Looking For A Highly Analytical, Exciting And Lucrative Career? Try AI!
By Kamal Jacob
Once upon a time
People got freaked out when Siri responds to “When is the end of the world?”, with “Whenever they start building that intergalactic bypass”. People used to dread automation thinking it’ll take away their bread and butter. People did not understand how Netflix so accurately could give out recommendations based just on their watch history which was eerie in their eyes. Not that they don’t dread about all this now, but the fear is gradually coming to an end as more people start to shun robophobia and are getting catapulted into the era of AI, short for Artificial Intelligence, which is a science and engineering of making intelligent machines, as John McCarthy, the person who coined the term, puts it.
The big bang in AI
Can you guess around when the concept of machine intelligence came into existence? Did I hear the 80s? The 70s? Well, it turns out that it’s the 1950s when Alan Turing, an ingenious inspiration, proposes the Turing Test as a measure of machine intelligence. Oh, this reminds me of an annual competition called “Turing Test competition” and the associated “The Leobner Prize” which is a mechanism to encourage further research in this field. It has a few different levels of reward and each year a medal and $2000 is awarded to the best entry. A ginormous $100,000 is the reward for the first program that judges cannot distinguish from a real human in a Turing test that includes deciphering and understanding text, visual, and auditory input.
The above snapshot shows Mitsuku, the chatbot in acton. On September 8, 2018, Mitsuku creator Steve Worswick won the 2018 Loebner Prize for the fourth time.
Not surprisingly, quite a few researchers are actively looking forward to bite the gold medal when there are far more lucrative avenues for research. So, get pumped up and make some quick bucks on 15th September, 2019 by winning the next Turing test competition. Grab your favourite algorithm, reload NLP libraries into your holsters and beat the humans. Let’s show them that intelligent machines are no less than humans in being humans.
I’ll let you in on a little secret
Consider yourself fortunate to be born in this Digital era, since you could be the next Peter Norvig or Larry Page of AI. Why? Because there isn’t any yet. No one has yet shown his AI prowess to be as influential as those legends. You are at the right place at the right time, buddy! Felt the adrenaline rush yet? In fact, AI has been described as the ‘fourth industrial revolution’ by Klaus Schwab among other breakthrough technologies just recently, in his World Economic Conference talk in 2016. “The changes are so profound that, from the perspective of human history, there has never been a time of greater promise or potential peril” is one of his popular quotes from the conference.
Ignore the slogans of “AI is overrated”. AI is yet to be emerged in a full-fledged way. That makes now the ideal time for young people like you to build the knowledge, skill sets and connections you need to be AI apocalypse ready and actually implement “join them if you can’t beat them” theory.
Jump on the AI bandwagon
You find computer programming languages complex and hard? Me too. But on the contrary, R and Python are simple and rigid compared to English or Russian. The same goes for understanding the gist of AI concepts (our motive right now) vs actual synthesis and in-depth study of Machine Learning (ML) algorithms (leave these to the AI/ML researchers).
Do keep yourself posted on the AI predictions and statistics by Gartner, IDC and such research companies. Mapping out an AI career path as new roles emerge that focus on problem-solving, collaboration and strategic decision-making is a smart move. Have a look at the latest predictions by Gartner.
You possess that zeal to make an impact on our world? AI offers a truly exciting opportunity to do so. It is an ideal career path for undergraduates, recent graduates, & corporates with a passion for technology and an entrepreneurial spirit who relish a challenge and a front-line role in game-changing innovations like transforming healthcare, contributing to the growing economy, fostering sustainability, providing next-gen education, etc. Name any sector, and you’ll find some or the other AI powered element in it. Given the gamut of possibilities, how does a young person like you go about pursuing a career in the AI field? Let me take you on a roller coaster ride of AI!
The survival kit
1) Unpopular advice: Ditch the engineering degree. Get a degree in Maths or Physics, or even better, a doctorate degree in these fields. You’ll get way more opportunities in job roles that require logical and analytical skills than your counterparts from Engineering department which is because Maths and Basic Science graduates have excellent eye for details and have already worked with several number crunching problems.
Don’t believe me? Have a look at these job posts:
a) Join us- Google AI
b) ML engineer job post
2) The degree curriculum, through textbooks, practicals and assessments, prepare you for the exams and fill you with bountiful of knowledge, but are you ready to face interviews? With the advent of educational websites and MOOCs( Massive Open Online Course) like Coursera, Manipal Pro Learn, among others, you get to build a solid technical portfolio to adorn your resume with along with satisfying your learning appetite!
3) For the primary learning source, what I’d recommend is joining a course like a full-time Post- Graduate Diploma in your favourite AI specialisation like Machine Learning, Data Science, Big Data Analytics, Natural Language Processing, Computer Vision, Robotics, etc., for those who can invest upto a year of time, either online or offline. No substitute for a live interaction with an expert, how much ever advanced the world gets.
4) Bonus tip: If you know MATLAB or Octave, you already have immersed yourself halfway into the sea of AI.
Enough of theory, let’s get practical
A) Our first step is to identify what kind of role suits you the best. For knowing this, you got to explore the different areas, do some RnD on AI trends, get dirty with the stats and data, until you find the one that interests you the most.
a) Data Engineer
b) Decision Scientist
c) Data Analyst
e) Data Scientist
f) Applied Machine Learning Engineer
g) AI Researcher
A newbie in the above roles with not so outstanding academic records or not an alumnus status from a prestigious university would earn about 3-6LPA. The geeky ones would earn about 10X the salary than average in the first few years. Did I pique your interest in AI yet?
B) Attend conferences, meetups and workshops: Learning from others in the field can help improve your skills. These activities give you lot of exposure within few hours into topical areas including ML and data science and can get you onboard with the trending APIs and libraries in R and Python. Websites like AI World Forum provides information on forthcoming conferences.
C) Put reminders for upcoming webinars: There are plenty of technical webinar organisers, one of which is Manipal Pro Learn, waiting for participants like you to absorb all the knowledge that the experts have in their minds.
D) Show your online presence: Flex your ML algorithmic muscles in front of Twitteratis. Be a top contributor in AI reddit threads. Get Kaggle-fied. Create attractive GitHub and LinkedIn profiles showcasing your hacking the hackathon skills gained by nailing Kaggle, Machine hack contests.
E) Build your business acumen:There's an increased demand for a different skill set that includes familiarity with AI techniques as well as deep business and domain expertise. Effective communication is the key.
F) Get your bookmarks ready: KDnuggets is a true nugget with treasure of resources for learning anything related to data science and AI. Subscribing to scientific publications and Data Science dedicated tech blogs like ours keep you updated on the latest news and breakthroughs in AI and other related fields along with tutorials and guides for beginners which enhance your employability.
G) Be unconventional: Follow the footsteps of Siraj Raval, a known face on YouTube, who founded The School of AI that aims to offer a world-class AI education to anyone on Earth for free. Andrew Ng, founder of Baidu, Coursera and deeplearning.ai is another great soul who has taught AI to millions. Sebastian Thrun, one of the leading minds on self-driving cars & flying vehicles. Also, Ray Kurzweil’s predictions and his concepts of Singularity are driving everyone crazy about AI.
1) Sure, majoring in computer science would ensure you get the required hands-on programming skills apart from the logical and analytical skills that you’ll need. But that’s just a part of AI that one would get to use only after a few years of toiling in this field.
2) The online courses with just tutorial videos, however, could be deceptive. They give you an illusion of having learnt quite a lot. Keep those courses as supplements and not as a main source of learning.
3) There are quite a few AI firms, the biggies in AI industry and startups, which give a six figure annual salary and others which shell out over seven figure salary for those who know their algorithm game well.
That’s all the information you’d need to build a successful AI career. For more insights on getting started the right way for AI, check out our Manipal Pro Learn course catalog.