Over the past decade, no technological advancement has gained more popularity than artificial intelligence. From Alexa to self-driving cars, we can find artificial intelligence in almost everything today. Simply put, it is the center of many amazing technology devices and applications that we use.
While a lot of people fear that computers will take over the world, a career in artificial intelligence is certainly the best thing that you can achieve. With more demand for advanced research, the supply is rather low. Hence, what is better than choosing a career option that totally needs you?
In this article, we will understand how you can master artificial intelligence.
What Is Artificial Intelligence?
Artificial intelligence refers to the study of making computers intelligent and training them to perform tasks just as humans would do. These tasks may include decision-making, visual perception, speech recognition, and even translation.
Here are the reasons why you should choose artificial intelligence:
- AI is a challenging yet exciting domain. Just think about it, how great it would be to work on chatbots and personal assistants. The journey in itself is extremely thrilling.
- Currently, there is a high demand for qualified professionals in this field. Additionally, the good news is that this demand is not decreasing any time soon.
- The pay scale of artificial jobs is amazing. It is a well-paid career if you are good at it.
How to Become an Expert In AI?
If you have an interest in artificial intelligence but worried about how to proceed, we have made a stepwise guide to assist you.
1. Knowing the Value!
Although artificial intelligence is a great career option, we still believe that you need to have an interest in the field. You should know coding, algorithms, and other AI tools. Without the will to learn all these things, it might be harder to penetrate the market.
2. Learning Concepts
To become an expert in artificial intelligence, you need to learn a few concepts. Let’s see what are these concepts.
- The first thing you need is mathematics. This involves basic mathematics such as matrices, vectors, and transformations. Then, move on and understand statistics and dimensionality. After both these things, the probability is your go-to concept. This would include Bayes theorem and AI algorithms.
- Now, every artificial intelligence professional needs to learn one programming language at least. Most go for R or Python but you need to have knowledge of JAVA as well. Just remember that programming language makes your life easier when we are talking about artificial intelligence. It is not a burden but a blessing in disguise.
- To know the type of system you need to develop for solving a particular problem, you need data structures. Knowledge of data structures can assist you to accurately reach an optimized result.
- Every person who is even remotely related to artificial intelligence will tell you to learn regression. It is a simple concept of mathematics which can help you with future predictions.
- After all these concepts, move to some of the machine learning concepts such as KNN, SVM, random forests, etc.
3. Understanding Deep Learning
Once you have understood machine learning and other AI concepts thoroughly, it is time for some deep learning knowledge.
- Understanding how algorithms are used to make a neural system intelligent. You need to know how decisions are made by adding new information.
- Neural networks have a huge amount of mathematics going on in the backend. Understanding these processes is necessary to gain expertise in artificial intelligence. This will, in fact, help you to design networks yourself someday.
- Learn different fields and types of neural networks such as recurrent neural nets, LSTMS, multilayer perceptron, etc.
- Gain knowledge of other related domains such as NLP (Natural Language Processing), as these fields are connected to AI.
Focus On The Application
The last step to mastering artificial intelligence is applying this knowledge practically. Unless you practically implement things, connect with other people in different communities, and read the research papers, all this knowledge would be for nothing. It is a lot different to learn something and implement it in real life. Hence, the main aim should be to apply your learning to create artificial intelligence apps, programs, and products.