Artificial intelligence (AI) today can do things one cannot possibly imagine. From playing music to creating a painting, AI has achieved yet another feat. AI can also predict which of the planetary system will collapse and which will survive in the future.
It has been a decade or so that people started adopting AI, and yet it is still misunderstood by many. It is the same with AI jobs. Artificial intelligence is in its nascent stage, even the world’s greatest scientists and researchers are still figuring out the capabilities of the technology.
Despite the trending technology, only a handful of AI professionals like AI engineers and AI specialists have the expertise to guide the upcoming generation of technology innovators.
Busting the myth about AI jobs
Conversations in AI have developed different views on how the technology will reap benefits while some believe it is destroying jobs.Myth 1: Artificial intelligence jobs are best suited for Ph.D. holders
General AI allows the computers to apply learning in different contexts via problem-solving and autonomous thinking. Whereas AI enables the system to do certain tasks like any other business application. Earlier, only Ph.D. scholars had the capability of doing AI jobs, but with time things changed. In the current scenario, narrow AI jobs are readily available for a candidate with a bachelor’s and a master’s degree in fields related to mathematics, statistics, economic, computer science, engineering, etc. truth be told, many employers are even willing to hire candidates with practical skills in lieu of educational qualifications.
Myth 2: Both artificial intelligence and machine learning are the same
Artificial intelligence helps computer function with the need for human intelligence whereas machine learning is a subset of AI which provides the computer system with data and algorithms through which they can learn by itself without any human intervention. AI is used as an umbrella term covering multiple areas, however, machine learning is just a specific application.
Myth 3: You need a large team to handle AI
Well, this entirely depends on the type of project you’re working on. Large scale projects at tech giants like Google or Amazon may require larger teams, but there are many other projects which can be handled by a single individual. Companies are seeking to hire AI specialists capable of exploring AI strategy, building pilot projects, and one-off consulting.
Myth 4: AI engineers do not code
AI engineers code. They hold the responsibility of taking their ideas into the production level, therefore, coding skills are a must. Recent AI job openings will show that employers require professionals who can code. The major programming language an AI professional needs to master include R, Python, Scala, and Java.
Myth 5: Freshers are not capable of AI jobs
AI jobs are not only one among the most coveted jobs in the tech industry but they’re also one of the best paid in the marketplace. Multiple startups are open to hiring fresh graduates or early-stage professionals to help with their data architects and data scientists. Startups give you the right platform to learn. However, if you’re still unable to find a job as a fresher, fret not, AI certification programs open a new avenue for those looking to expand their skill sets in AI.
Myth 6: Your past work experience is useless while switching to an AI career
An IT professional having more than ten years of work experience in the field of programming, application development, testing, or DevOps is highly suitable for a job in AI. In the same manner, professionals with experience in multiple sectors like insurance, healthcare, e-commerce, and banking will have extensive knowledge about how AI can be applied to their used cases. Past experiences at times act as a differentiating asset for professionals in making a career switch.
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