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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.
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Key roles and how to get there

In the previous step, we heard from creative AI artists and researchers who are currently working in this field. They discussed the skills needed to work in the industry and how they were able to acquire those skills.

As we have seen, there is no single path to entry into the field for our experts, rather a combination of technical skills and creative interests.

The types of roles filled by creative AI practitioners include digital artists, university researchers and lecturers, musicians and game developers, among others. The main skills you would need to learn depend on the domain you want to work in. For example, if you are a musician, you would likely want to have a good foundation in music and music technology alongside knowledge of machine learning algorithms and frameworks.

A universal skill that can be applied to most fields is computer programming. Much machine learning work is done in the Python programming language for example. This skill will give you the ability to fully explore your machine learning algorithms and perhaps even develop your own. If you are interested in developing AI and machine learning algorithms of your own, then a computer science or data science qualification would be the best place to start. A qualification or short course in these areas will focus specifically on developing skills directly involved with AI such as algorithms, mathematics and statistical analysis methods.

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This article is from the free online course:

Introduction to Creative AI

UAL Creative Computing Institute