How to Get Your Career Started in Artificial Intelligence

By Vivek Kumar

Source: PwD Report - Artificial intelligence in India – hype or reality

Artificial Intelligence (AI), Machine Learning (ML), Cyborg Intelligence (CI), and Deep Learning, and more such terms, which were the stuff of science fiction not long ago, are the buzzwords of today. Artificial Intelligence is ushering in a new era of technological revolution, and in the process giving birth to many such jobs that didn’t exist in the past. According to a study by Pew Research Center on future jobs (2014), AI is set to penetrate every aspect of our lives by 2025. Furthermore, according to a 2017 Gartner report, over the next three years, AI will create 500,000 more jobs than it will displace.

A study conducted by Capgemini revealed that out of the 1000 firms interviewed, almost 83% firms leveraging AI technologies have witnessed the rise of new career avenues within their organizations. Thus, this is the right time to get your career kickstarted in the field of AI. Moreover, as an increasing number of organizations across the world start implementing AI technologies, not only will the demand for skilled and trained professionals increase, but it will also make the competition even fiercer. Hence, it is essential for aspiring individuals to develop the right skill set and continually educate themselves about the new technological innovations if they wish to hold their ground in an automated work environment.

Source: PwD Report - Artificial intelligence in India – hype or reality

Skills To Develop Before Diving Into AI

AI is still a developing concept that is both complex and dynamic. So, before leaping into the field of artificial intelligence, it would be wise to gather fundamental knowledge about this branch of Computer Science. Here are the prerequisites for getting started in AI:

Mathematics

Having a strong Mathematical background is of foremost importance for AI. If you are well versed in Mathematical concepts such as Algebra, Calculus, and Statistics, higher are the chances that you’ll be able to understand data and how to go about it. Big Data is primarily about understanding the intricate patterns, trends, and behaviors in large data sets and unraveling meaningful insights from it using a statistical and analytical approach. According to Gary Kazantsev, Head of Machine Learning at Bloomberg,
“Mathematical background—solid grasp of probability, statistics, linear algebra, mathematical optimization—is crucial for those who wish to develop their own algorithms or modify existing ones to fit specific purposes and constraints.”

Data Science

The core concept behind AI is to infuse intelligence in machines and make them capable to ‘learning’ and performing specific tasks autonomously. Data science is a multidisciplinary field that focuses on processes and systems to extract meaningful insights from data. Thus, data science complements and enhances the functioning of AI tools and technologies to find the hidden patterns in data. Having basic knowledge about the primary data science concepts such as regression, classification, ML algorithms, etc. is recommended. Also, one should have a flair for working with high-level programming languages like Java, Python, Scala, R, and C++, to name a few. Knowing a few mainstream AI libraries like Cafe, Torch, and TensorFlow will give you an edge over your competitors.

Intelligent And Creative Thinking

AI demands intelligent and conceptual thinking. One needs to have a keen observation to uncover the hidden patterns and trends in large data sets. Your approach to data should be unique. Creating pioneering AI applications demands a deep understanding of the ways AI algorithms function and their consequent decisions. The lack of this knowledge could reduce AI to a ‘black box’ which could be quite harmful in the wrong environment. Kazantsev further maintains:

“You need to be aware of over-fitting, outliers and other inconvenient properties of your data set, and be able to detect and avoid these issues.”

The Role Of Online Courses

Along with reputed Universities offering courses in AI, today numerous online platforms offer specialized Artificial Intelligence courses. Online certifications and MOOCs (Massive Online Open Courses) are a great way to begin in the field of AI if you do not have the time to attend regular classes. The most significant benefit of enrolling in online courses is that you get to learn at your own time and pace all the while interacting with an active community of peers and instructors.  Not only will the courses offered by these platforms introduce you to the fundamentals of AI, but will also guide you through the more complex concepts such as neural networks, deep learning, machine learning, among other things.

Career Opportunities In Artificial Intelligence

While it is true that AI demands a standard skill set and a background in software engineering (coding, mathematics, computational thinking), many individuals hailing from other fields of specialization also pursue this field. And although the job designations may differ, there are a few core areas in AI that overlap. Thus, the two key factors in landing a job in AI are agility and flexibility.

Image Source: World Economic Forum - These charts will change how you see the rise of artificial intelligence

1. Data Scientist

Salary Range: $130,000 - $210,000

Harvard Business Review declared that the job of a Data Scientist is the “Sexiest job of the 21st century” and rightly so. Data scientists are highly trained professionals who bear the skills of a data analyst as well as a data visualizer. Essentially, data scientists incorporate the best of both worlds - IT and Business.  Analytics being their strongest trait, data scientists combine it with the right set of ML and statistical tools to harness Big Data to the optimal level.

2. Cognitive Software Engineer

Salary Range: $56,027 - $128,095

Ever since IBM’s Watson came to the fore, cognitive systems have gained increasing importance in business ecosystems around the world. While cognitive systems are an integral part of IBM’s business strategies, today, there are a host of smaller companies revolving around Watson. This has given rise to the demand for professionals who are equipped with all the necessary cognitive computing skills that go beyond the basic Big Data concepts. A large part of a cognitive software engineer’s job requires handling unstructured data and hence, they should possess extensive knowledge on machine learning, natural language processing, statistical extraction of entities, search, and so on.

3. IoT Architect

Salary Range: $55,282 - $160,000

As the number of connected devices is increasing exponentially, so is the demand for IoT Architects. IoT architects are experienced professionals possessing strong technology marketing and analytical skills to successfully manage and deliver actionable solutions to complex problems related to cloud platforms, SaaS, IoT, M2M, and security. An IoT architect’s job is to develop discrete and versatile IoT solutions and simultaneously supervise an organization’s IoT infrastructure to extract optimal results.

4. Machine Learning Engineer

Salary Range: $51,000 - $260,000

Machine learning engineers specialize in Artificial Intelligence. They are sophisticated programmers who program machines that can ‘learn’ from behavioral cues and experience, and accomplish specific tasks independent of human supervision. Although computer programming is their forte, they also have a solid Mathematical background and comprehensive knowledge of cloud applications.

Ever since its inception in the 1950s, AI has been a major driver of groundbreaking innovations in technology, be it smart assistants like Siri, Alexa, and Cortana or self-driving cars. As AI continues to permeate our lives rapidly, it is bringing with it new and exciting job opportunities.

About the Author:

Vivek Kumar

Vivek is the President of Consumer Revenue at an online education platform providing industry-oriented courses like Artificial Intelligence in collaboration with world-class institutes, some of which are MICA, IIIT Bangalore, and BITS.

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