Artificial Intelligence – A Field of Study

You are reading about artificial intelligence everywhere. But do you want to find out the artificial intelligence – a field of study? If yes, then continue reading.

We all know this booming industry of Artificial Intelligence (AI). It is a part of computer science, concerned with the designing of human behavioral traits and intelligent computers. Some of these traits include understanding language, learning, reasoning, and solving problems.

You might have not observed but, artificial intelligence is used in our everyday online work i.e., in computer search engines, voice recognition, chatbots, etc. Do you want to pursue it as your career?

Table of Contents

Artificial Intelligence Degrees

A fun fact is that you can become an AI engineer without an AI degree. However, it is better to have at least a bachelor’s degree for entry-level jobs. These degrees can include:

Computer Science Degree
Artificial Intelligence Degrees
Machine Learning Degrees
Robotics and Autonomous Systems
Computational Linguistics
Data Science and Analytics Degree

Skills Required

AI is not an easy field for everyone. You have to develop technical skills along with the knowledge of the latest tools. You should learn at least a few of the below skills.

1) Programming

Programming is the fundamental thing to work in AI – a field of study. You should learn commonly used and high-level programming languages, such as Python, Java, R, C++, etc., to build models.

2) Mathematics

You should be good in some mathematics operations, such as statistics, probability, and linear algebra. If you are not good at mathematics, it is not a problem, but you should be capable to learn and implement mathematics.

3) Big Data Technologies

You should be aware of big data technologies used by AI engineers, such as Apache Spark, MongoDB, etc.

4) Frameworks and Algorithms

You should understand machine learning algorithms along with deep learning algorithms. Examples: are linear regression, Naive Bayes, recurrent neural networks, and generative adversarial networks.

Artificial Intelligence – Fields

1) Neural Networks

AI’s brain consists of neural networks. They function the same as the neural systems of the human brain that’s why they are termed as neural networks.

These machines are staked up by several perceptrons together. The ultimate goal of neural networks is to process and display the final output with the least amount of error and the highest accuracy possible. The technique involves several levels, comprising predictions, error management, and weight updates.

Neural networks don’t understand which data subsets will allow them to translate the input to the most appropriate predictions at the start. As a result, they will become like young children, i.e., they will use various subsets of data and weights as models to make predictions sequentially to get the optimal result, and they will learn from each mistake.

Read the below equation, to imagine the architecture of the feed-forward neural network:

Input * weight = prediction,

Ground truth – prediction = error

Error * weight (contribution to error) = adjustment

2) Deep Learning

The machine engages in learning by processing and analyzing input data through various methods until it identifies a single desirable output. The machine converts input data to output data by using a variety of random programs and algorithms.

Deep learning analyses and witnesses all possible human characteristics, such as emotions, signs, human and animal images, voice recognition, etc.

For example – deep learning helps you group your emails into multiple categories.

3) Cognitive Computing

The artificial intelligence field of study initiates and expedite human-machine interaction for complete job completion and problem-solving. When cognitive thinking is combined with AI, it leads to products with human-like actions and super data-handling capabilities.

Machines just like humans, learn and understand things as a result of practice. Hence, cognitive computing is capable of making accurate decisions in areas where solutions must be improved at lower cost.

4) Computer Vision

Computer vision comes under AI because it allows computers to detect and interpret visual data from real-world images. It also involves deep learning and pattern recognition to extract the visual content from images or video files.

5) Machine Learning

One of the major and top-paid fields of AI is machine learning. Machine learning is based on a, ai characteristic to automatically acquire data and learn from the difficulties. The field of AI known as machine learning focuses on creating algorithms capable of analyzing data and making predictions.

There are various types of machine learning: