As Artificial Intelligence grows more and more popular over time, parents and students alike have grown more interested in the subject. However, with little guidance from teachers or courses (sadly, there’s no AP Artificial Intelligence), getting into the field itself can seem like a huge hurdle. In this blog post, we will be going over when to take the first step into AI, and how you should do it.
When should you start AI?
Artificial Intelligence is presented as a terribly challenging and almost mystical field by the media and communities around us. However, a lot of Artificial Intelligence simply boils down into an understanding of mathematics and programming. Moreover, there are many different paths of AI, from image classification to natural language processing. There are multivarious models as well, such as the CNN or RNN. In a sense, there is a great diversity of possibilities, which means that young students can specialize and pursue their own specific interest in this vast field.
Thus, each branch of AI will have different spheres of knowledge involved. We can simplify these complexities though, and pinpoint what many consider to be AI to just one subject: the artificial neural network (ANN). This is the core of much of AI, and is usually one of the first subjects students learn about. To learn about the ANN, the student will need an understanding of Linear Algebra, Calculus, general mathematics, and programming. I, specifically, use Python. This may be a slight concern for some students or parents though, as many students only learn Linear Algebra, which is usually a Post-Calculus course, in junior or senior year at best.
For students under 11th grade who still want to start an interest in AI, there are other opportunities that don’t require that greater math level. There are free resources that allow students to create models without any knowledge in the math side (only some programming experience). These include MachineLearningforKids and other similar websites. You can also try out the Python deep learning API Keras, which has built in functions that does the math for you. With this, students can create their own simple AI model, as long as they have a bit of line coding experience and as long as they do research.
To summarize, if the student wants to learn the complexities of AI and the more mathematical aspects, grades 11th or 12th are recommended. If the student just wants to take a step into the field, then they can start as early as grade 5 with basic concepts.
How should you start AI?
As previously stated, there are an abundant amount of sources and help online. These include articles about different AI concepts, and some even include simple code. Most of learning about AI and getting started is a click away; simply search up “Neural Networks for Beginners” in Google.com and you’ll already see a lot of helpful information. With professional IEEE journals on Google Scholar as well, passionate students can build up a good amount of specific AI knowledge.
It is recommended that students and parents get a good look at the different applications of Artificial Intelligence, some simple beginners’ projects on the subject, and then choose a branch they want to tackle. Let’s say the student is interested in having the model classify different types of skin diseases from images. Then, the student should learn about basic AI, image classification, how to program the model, and finally training and testing it. With this style of learning, the student will have a better grasp on the modern and current AI knowledge specific to their interest, and be able to do their own research.
For younger students that may not be able to do their own research, there are courses and even books on Artificial Intelligence for beginners. This may be an easier option (although a costly one) for parents who may not have the time to help their child learn and tackle the tough subject.
AI is such a vast term encompassing a large variety of subjects. Students and parents should get a better understanding of what branch of AI they want to pursue. By doing research or taking a course, both younger and older students will be able to learn about it. Once you take the first step in, even swimming is possible.
For students younger than 5th grade: learning about AI is not really recommended
For students older than 5th grade: getting basic concepts should be fine
Helpful resources and requirements:
To code a model with Keras: Python programming is needed
To create a model with MachineLearningforKids: no programming needed
For students in high school: doing a simple research project is very possible
Most likely Linear Algebra, Calculus, and a general understanding of mathematics is needed
Programming knowledge is needed (if the student wants to code a model)
Google Scholar or any large database of professional information on AI
Articles, books, websites (such as Github) are all helpful
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