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 of multiple fields like mathematics, statistics, physics and computer science which looks it difficult to learn at a glance. But systematic learning and the right balance between theory and practice is all you need to make the learning fruitful.

Why do we need to learn AI?

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

Let’s list down the top 3 reasons why you need to learn AI?

1. Because it’s everywhere

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

2. AI is changing the Job Landscape

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

3. Because the opportunities are endless

As per google still, Industries are using 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

In a high level, we can divide the genres of AI application as following

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 flu outbreak before 15 days based on the google search! Can you imagine? This is where the magnitude of change is happening around the world based on AI.

Prerequisites

Basic understanding of mathematics especially linear algebra, probability and statistics is a must. Experience in any of the programing language will be a plus.

Target Audience

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