The accessibility of information makes it possible to learn almost anything with just a click of a button. This allows anyone from all walks of life to discover new hobbies or develop new skills, no matter their age. It’s a great benefit for the younger generation that wants to get started with the work skills they want to develop later in life.

Coding used to have a tall barrier of entry, especially since computers used to be scarce and networking capabilities were much slower. Nowadays, it’s easy to have a device connected to the internet, even if you’re just using a tablet or laptop. Because of this, learning code is much easier for the newer generation.

How to Start Learning AI at a Young Age

There’s no one clear way to get better at coding, especially since the internet gives you different ways to learn new things. There’s no end or limit to the number of things you want to know, even if you wish to approach AI projects. Although there are no strict rules in learning how to build AI, you can follow certain guidelines to make sure you’re making the right progress if you fancy yourself learning AI.

Here are three tips you should follow when learning the fundamentals of coding:

1. Start with Python

Although you can do just fine with learning the basics of Java and Swift, you’ll still need to learn Python to develop AI projects. Learning Python is an excellent foundation of your coding skills to prepare for AI projects. By simply understanding the basic syntax of Python, you can understand the process of debugging AI and developing your AI model. Thankfully, there are numerous online courses on Python if you’re struggling with specific topics.

2. Learn About Traditional Machine learning (ML)

An essential part of an AI project is its method of interpreting data. This is why you need to know the basics of creating traditional ML models. Instead of heading straight into deep learning and neural networks, it[‘s important to have a strong understanding of base infrastructures.

Through the linear regression models of traditional ML, you’ll better understand the relationship between data sets and machine learning. This also makes it easier to encounter and deal with loss functions, which will be important for AI and deep learning later on.

3. Use Jupyter Notebook

Having a thorough understanding of coding won’t do you well once you become a full-fledged developer. You should also be good at organizing your code so you can identify different strings with ease. For example, you can use Jupyter Notebooks to conveniently format and compile your code while saving notes and end results.

These notebooks have marked features in between cells to make it easier for you to leave notes. Additionally, this intuitive organizational model makes it simpler to revise notes or comment on scripts. Since building an AI project can get messy real quick, having an organized notebook is an excellent way to serve as a testing ground and to request feedback from other coders.

Although the tips above can guide you in learning your first steps into AI, your education shouldn’t stop by being isolated. The best way to develop your coding skills is to join a community that shares your interests and gives you opportunities to flex your new insights! If you challenge yourself beyond your personal projects, you’ll learn a lot more through experience instead of following expectations.

If you want to test your coding mettle, why not join a hackathon event? At, we provide a great way for newcomers and hackathon experts to easily find any hackathon event, online and in person! Join our community and meet like minded people learning the same thing you are, and take advantage of our free Masterclass series!