About this guide
A concise exam companion for the programming AI courses assume. It covers Python fundamentals for data work, structured data through iteration, comprehensions and files, the NumPy n-dimensional array and its data model, and vectorisation: replacing loops with fast array operations, building the numerical patterns used across AI coursework. Every chapter ends with a worked example carried through step by step, so you can check the reasoning yourself.
Inside the guide
- Fundamentals for data work
- Structured data through iteration
- Comprehensions and files
- NumPy n-dimensional array and its data model
- Vectorisation: replacing loops
- Building the numerical patterns used across AI coursework
Questions students ask
What does Programming for AI cover?
It covers Python fundamentals for data work, structured data through iteration, comprehensions and files, the NumPy n-dimensional array and its data model, and vectorisation: replacing loops with fast array operations, building the numerical patterns used across AI coursework.
Who is Programming for AI for?
It is written for university students learning the programming AI courses assume, and for lecturers and librarians choosing a clear, exam-focused reading-list text.
What format does it come in?
Kindle ebook and paperback on Amazon.
Can I read part of it for free?
Full Marks Press offers a free sample chapter at fullmarkspress.com/free, and the full guide is free to read with Kindle Unlimited.