The framework for decision-making that will affect your life and career
This article would end here if picking the best degree course or program to study artificial intelligence (AI) at a university were simple. However, it doesn’t.
This implies that there is more to it than simply choosing to study AI at a university, particularly if the goal is to eventually work in the field.
The title of an AI course for an MSc, PhD, diploma, or BSc at a different university in the United Kingdom is shown in the image above together with keywords and themes related to that course. Even more keywords were present in each of the courses I studied to make this word cloud.
The academic route to becoming an AI practitioner is not without its challenges.
Let’s say you choose your university courses without giving them any thought. That suggests you could have been better suited for a course that covered robotics or mechanics rather than a data-centric course as your interests lie in the hardware-focused area of AI.
In this paper, I describe a useful framework that offers a flexible method for choosing a suitable AI-related course at most higher educational institutions. You are welcome to use this framework on your own projects or to distribute it to other young AI enthusiasts.
What, Why, How and Where
How do you decide the AI subject at university to enroll in?
The aforementioned question does not have a clear solution. Utilizing various reasoning techniques that take into account your aspirations (what and why), capabilities (how), and environment (where) is a practical way to choose AI courses at university.
The “what” and “why” evaluate both internal and environmental factors that encourage you to work toward a particular objective. More specifically, the ‘what’ approach makes sure that you are not just chasing an arbitrary goal but that you understand what you want to achieve over the course of a 30 to 50-year career in AI, taking milestone goals into account as well.
