In a world where technology is developing at a rapid rate, fields that focus on automation and artificial intelligence are becoming the most lucrative. With many artificial intelligence courses available, it is important to remember that a strong base is fundamental.
So, the question is – What do you need to know before you can venture into a field like artificial intelligence?
Before heading to the pre-requisites, it is important to understand that AI is a field that is multi-dimensional. It can be used for anything from medicine to education. This also means programming AI is diverse, akin to law, where you constantly need to educate yourself on the updates of the technologies available in your field of AI.
Finally, the different fields of AI can have specific requirements, but on a broader scale, most AI in any field requires strong foundations that are basically the same. Here are a few things you need to know before studying about artificial intelligence.
Numbers Are Key
A strong understanding of mathematics is a must when venturing into artificial intelligence. The key here isn’t just knowing basic math. If you hope to venture into artificial intelligence, a deep understanding of discrete mathematics is part of the core foundation of the field.
Most artificial intelligence is based on various algorithms, and an understanding of these algorithms, as well as the ability to mathematically analyse them for errors and solutions, are considered the most basic requirement for AI.
Much like math, programming is an essential part of artificial intelligence, implementing the mathematical data into code in a manner where you can not only develop but maintain and enhance machine learning is also part of the core foundation of AI. This means you must be able to code at a high level and find a way to be creative with code to improve the functions of a developing AI system.
In-depth knowledge of Python is often considered a mandatory pre-requisite to learning artificial intelligence as this open sourced programming language is currently the most popular and widely used.
While programming and math are the foundations, the ability to analyse and interpret data is considered a cornerstone for anyone involved with developing AI. This skill is important as this is where the error guidance and solution base of AI stems from. Imagine a world where you create an algorithm and program that algorithm into a robot to vacuum.
This works successfully as a single task. Imagine now that you integrate another code into the same robot to do the dishes. The robot accidentally breaks the dishes or uses bleach to wash the dishes. This error is because the codes can overlap and create a fault or a bug. Data interpretation is essential to identify faults and bugs in order to rectify them.
While the three pre-requisites mentioned above are core tools for those studying AI, they aren’t the only ones you need. The field of AI you venture into may require knowledge of the field itself. An example of this is medical AI, where you will need an in-depth knowledge of medicine and how medicine functions. AI is ever growing, and its complexities are deep.
No matter the type of AI you choose to learn, a strong understanding of math, programming and the ability to analyse data accurately are a must.