The Artificial Intelligence tutorial is the set of resources and training materials to set the course of your data science journey. Artificial Intelligence is an interdisciplinary field that combines concepts from multiple fields like mathematics, statistics, physics, and computer science which looks difficult to learn at a glance. But systematic learning and the right balance between theory and practice are all you need to make the learning fruitful.

Why do we need to learn AI?

Artificial Intelligence is changing the world in every aspect. It is now a fact that ‘Data is the new oil’ from the end of the last decade. Artificial intelligence is driving business and innovation from manufacturing, communication, Insurance, heavy engineering, and defense to healthcare.

Here are the top 3 reasons you need to learn AI.

1. Because it’s everywhere

With the boom in cheap data rates and indefinite bandwidth, AI has become an integral part of our day-to-day life. Do you ever wonder how ecommerce giants like Amazon, Flipkart, or entertainment giants like YouTube and Netflix recommend your taste with utmost accuracy? In the literacy of AI, this is called recommendation systems. Amazon’s Alexa, and Apple’s Siri are some examples of the advancement of Natural Language Processing. Transport, Insurance, and Healthcare AI is everywhere.

2. AI is changing the Job Landscape

Days are gone when companies with higher revenue generate more jobs. AI is creating new job profiles every year by changing traditional job roles. For example, if you no longer need a support team for 24/7 support. Chatbots are replacing manual intervention. Indian fashion giant Myntra even started designing their outfit with state-of-the-art deep learning models instead of fashion designers. One interesting job perspective of AI is any domains do not bind the applications.

3. Because the opportunities are endless

As per google, Industries still use only 50% of structured and 1% of unstructured data for business insights. So it is certain that more and more carriers from different sectors will involve in the digital transformation, which is a great opportunity for IT vendors and technology professionals.

Applications of AI

At a high level, we can divide the genres of AI applications as follows

Machine learning.
Computer vision.
Natural language processing and machine translation.
Unsupervised learning and cluster analysis etc.

Example

Google has developed a model that can predict a flu outbreak before 15 days based on a google search! Can you imagine? This is where the magnitude of change is happening around the world based on AI.

Prerequisites

A basic understanding of mathematics, especially linear algebra, probability, and statistics, is a must. Experience in any of the programming languages will be a plus.

Target Audience

Professionals for this field come from various domains like mathematics, statistics, engineering, management, etc. Therefore, anybody interested in pursuing a career in AI or genuinely wants to know about various domains and applications of AI can go through the tutorials.