AI will rule the world in the times to come in its truest sense while affecting the daily lives of people, as well as for deciding the fate of the businesses across industries. The disruptive technology has already traversed to multiple industries such as travel, manufacturing, healthcare, logistics & supply chain, sports, entertainment, among many others. It will soon take over other industries and will put them under its reign of immense possibilities.

Ever-Towering AI Revenue Collections

By 2025, a whopping $90 billion will be collected worldwide in revenues generated out of the use of AI across industries. The countries that will experience the biggest impacts would be India and China, while the labor productivity will increase significantly in the Nordics. AI software market, on the other hand, is projected to grow to $59.8 billion by 2025, from a mere $1.4 billion recorded in 2016.

Top AI Skills in Demand in the Global Job Markets

React, Python, Machine Learning, Angular, and Docker are the five most in-demand skills in the AI sector at the moment. Added to that, familiarity and hands-on experience in working with OpenCV, TensorFlow, and neural networks would be a big advantage going for an interview for an AI-based job role.

What is Required from To-Be AI Professionals in Terms of Preparation

Given that the AI career is highly lucrative, it demands a varied set of skills to be learned before breaking into the industry. Here are some valuable tips and skills to consider while preparing for a potential AI career.

Desired Educational Background

Starting a career in AI, you must understand the basics of computer science and coding. A degree in computer science would serve as a great foundation for building a rewarding AI career. For entry-level jobs, a bachelor’s degree in robotics or computer science is preferred over many other degrees pertaining to different subject disciplines. If one happens to be a software developer, or a research scientist, transitioning into the AI domain becomes even more smooth.

Apart from computer science, the other degrees desired by recruiters in the AI sector comprise statistics, mathematics, economics, business, or related subject disciplines.

Develop Advance AI Skills

Artificial intelligence, as a revolutionary technology of the present times, is classified into two major divisions, i.e. strong AI and weak AI. While strong AI deals with complex functionalities that involve mimicking human cognition, weak AI is limited to performing some specific tasks at which it is trained. Strong AI is strongly differentiated from weak AI by its ability to perform tasks without any human intervention or instructions.

To excel in job interviews for AI roles, one must learn as many new skills related to the domain as possible. A few of those comprise deep learning, NLP (Natural Language Processing), statistical, mathematical, reasoning, knowledge representation, pattern recognition, data pre-processing, cognitive science theory, ontology, neural networks, semantic, algorithm design, and physics. There exist numerous AI certification programs that are available online to master each of these skills.

Learn AI-Specific Coding Languages

Being a good programmer is a must to build a successful career in AI and Machine Learning. One must be familiar with the syntax of different programming languages used in algorithm development in the AI domain. Working on an AI or ML project, you will need to apply the coding skills attained from different programming languages. Remember, expertise in more than one coding language is required to be an AI professional.

Some of these languages comprise Python, R, Javascript, LISP, Prolog, Scala, C++, among others. However, Python is the most popular in the current times in the AI sector. Besides, it’s easy to train into and implement. An abundance of Python libraries further helps limit the use of code.

Get Familiar with the Industry-Specific AI Frameworks & Tools

When working on an AI project, you will need to use various kinds of AI frameworks and tools. As an individual starting in the industry, get yourself familiar with the popular AI tools utilized in developing AI projects. Some of these include Microsoft Cognitive Toolkit (CNTK), Caffe, Theano, Keras, SciPy, NumPy, TensorFlow, Apache MXNet, Spark MlLib, and PyTorch. Being an AI industry aspirant, you must understand which AI tool or framework will make the implementation of your code easier.

Hands-on Experience at Building AI Algorithms

Building algorithms is a vital part of day-to-day activities in an AI or an ML job. Each kind of algorithm has its own importance. Every algorithm is different from the other, while some are complex, others are easy to build and develop. Here are the varied kind of AI algorithms you must train into - Naive Byes, K-nearest Neighbor (KNN), K-means, Decision Tree, Linear Regression, Support Vector Machine (SVM), and Gradient Descent.

I hope the article will motivate you to get started with your preparations leading to a rewarding career in the AI domain.

May luck favor you in all your future career endeavors!

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