Want to keep learning?

This content is taken from the UAL Creative Computing Institute & Institute of Coding's online course, Introduction to Creative AI. Join the course to learn more.
Brain with linear icons and ai brain outline signs

Welcome to Week 2

Welcome to Week 2.

Last week, we talked about how specific types of machine learning are changing the creative industries, both in terms of how we consume and make creative work. We started to get a better understanding of what AI in the creative industries is, and we thought about important issues affecting artists who work in the area.

This week, we will be meeting more people who use AI in their work in the creative sector, and also thinking about what skills you need in order to develop your career.

You now have an appreciation of some of the philosophical questions that recent advances in AI are raising. These questions include the role of the researcher or artist in the creation of new material. Even the word ‘new’ has become ambiguous as critics and practitioners debate what exactly ‘new’ means and where the boundaries of creativity lie.

Armed with this knowledge, you can now start to look at some of the more technical aspects of AI and machine learning, that is the specific use of computers to learn from input data. This week you will learn about some methods used in AI practice.

Machine learning

To begin with, you will learn how to assess the type of data you have, and also the type of data you want as a result of a machine learning process. You will also be introduced to classification and regression, two statistical analysis techniques that are the foundation of many types of machine learning algorithms.

Deep learning is a particular machine learning technique that has become prominent in popular media and is responsible for many of the advances we have seen in AI during the past few years. This week you will learn what this term actually means and you will hear from artists who have used deep learning in their work.

There is no single way to approach a machine learning problem and as the field expands, more new techniques are being discovered. You’ll investigate an alternative approach to creative AI practice known as interactive machine learning (IML). This uses a rapid and iterative approach to model training and the use of much smaller datasets than are necessary for deep learning. This approach has proven to be a fruitful area of practice and research for musicians and live performers.

Finally, you will hear from the experts about what skills you need to kickstart your career in creative AI. You will gain an appreciation of the different paths available to you and learn about the many great opportunities for learning that exist to take you to the next level.

Over to you

Before we begin, think about where you would like your interest in creative AI to take you.

  • Are there any particular paths you are more interested in?
  • What skills do you think you might need to begin or refresh your career in creative AI?

Use the Comments section to answer these questions and share your ideas with other learners.

Share this article:

This article is from the free online course:

Introduction to Creative AI

UAL Creative Computing Institute