Road map to AI(Artificial Intelligence) — Part 1

Artificial intelligence or AI is not something new to us. We are surrounded by AI everywhere, from google personalized ads to messenger bots. Even many of us want to be AI developers. But due to lack of proper guidelines, many leave this road. In this article, I’m talking about the roadmap to AI. How can we start learning AI?

What is AI?

I’m not talking about the definition we read on books. I’m talking about what AI is, and how it works. Let’s learn about parts of AI.

Developers mostly work on 3 parts of AI. 1. Machine Learning(AI) 2. Deep Learning(DL) 3. Reinforcement Learning(RL)

The basic part of AI is machine learning. Machine learning is not learning about the machine. It’s the learning of machine. Machine learning is when a machine is learning. Imagine how a kid identifies a dog? We show him an animal, and say this is a dog. Next time when he sees a dog, he identifies that animal as a dog. The same goes for ML. We show our program some examples of what we want it to identify, the program learns from the examples and evolves. Let’s say we are programming a dog recognization system. We have to feed the program some examples of dogs. The program will learn from the examples and make itself better day by day. This process is machine learning.

Now come to deep learning. To be honest, I’m not interested in explaining deep learning. Because deep learning is not something different to explain. DL is just a deeper section of ML itself. The image shown below will clear your confusion.

Now let’s come to Reinforcement Learning(RL). This is the most interesting topic about AI. I’m more interested in RL rather than ML or DL. Have you ever heard about self-driving cars? or something like robots? Yes, you caught it right. When Artificial Intelligence comes to hardware and controls a mechanical thing like a car or a robot, that is called Reinforcement Learning. Things are getting interesting, right? Maybe these concepts look like interesting or fun-to-do to you. But the learning path is not so easy. Let’s talk about the learning path.

Let’s learn Artificial Intelligence

I’m talking about ML here. There are two major parts of learning ML. 1. Math, 2. Programming. Why math? Math is the most critical part of AI. You must learn math to learn AI. Then you have to start programming. I’ll explain the full process in the next part of this article.

What about RL? Well, learning electronics will help you here. And the rests are the same as ML.

Read Part 2 here.