Artificial intelligence is growing both vertically and horizontally across many sectors and domains. In this article, we explore what AI is, which domains it has made inroads into, and some details on the career opportunities that AI offers to both newbies and hardened professionals with relevant experience.

Man has been on a constant endeavor to build intelligence into the devices he makes, so they do the required tasks independently as possible without human intervention. AI is one such technology that has the power to shape the future of humans. However, as per many experts, AI is still in its nascent stage, and there is a lot left to develop.

More and more businesses are trying to build artificial intelligence into their products to stand out in the marketplace. AI helps them make their products stand out and helps them streamline many processes that are critical to the design, development, and production of the product.

Table of Contents

1. AI for Beginners– A short story of what AI is, for those new to AI and are ready to this complicated beast head-on.
2. Skills Required for Artificial Intelligence – A quick summary of skills demanded of any candidate looking for a career in AI.
3. Artificial Intelligence Career Paths – A brief discussion about career paths and listing of job roles in AI.
4. A Career in Artificial Intelligence in India – Overview of the AI industry for freshers and working professionals.
5. How to Start a career in Artificial Intelligence – A high-level guidance on initiating a career in AI.
6. How to Switch Career to Artificial Intelligence – A quick guide on switching from an existing career to a career in AI.
7. Concluding Thoughts
8. FAQs – Frequently Asked Questions

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What Is AI for Beginners?

Artificial Intelligence, a term that has been around for quite a few years (since 1960 to be precise), more of a buzzword from the early 2000s, does not seem to get old at all, and it doesn’t look like it will for at least half a century into the future.

To a commoner, it will suffice to say that it is intelligence that is exhibited by something human-made. According to Wikipedia, a textbook definition can be appropriated to, “Artificial intelligence is a study of intelligent agents which are devices that perceive the environment and take actions that maximize its chances of successfully achieving its goals. AI is often used to describe machines that mimic cognitive functions that humans associate with the human mind, such as learning and problem solving”.

Before we start a discussion on Artificial Intelligence career paths, let’s look at the types of AI we generally deal with. AI generally falls under two broad categories, namely Narrow AI and Artificial General Intelligence.

Narrow AI

Intelligence in humans is in everything that we do, from watching and learning to carry out the simplest and mundane tasks while being self-aware and the surrounding. This, when narrowed down to a particular function, like image processing or face detection and face recognition, which is subsets of the general or greater intelligence we humans have, is called Narrow AI. Each function of a human being that exhibits intelligence is being replicated in machines to perform specific functions by a machine instead of a human being.

A few examples of Narrow AI include:

• Autonomous mobility or self-driving cars
• Image recognition
• Face recognition
• Chatbots
• Personal assistants on devices like tablets, mobiles, and home automation systems

Machine learning and Deep Learning are ways to achieve this Narrow Intelligence in various domains. Therefore, most of the career opportunities are available for this type of Artificial Intelligence.

Artificial General Intelligence

This type of intelligence is not yet perfected in our world. Still, to define it, we could say, these are machines that can replace a human completely when it comes to being conscious or self-aware, with cognitive capabilities, making it intelligent enough to handle any interaction with its environment, much like the robot Data in the famed television series Star Trek: The Next Generation, or TARS in the Hollywood flick Interstellar.

Related: 101 of Artificial Intelligence (AI) – What to Know as a Beginner?

Industry Penetration of AI

Although AI is making inroads into all industries gradually, industries where AI is making a significant impact are,

• Healthcare
• Customer Service
• Airline industry
• Cybersecurity
• Education
• Marketing
• Retail and E-Commerce
• Financial Markets and Services

Related: 15 Real World Applications of Artificial Intelligence

Skills Required for Artificial Intelligence

There are several aspects of human intelligence that AI seeks to mimic human behavior, like Speech Recognition, Image Recognition, Natural Language Processing, Facial Detection and Recognition, Recommendation Systems. In contrast, conventional ways to program a computer to perform specific behavior closely related to human intelligence like Speech Recognition or Image Recognition, Machine Learning, and Deep Learning are the methods closest to how humans learn by exploring and practicing.

Machine Learning and Deep Learning are two techniques used to achieve Artificial Intelligence.

Machine Learning (ML)

ML is a technique by which a computer can learn from data without using a pre-programmed complex set of rules. Instead, ML algorithms build a model based on sample data or training data, which are huge datasets. These models are then used to make decisions and predictions without explicitly programming the rules, as is done using conventional methods of programming.

Deep Learning

Deep learning is a specialized Machine Learning technique based on Artificial Neural Networks, which is inspired by the biological neural networks that we humans possess.

Does AI Require Coding?

The narrow intelligence that we have prevalent in the industry is based on Machine Learning and Deep Learning, both of which need extensive libraries to handle and process data quickly and easily. So yes, the answer to that question is yes, coding is a requirement in AI.

What Language is Preferred?

Various programming languages can be used for Machine Learning and Deep Learning, but Python is the most popular language. Python is well suited to ML, mostly due to its ease of use when handling datasets. Python is also a preferred language because of its short learning curve.

What is Python?

Python is one of the most widely used programming languages in Artificial Intelligence, thanks to its simplicity, flexibility, and scalability.  You can seamlessly use it with the data structures, and other frequently used AI algorithms. Furthermore, being an open-source programming language helps developers modify and evolve it continually and make syntax easier, contributing to its efficiency. In addition, there are a large amount of in-built libraries that help accelerate AI programming. For example, Tensorflow is widely applied for Mevolving but is; PyTorch for natural language processing. On top of that, python copes well with small scripts as well as easily supports enterprise applications.  In short, it’s the most favorable choice of programming when it comes to AI.

What Should We Study for AI?

• Concepts-Computer Science, Statistics, Mathematics, Machine Learning, Deep Learning, Neural Networks, Distributed Computing
• Programming skills required– Python, R, and Scala.
• Database-related skills-SQL, Apache Spark, Hive, No SQL.
• Frameworks/platforms-Hadoop ecosystem or other Hadoop based big data implementation (like AWS Big Data, MS Azure Big Data), Apache Kafka, Apache Spark

Related: Artificial Intelligence Tutorial – A Beginner’s Guide

Let’s discuss Artificial Intelligence career paths, in the next sections.

Artificial Intelligence Career Paths

AI career opportunities have been on the upswing in the past half a decade. If you have a data-driven mind and have a penchant for improving or transforming existing systems, you are well cut out for the AI world. With almost every industry having a few pioneers who have dabbled in AI already, the demand for AI-related jobs has been ever increasing.

Understanding the job roles in the AI industry will help you understand better the career choices you need to make or the education path you need to take to make it on top of the AI pyramid. The jobs are listed in no particular order or hierarchy, along with the skills required for artificial intelligence.

AI/Machine Learning Engineer/Developer

The key responsibilities of an AI/Machine Learning developer are Statistical analysis, Statistical tests, design, and development of machine learning programs, developing deep learning systems, deciding and implementing a suitable AI/ML algorithm, and training ML systems with the perfect data set.

• Concepts-Computer Science, Machine Learning, Deep Learning, Statistics, Cloud Computing, Natural Language Processing.
• Programming Skills– Python, Scala, and Java.
• Frameworks-Apache Hadoop, Scikit Learn, Spark MLib, H2O, Azure ML Studio, Amazon Machine Learning, Apache Signa