

Python foundations, including a brief introduction to the language How to automate text, write command-line tools, and automate the filesystem Linux utilities, package management, build systems, monitoring and instrumentation, and automated testing Cloud computing, infrastructure as code, Kubernetes, and serverless Machine learning operations and data engineering from a DevOps perspective Building, deploying, and operationalizing a machine learning project

Pragmatic AI: An Introduction to Cloud-based Machine LearningPublisher: O’Reilly MediaRelease Date: December 31st, 2019


Pragmatic AI will help you solve real-world problems with contemporary machine learning, artificial intelligence, and cloud computing tools. Noah Gift demystifies all the concepts and tools you need to get results—even if you don’t have a strong background in math or data science. Gift illuminates powerful off-the-shelf cloud offerings from Amazon, Google, and Microsoft, and demonstrates proven techniques using the Python data science ecosystem. His workflows and examples help you streamline and simplify every step, from deployment to production, and build exceptionally scalable solutions. As you learn how machine language (ML) solutions work, you’ll gain a more intuitive understanding of what you can achieve with them and how to maximize their value. Building on these fundamentals, you’ll walk step-by-step through building cloud-based AI/ML applications to address realistic issues in sports marketing, project management, product pricing, real estate, and beyond. Whether you’re a business professional, decision-maker, student, or programmer, Gift’s expert guidance and wide-ranging case studies will prepare you to solve data science problems in virtually any environment.

Python for Unix and Linux System AdministrationPublisher: O’Reilly MediaRelease Date: June 2009

Python is an ideal language for solving problems, especially in Linux and Unix networks. With this pragmatic book, administrators can review various tasks that often occur in the management of these systems, and learn how Python can provide a more efficient and less painful way to handle them.

Each chapter in Python for Unix and Linux System Administration presents a particular administrative issue, such as concurrency or data backup, and presents Python solutions through hands-on examples. Once you finish this book, you’ll be able to develop your own set of command-line utilities with Python to tackle a wide range of problems. Discover how this language can help you:

With this book, you’ll learn how to package and deploy your Python applications and libraries, and write code that runs equally well on multiple Unix platforms. You’ll also learn about several Python-related technologies that will make your life much easier.

His most recent video courses are:

His most recent online courses are:

You can follow Noah Gift on social media and on the web at:

Appointments and Affiliations

  • Executive in Residence in the Social Science Research Institute

Contact Information


  • M.B.A. University of California, Davis, 2013
  • M.S. California State University, Los Angeles, 2003

Courses Taught

  • IDS 793: Independent Study
  • IDS 721: Data Analysis at Scale in Cloud
  • IDS 706: Data Engineering Systems
  • AIPI 561: Operationalizing AI

Representative Publications

  • Gift, N; Behrman, K; Deza, A; Gheorghiu, G, Python for DevOps: Learn Ruthlessly Effective Automation (2019) [abs].
  • Gift, N, Pragmatic AI An Introduction to Cloud-Based Machine Learning (2018) [abs].
  • Beazley, DM, Python Essential Reference (2009) [abs].
  • Gift, N; Jones, J, Python for Unix and Linux System Administration (2008) [abs].