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How to Write Code for Artificial Intelligence

Ivy PedersenJuly 5, 2021
How to Write Code for Artificial Intelligence

We have all seen Terminator, Chappie, and Blade Runner which shows how robots and machines can display human-like intelligence or even supersede humans. This is closer to reality than science fiction these days, artificial intelligence is a field of computer science that studies the theory and practice of developing intelligent systems that are equal to or exceed human intelligence. AI is a broad topic ranging from simple calculators to self-steering technology to something that might radically change the future. It's an exciting time in this industry, with many new opportunities emerging as we move towards a world where AI is everywhere. 

Note: This article will guide you on what you should study in order to start working on your code, this is a general article and would not include many technical details.

Goals and Types of AI

Before getting started with how you can code your very first AI program one should have the basic knowledge of the types of AI and goals associated with artificial intelligence. AI has heavily influenced every sector with us even recognizing that why there are a number of goals regarding AI which can be associated with different sectors, the goals are as follows:

  • Deduction and reasoning
  • Planning
  • Natural Language Processing (NLP)
  • Learning
  • Perception
  • Ability to manipulate and move objects

The long-term goals regarding AI include creativity, social and general intelligence. AI can be classified into three distinct types being weak AI, strong AI, and artificial superintelligent. 

Weak AI also referred to as a narrow AI only focuses on a single task, the AI isn’t self-aware at all, the example of a weak AI is the assistants in our smartphones like Siri or Google assistant. Strong AI is based on a computer and can mimic human-like behavior, this type of AI is called a true AI. Artificial superintelligent is the type that worries scientists and technologists alike, according to them, the AI would be much smarter than the best human minds.

Getting Started

In order to get started one should know how to write code in Python, most people prefer Python because it has built-in libraries which can make machine learning a lot easier. The next thing is to select a dataset on which you will train your AI, datasets are necessary as it acts as the basis for both training and testing. Datasets are generally divided into training and testing subsets, the training set is used for training the AI and vice versa. 

The learning is also of two types, supervised and unsupervised, in supervised learning the program is “trained” on a predefined set of “training examples”, which then facilitate its ability to reach an accurate conclusion when given new data. Whereas in unsupervised learning the program is given a bunch of data and must find patterns and relationships therein. So, in order to start with python, you can visit the following resources:

After getting enough practice on the programming language of your choice you can move onto more advanced topics in machine learning. Builtin libraries like Scikit-learn, NLKT, SciPy, Numpy, and PyBrain you can start writing more advanced ML algorithms. Following are some resources which you can follow to get more information on advanced ML topics:

You can also join AI camps and participate in various AI and BOT competitions in order to test your knowledge against others.

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