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How to teach an art or technology class based on my book: MAKE ART with Artificial Intelligence

If you are planning to teach an art or technology class, this post is for you! You can use this as a textbook, including online supplemental materials to teach a course on art and technology. The book comes with 20+ practical studies, 35+ notebooks, 200 illustrations, examples, and online resources that each student can access. I’ll also be offering a video (announced for Microsoft Garage launch in Atlanta).

Prerequisites

No special prerequisites, general interest in arts, technology and digital art. Students can be introduced to tools, techniques (online).


What’s included:

  • Paperback edition of the book – perfect as a textbook (184 pages), great for students, it’s a beautiful 8×10 edition with color illustrations and section highlights for tips and practical exercises. (Available on Amazon)
  • Online repository with practical examples from the book – the best part of this course for your students is the abundance of training materials and examples, including more than 20+ practice studies, 35+ online notebooks and examples.
  • Art Gallery with examples – all artwork from this book, created or augmented with Artificial Intelligence, including sketches is available in the Art of AI Gallery.

 This is similar to the best lecture classes I had in college where the professor talked in class about the concepts and fundamentals but then gave us homework that would let us experiment and try out the concepts hands-on.

From Reviews

Every chapter of this book has a practice section with practical exercises.

Contents

  • Getting Started (History of Art and AI – Getting started with AI – Drawing – Sketching – Action and Poses – Landscapes and Scenery – Animation – Selling your Art).
    Practice Exercises
  • Creative AI Tools (Traditional tools – Digital tools – AI Tools – Python – Notebooks)
    Practice Exercises
  • Neural Networks (Neurons – Neural networks – Supervised learning – Unsupervised learning – Generative Adversarial Networks – Reinforcement learning)
    Practice Exercises
  • Drawing and Sketching (Sketching with AI – What’s a Sketch? – Improving Sketches with AI – Childhood Drawings – Creativity – Inking – Shading and Light – Coloring)
    Practice Exercises
  • Faces and Facial Expressions (How AI recognizes human faces – Facial features – Emotions – 3D Faces – Cartoons and Caricature – Generating Faces with AI)
    Practice Exercises
  • Pose and Action (Humans in action with AI – Keypoints – Pose Estimation – Drawing Human Body – Human Pose Datasets – Perspective and Depth – 3D)
    Practice Exercises
  • Landscapes and Scenery (Landscapes – Generating Landscapes – AI Models and Methods for Landscapes – Practice Studies)
    Practice Exercises
  • Animation (Animation – 12 Principles of Animation – Animating Speech and Lips – Animating Neural Transitions – Practice Studies)
    Practice Exercises
  • Style and Content (Style and Style Transfer – Generative Adversarial Networks – Creative Style)
    Practice Exercises
  • How to Sell your Art (Why Blockchain – Smart Contracts and NFTs – Creating a Crypto Wallet – Creating your Gallery – Listing for Sale – Getting Paid)
    Practice Exercises
  • The Art of AI – Gallery of AI Art

Class structure

The book is logically structured, beginning with the basics, history of art, technology and artificial intelligence, and applications of sketching and drawing. Chapter 1, Getting Started shows students examples of “before” and “after” artwork. At the end of the first chapter, students can take the first practical exercise by drawing a sketch using their favorite (traditional or digital tools).

Chapter 2 takes a look at creative tools. In addition to traditional and digital tools, students learn about Artificial Intelligence tools. Includes a practical example for art.

The course progressively navigates students towards more areas of artificial intelligence applications in art: portraits, emotions, facial expressions, poses, scenery and landscapes, animation etc. Students are introduced to practical neural networks for art, with easy-to-use exercises, from creating a simple neural net to advanced methods for style transfer. This is very similar to classical drawing/art classes, but with the emphasis on using Artificial Intelligence and technology.