What, Why, and How of Artificial Intelligence Career in India 
By Kamal Jacob
I would like to start with a question for the readers that what is the first thing that pops into your mind when you think of “Artificial Intelligence (AI)”? The first thing may be Robots or any automated machine or an image of the brain with processing. If it is so then your understanding of AI is appropriate but vague. I am sure you are wondering - what exactly the concept of AI is? In this blog post, we are going to discuss this along with some more important topics like:
1. Applications of AI/ML in various industries.
2. Different areas of specialization under AI
3. Skills a person should have to pursue a career in this field
4. What are the useful resources for self-learning?
5. What are the current job scenarios and salaries in India?
6. Which big companies are using AI and how one can start a career in this field?
Come, let’s dive deeper into the realm of AI.
What is AI?
The hype around AI these days is ubiquitous, and I am sure you are getting the buzz of AI everywhere from newspapers to TV channels. Isn't it? As soon as we start talking about AI, lots of words like Machine Learning, Deep Learning, Predictive Analysis, Natural Language Processing, Machine Intelligence, data science, Statistical Analysis, etc. get popped at us. But, AI is not an isolated discipline, it is an umbrella of every technology that helps transcend human capabilities.
So, are you also getting curious, to unravel the depths of AI? Let's move on and demystify it.
The easiest way to understand AI is in the context of the human brain because we know, humans are the most intelligent creatures of this planet. AI is a broad branch of computer science which aims to create systems that could think & act in an intelligent & independent manner like human beings. In simple words, we can say that AI is the science of mimicking human abilities.
The bigger picture of AI with Machine Learning (ML) and Deep Learning (DL):
Artificial intelligence, especially machine learning and deep learning, set to be the most transformative technology existing over the next decade, started seeping into every aspect of our lives and affecting us in many ways. Chatbots, voice-enabled personal assistants like Siri and Alexa, music & movies recommendations, self-driving vehicles, behavioral algorithms, suggestive searches, instant machine translation are several examples & applications of how AI is in use today, and there are many more to come in the future.
AI, ML and DL is a set of stacking dolls nested within each other. You can also see in the diagram that ML is a subset of AI and DL is a subset of ML.
As you got an insight into AI, ML, and DL, let's move further and dive into the discussion of other important aspects of AI.
Applications of AI/ML in various industries:
Artificial intelligence, machine learning, and deep learning are becoming a disruptive force that is redefining today’s world. With applications ranging from heavy industry to education, the importance of AI technology is being felt across a broad spectrum of industries. Are you feeling electrified to know about some cool applications of AI? Here are five fast-growing industries that are tremendously reaping the benefits of AI:
1. Education: Education is the backbone of a nation. Isn’t it? AI technology is improving education systems by replacing traditional techniques with personalized, adaptive learning to tailor students’ strengths & weakness along with providing extra resources for weaker ones. Augmented Reality (AR) and Virtual Reality (VR) are the realities of immersive learning. AR, a type of software uses device’s camera to overlay digital aspects onto the real world, facilitates teachers and trainers in performing tasks, they previously cannot, in a safe environment. On the other hand, VR takes this one step further by creating a new 360 degree view digital environment. It allows students to interact directly with study material by using e-learning resources on mobile devices.
2. Healthcare: Doctors are using AI-based programs in diagnosis, treatment, patient monitoring, and care. The latest advancement in this field is Google’s Medical Brain, enabled with a new type of AI algorithm, being used to make predictions about the likelihood of death among patients. AI is hugely helping laboratory segment of healthcare, see this example: https://doctorc.in/ai/. Moreover, ML enabled laboratory robots can study new molecules and reactions.
3. Automobiles: Driverless cars or self-driving cars are not sci-fi things anymore. With the advancement in AI technology, it becomes a reality now. AI-enabled autonomous car technology is already being developed by Google, BMW, Tesla, and Mercedes. In India, Tata ELEXSI has developed an autonomous vehicle middleware platform named ‘Autonomai’ which is enabled with deep learning and AI capabilities. It’s not far when we will see driverless cars on Indian roads. Are you interested to see? Taking it to another level, how do you feel if you would be able to travel in air daily? Kitty Hawk, the secretive flying-car startup that’s funded by Alphabet CEO Larry Page, builds Cora with the vision and dream of making people able to travel by air daily.
4. E-Commerce: In this era of internet and e-commerce, all have experience of online shopping. Am I right? But, have you ever realized that sometimes we buy the stuff that is not required at all or we seldom use? If yes, then we are in the trap of e-commerce websites. Selling the stuff even before you realize the need for it, is the new strategy of e-commerce companies. They achieve this via attractive deals, coupon codes, and discounts, based on our personal preferences and various other factors. It is generally called Purchase recommendations or in other words intuitive selling which is purley based on AI and ML algorithms.
On the other hand, Amazon go is redefining the way of doing shopping in supermarkets by using AI, computer vision, and deep learning algorithms. It adds the items automatically in your virtual cart and charges on Amazon account once you leave the store. So, no more line and no checkouts. Amazing!
5. Digital Marketing: What can be one of the biggest dreams of modern-day marketer? Most probably, it can be marketing to the audiences across demographic at the click of a button. Imagine how effective your marketing becomes if most of the time-consuming tasks such as identifying right perspective, generating targeted messages, segmenting as well as targeting audiences, selecting relevant visuals, building a winning content strategy and scheduling the release could be driven without human intervention!
AI and machine learning are bringing this power into marketing automation by using tools like Boomtrain, Phrasee and Persado for email marketing, Adext, an Audience Management as a Service (AMaaS), for handling your ads on platforms like Google AdWords & Facebook Ads, RankBrain, Google’s algorithm for Search Engine Optimization (SEO), Chatbots for providing information to customers and Predictive analysis to identify the probability of future conclusion based on data history.
You may be wondering if AI technology has any application(s) for our day-to-day life or it is meant for future and industrial use only. Friends, look around, you could see and feel AI-powered things and devices. Haven't you noticed yet? No worries, next, here are some cool AI applications that is enhancing our lifestyle.Interested? So, let's begin:
1. Maps and Directions (Google Maps): This feature of your smartphone makes you an explorer. Isn’t it? Now no more fear of getting lost and no more bugging strangers.Let AI help you. Yes, it is AI that directs app like Google Maps to calculate traffic and find the quickest route to your destination.
2. Ride-sharing feature: Open your smartphone and see may have at least one cab service app because it is one of the best ways to commute. Right? Many of us prefer to share our ride with other riders to save on expenses. But have you ever thought,
i) How does your app get a booking from the person going on the same route as yours?
ii) How an individual’s price of the ride is determined in a shared-ride?
iii)How does cab service companies cater to the increasing demands of rides?
All such queries have a single answer: AI and ML algorithms.
3. Virtual Personal Assistants (Intelligent too): Have you ever used Siri, Alexa, Cortana, Google Now? Most of you would be interacting with those apps on regular basis for getting the desired information. Just because of AI and ML, they continually learn information about you to provide you better services. What if I say, you can use Google Assistant to talk to plants, in particular, tulips? Can’t believe but it’s true, Google and Wageningen University and Research team were able to build on Assistant’s existing Neural Machine Translation in order to map tulip signals to human signals. It means Google Assistant now offers translation between Tulipish, added as a language Google Home’s interpreter mode, and dozens of human languages. Hence, users can say, “Okay Google,talk to my Tulip.”
4. Smart Recommendations: What if I say, AI technology is able to anticipate your thought process as well as preferences also. Amazed? You will be more amazed once you got to know that apps like Netflix, Amazon Prime, YouTube, Spotify, and some other similar also, are using AI algorithms to throw precise recommendations of music & movies at you.
5. Video Games: How many of you remember the classic video games like Super Mario, Road Rush, Pac-Man, Virtua Fighter and of course Nokia Snake game? I am sure everyone remembers because we grew up playing them. In contrast, today’s video games like Fortnite, Call of Duty, Grand Theft Auto, Far Cry and many more are empowered by AI algorithms. They are highly realistic as the characters understand a gamer’s behavior, learn from stimuli and change their traits accordingly. This makes players coming back to play again and again. But, how do the companies do it? The answer is by applying hooked model, that uses hooks to connect the user’s problem with the company’s product with enough frequency to form a habit. Every hook starts with a Trigger followed by Action, Reward and Investment. Once the hook is complete, user feel good and it becomes its habit.
6. Humanoid Robots (Robot like humans, for humans): First, I would like to introduce the most famous humanoid robot, Sophia because she is the first ever robot to have a nationality. Yes, you heard it right, the robot with a nationality. Saudi Arabia, in October 2017, granted Sophia her citizenship. This AI-powered robot, developed by Hong-Kong firm named Hanson Robotics, can imitate human gestures, facial expressions and initiate discussion on predefined topics. Astonishing! We can call Sophia ‘a social humanoid robot’ or ‘Sister with another mother!’
India is also not far behind. Rashmi, world’s first Hindi-speaking humanoid robot, is created by Ranjit Srivastava of Ranchi. Rashmi is also hosting a show on RedFM since December 2018. That’s why we can call Rashmi 'The Indian sister of Sophia'.
A career in AI/ML: worth it or not?
If you are having this question in mind and think AI is just a hype, rethink. Check below list of some hard facts about what’s happening in the field of AI/ML:
a) A report from PwC says, AI is reshaping the global economy and as its result, global GDP is going to be 14% higher in 2030. India also woke up to this and built a task force on AI.
b) The same report also says, there would be a challenge in front of companies to fill AI related jobs and 31% of the executives are worried about the inability to meet the demand for AI skills over the next 5 years.
c) By 2020, AI is going to handle around 85% of all customer service interactions.
d) Accenture states that the total number of AI start-ups has increased 20-fold since 2011 and predicts that AI market will reach to USD400B in spending by 2020.
e) The NASSCOM Research report titled “Artificial Intelligence Primer 2018” says that India is stepping up in the AI market ladder and saw funding of USD73Mn in 2017. It also depicts, more than 50% of the firms are working on Advanced Analytics & Computer Vision based AI technologies.
f) Gartner, the world’s leading research and advisory company, says, by 2020, AI will act as a net job motivator and creator. An estimate says, AI is going to eliminate 1.8 million jobs but, in contrast, it is also expected to create 2.3 million jobs by AI in the years ahead.
g) The latest report from the same firm Gartner says “The use of AI across enterprises is ramping up quickly. By 2023, 40% of the I&O teams will use AI-augmented automation in large enterprises, resulting in higher IT productivity.”
Different areas of specialization under AI:
AI is the technology of mimicking humans & making machines ‘smart’. At a basic level, ‘smart’ means to achieve a goal which can be anything like identifying an object, answering customer queries, solving a logical problem, or anything else a human can do (except yoga/meditation).
All the examples, mentioned above, have one thing in common, they come under AI. But, can they be solved by using any single technique or algorithm of AI? No, they can’t be, because each example is a distinct field of study under the umbrella of AI. Here, we are going to discuss such distinct fields of study under AI.
1) Robotics: We can see robots in movies, factories, homes and now even as a citizen like humans. Remember ‘Sophia’ and ‘Rashmi’, humanoid robots? Robotics is a domain in AI, deals with the study of creating intelligent and efficient robots. AI and robotics, branched from the same root, is having a long history of interaction. We may call it an interdisciplinary field of study as Electrical engineering, mechanical engineering, and computer science is to play valuable roles in designing, construction and applications of robots.
2) Computer Vision: How machines can see? Computer vision, one of the most buzzing fields of study under AI, is the answer to this question. Computer vision is responsible for the transition of data from either a still or video camera into an accurate representation. In simple words, computer vision is ‘to extract “meaning” from pixels’. Explosive growth in digital imaging technology makes this field even more exciting and relevant than ever. You will find 3D geometry and recognition as two major themes in computer vision.
3) Pattern recognition: In the digital world, a pattern is everything. It can either be seen physically or it can be observed mathematically by applying algorithms. Pattern recognition, one the important field of AI, uses machine learning algorithms to train machines for recognizing patterns. Presently it is widely used in speech recognition, traffic analysis, and control, stock exchange predictions, classification of rocks, etc. In future, pattern recognition will be employed in almost every facet of life. Some amazing pattern recognition examples are: Amazon Go, Instagram fake comment filter, Flying cars, etc.
4) Artificial Neural Networks: Artificial neural networks (ANNs) is that field of AI which is inspired by the workings of the human nervous system. ANNs are the software implementations of the structure of the brain. Developers and researchers around the world are getting fascinating about it because it is the foundation of one of the most exciting subsets of AI called Deep Learning.
5) Natural Language Processing: If you want to create a chatbot or want to use the power of unstructured text then this field of AI is for you. Natural language processing (NLP) is a branch of AI that is focused on enabling computers to understand, interpret and manipulate human language. In simple words, it is responsible for Human-Computer Interaction (HCI). Python programming language has numerous useful libraries like NLTK, spaCy, CoreNLP, TextBlob to implement NLP. Presently Amazon Alexa and IBM Watson portray the the most creative use of NLP.
6) Natural Language Generation: Natural language generation (NLG), the inverse of Natural Language Processing (NLP), is the field of AI enabling computers to produce written or spoken narrative from a dataset. NLG can mine a large amount of data, identify patterns and share information in a way that is easy to understand for humans. Companies are using NLG for customer service, report generation and summarizing business intelligence insights.
Skills a person should have to pursue a career in the field of AI/ML:
Now, there’s a lot of myth around AI/ML skills - like - “Programming for AI/ML is only for hardcore coders and not for novice”, “I’m bad at math, so I’m not eligible for AI”, “To be an AI engineer requires a nerd mind”, etc. Well, all these myths are really myths. AI/ML skills can be acquired if given proper dedication. With valid efforts you’ll not just be an AI engineer but also the creator of utopian world.
So, to get started, you must have a few essential skills. Let’s know those essential skills to build a career in AI and ML.
i) Python Programing Language: We don’t have any special programming language dedicated to ML but when we compare the characteristics of each language that can-do ML, Python looks superior among them. Even IBM announces Python as the most popular and the best language for ML.
Python has all the ability to do heavy-lifting for us like loading & playing around data, visualizing the data, transforming inputs into a numerical matrix and even assessment. These are some of the basic tasks which a machine learning engineer would do on a day-to-day basis. That's an important step that one must take to be an ML / AI engineer.
ii) Choice of OS (Linux, Windows or MAC): “Fancy things don’t last forever but classic one does”. This also holds true when you have to choose an operating system for implementing AI and ML projects. Don’t go for any fancy OS whose name is never heard before, rather choose from the classics one like Linux, Windows, and MAC. Linux is preferable than Windows or MAC because most of the research around AI is happening on Linux boxes. You can also go with Windows but sometimes you may need to perform a few extra operations on windows, which you can perform on Linux by using few commands.
iii) Mathematical Concepts: Brushing up your math skills isn’t that hard. There are plenty of free courses available online (better than your school math teacher!) which you can learn from. The primary reason for having good mathematical skills is that ML and AI are built on the following:
b) Linear Algebra
c) Probability & Statistics
iv) Algorithms: Algorithms works like seeds, the very foundation to the trees (AI products).
If you want to pursue a career in the field of AI and ML, you can't underestimate the power of algorithms. They are one of the most integral parts of AI and ML. It is very important to understand the logic behind each algorithm, its functionality, and applications. You may assume algorithms as the wetsuit, which you must wear before diving into AI and ML.
v) Data Structures: Are you confident to acquire the skills discussed above? I know you are saying a ‘YES’ because you have strongly made up your mind to walk on AI and ML path. But friends wait, you will have to carry one more skill called Data Structure, with you on this journey. If you want to solve some real-world problems with AI and ML, good working knowledge of data structure, especially its use in solving mathematical problems would be very beneficial in tackling real-world problems using AI / ML.
Your Roadmap on how to be a full-fledged AI/ML Engineer:
“DON’T WAIT. THE TIME WILL NEVER BE JUST RIGHT. START WHERE YOU STAND, AND WORK WHATEVER TOOLS YOU MAY HAVE AT YOUR COMMAND AND BETTER RESOURCES & WAYS WILL BE FOUND AS YOU GO ALONG.”
What a beautiful quote! Isn't it? It encourages us to take the first step, with whatever you have, however, in today's world knowledge is available at the click of a button.
But, taking the first step, with an appropriate approach and useful resources, creates a big difference in achieving the goals. So what might possibly the best approach to be a full-fledged AI/ML engineer?
One of the best approaches is to pursue a certificate program/course that provides you all the required useful resources. Among the most useful resources, to master this cutting-edge technology, are GPU-based labs, real-life capstone projects, and case-studies from industries for practicing. For example, MOOC’s (Massive Online Open Courses) like Manipal ProLearn covers all those useful resources with its in-depth curriculum and practical learning methodology. Courses like these lay heavy significance on fundamentals and helps you build a solid portfolio required for a career in AL/ML. Some courses encompassing these advantages are the following courses: Advanced AI course, Machine Learning course, Deep Learning course, and Data Science course.
Also, once you’ve pursued an extensive course like the one listed above, what next? It’s essential for you to stay connected with AI/ML trends so that you flourish with the community. That’s why I am also providing a list of some Popular Blogs, Useful Textbooks, Tutorials, and Video Channel suggestions that you can visit to keep yourself updated with latest research in AI/ML. Have a look!
Here are the 10 most popular blogs, on AI and ML, that would be very useful as you start your journey to learn AI / ML.
a) Machine Learning Mastery: This blog, created by Dr. Jason Brownlee, is dedicated to help developers get started and become good at applied ML. If you are interested in starting ML then this blog will help you to take the first step.
b) Artificial-intelligence.Blog: What if you get everything you need under one roof? You can expect the same from this blog. It covers everything about AI like news, research, conferences, and books, etc.
c) Algorithmia: Take a moment and think about the smart future, the future with intelligent applications in every sector. If you think such a future is far away, Algorithmia is going to prove you wrong.
d) Machine Learnings: Check this blog if you want to understand, with facts, how AI will change your work and life.
e) MIT News-Artificial Intelligence: If you want to get insight into the achievements, in the field of AI, of students and the staff, of one of the most prestigious universities of the world, MIT-Massachusetts Institute of Technology, then follow this blog. It also covers news on the latest trends in AI and different areas of AI application.
f) AITopics: Do you think AI-enabled machine will provide the best content to you? If No, then check this blog. I am sure, after this, you will change your answer. It is an ultimate source of best and latest AI news collected by scanning several trusted websites by NewsFinder, an application of AI itself.
g) Chatbots Life: Want to build your own chatbot? If yes, then this blog is for you. This blog is having everything from tutorials to tools for learning as well as building chatbots. What if I say you can even start a project here? Exciting?
h) Chatbots Magazine: Imagine chatbot with a cap and you will find this blog as another feather in its cap :). Along with learning, you can also share your knowledge with the community by writing an article here.
i) Open AI: This is the perfect blog to know about the research work in the field of AI and ML. The research work available here is free to access.
j) Google AI Blog: Are you interested to know how Google is incorporating AI and ML into its products? I know your answer, of course, it’s a Yes. Then this is the perfect blog where you can get a glimpse into the Google AI team’s research and thought process.
Books are one of the primary sources of knowledge and will always remain. That’s why here is a list of insightful books for beginners in AI and ML:
1. ‘Machine Learning’ by Tom M Mitchell, is one of a great introductory book that takes you to the world of ML.
2. ‘Artificial Intelligence: A Modern Approach’ by Stuart Russel and Peter Norvig, provides an overview of AI to the beginners. This book covers almost all topics, from basic to advance, of AI.
3. ‘Programming Collective Intelligence’ by Toby Segaran was written long before ML acquired the cult status, but the topics are relevant even today.
4. ‘Pattern Recognition and Machine Learning’ by Christopher M. Bishop, shows the use of statistical techniques in machine learning and pattern recognition.
5. ‘Superintelligence’ by Nick Bostrom is a thought-provoking book and I consider this a must-read book for everyone who is already working in AI/ML field or thinking to pursue a career in the same. The author in this book lays down a future scenario where machines acquire the superintelligent stage and deliberately or accidentally lead to the extinction of humans.
Wikipedia says “A tutorial is a method of transferring knowledge and may be used as a part of a learning process. More interactive and specific than a book or a lecture, a tutorial seeks to teach by example and supply the information to complete a certain task.”
You will find it precise in every aspect once you go through the following interesting tutorials on ML:
1. kaggle.com (Machine Learning Tutorial for Beginners)
2. machinelearningmastery.com (Applied Machine Learning Process)
3. pythonprogramming.net (Practical Machine Learning Tutorial with Python)
1. Github: Another deep well of knowledge for AI is GitHub. Most of the new AI-related projects are open sourced and available on GitHub. There are many educational resources, providing example algorithms implementations in Python, on GitHub too. Below are the links to some useful reports.
1. Machine Learning
2. Deep Learning
3. Neural Network
2. Podcasts: Listening to the podcast is to gradually transition into your phase of learning. You can master your basics while listening on podcasts, by moving back and forth between your basics and transitioning. Isn’t it?
1. Learning Machines 101 is a free podcast on the fundamentals of AI and ML. From episode transcripts to technical concepts, it covers various topics like ‘How to Represent knowledge using Logical rules’, ‘How to Build a Machine that Learns Checkers’ and many more.
2. The AI Podcast connects you to the leading experts in AI, machine learning, and deep learning to explain how it works, how it’s evolving from art to science.
3. This Week in Machine Learning and AI, hosted by Sam Charrington, gives you insights into the field of AI and ML.
4. Artificial Intelligence in Industry provides the interviews of top AI and machine learning executives, investors, and researchers from companies like Facebook, eBay, Google and many more.
5. Machine Learning Guide is for those who are intermediates in this field. You can learn high level fundamentals of AI and machine learning here.
3. Popular YouTube Video Channels: One of the emerging ways of learning in this age of the internet, is YouTube. Check the list of the 5 most popular YouTube video channels on AI and ML below and think again.
1. Siraj Raval’s School of AI: School of AI, is one the fastest growing community on YouTube with a mission to teach AI, ML and use it for the benefit of humanity.
2. Artificial Intelligence-All in One: This YouTube channel is having very useful video lectures from prominent experts on AI, ML and even other computer science topics.
3. Sentdex: If you want to learn some advanced programming stuff in ML with Python then this is the perfect YouTube channel for you. It has more than 1000 videos on Machine Learning, Robotics, DataScience, Game Development and on many more exciting topics.
4. Luis Serrano: Mathematical concepts are essential to learning AI and ML. Agree? But what if you are not so good in mathematics? Not to worry, you can learn from Luis Serrano through YouTube. This channel has many videos to demystify complex topics on mathematics, ML and AI.
5. Data School: One of the best YouTube channels to learn data science, the most widely used techniques among AI and ML using Python. It provides in-depth video lectures on data science that anyone can understand regardless of their educational background. So what are you waiting for, go check it out!
Artificial intelligence job profiles
What kind of job should you start looking for once you get the right skills? Let’s have a closer look at the 5 most-in-demand jobs in the AI industry right now.
1. Machine Learning Engineer: Machine learning engineers, responsible for building and managing platforms for machine learning projects, are most sought after. To get hired, it will help if you have the skills such as NLP, applied math, statistics along with working knowledge of leading software development IDE tools like IntelliJ and Eclipse.
2. Data Scientist: Data scientists are primarily involved in collecting, analyzing and interpreting large datasets by using machine learning and predictive analysis. Chances of getting hired increases if you have a good hand-on-experience working with machine learning, cloud tools like Amazon’s S3. Strong analytical and good communication skills also play a vital role in data scientist's career as he/she requires to collaborate with marketers and product developers.
3. Research Scientist: The role of a research scientist is to work on ground-breaking research to solve pressing problems in the realm of AI and ML. For this role, companies are on the lookout for technology professionals who possess an in-depth understanding of multiple AI disciplines like applied machine learning, deep learning, natural language processing, and computational statistics.
4. Business Intelligence Developer: It is one of the leading artificial intelligence careers. The main goal of a business intelligence developer is to analyze complex data sets for identifying business and market trends. To be considered, a candidate should have considerable experience in data mining, SQL queries, SQL Server Reporting Service along with knowledge of AI and ML.
5. Computer Vision Engineer: Computer vision engineer role is to create algorithms for recognizing patterns in images. To get hired, a candidate should have in-depth knowledge of Neural Network and Machine Learning algorithms. Having working experience in Python, OpenCV and other related tools will be an added advantage to the candidate looking to pursue a career as a computer vision engineer.
Current job scenario, salaries and future scope of AI in India
In recent years, the demand for AI and ML has increased many folds and hence changing the future of IT jobs very rapidly. The recent developments in India have shown, people willing to work in this field get the support they need. NITI Aayog, the government think tank, also released a paper titled ‘National Strategy for Artificial Intelligence’ with an overarching vision of implementing AI innovations in the social sector.
It is heartening to see artificial intelligence is high on the agenda of the Indian government and got a place in Union Budget-2019 too. The interim Finance Minister Piyush Goyal in his Budget Speech 2019 announced that a national AI portal will be developed by the government to harness the benefit from new cutting edge technologies.
Everything above is pointing towards a bright future scope of AI in India. Some good findings below will help you build even more trust in the future of AI in India:
a. India ranks 3rd in Salesforce Asia-Pacific AI Readiness Index.
b. In an analysis published by research agency Itihaasa, founded by Kris Gopalakrishnan, former CEO & co-founder of Infosys, India also ranks 3rd in the world in terms of high-quality research publications in AI.
c. AI has the potential to add US$957billion to India’s economy in 2035, a report “Rewire for growth” from Accenture said.
d. At AI for Social Good Summit held in Bangalore on 26th March 2019, Facebook announced numerous social initiative in AI for India including women-led AI startups, 100 scholarships for projects in AI and creation of an innovation accelerator focused on AI for social good.
e. CBSE introduced AI as a new optional subject at class IX in session 2019-20.
Now, let’s have a closer look at the current job scenario and salaries in the field of AI.
A recent study by Analytics Magazine reveals a substantial growth of nearly 30% in the AI industry in last one year. According to this study, in the AI industry, 4000 positions, that doesn't include new jobs being posted every month, at mid and senior level are vacant for the last 12 months. So, because of this significant gap in supply & demand, there is a huge opportunity for mid and senior-level professionals who are looking to transition into AI.
Similar findings have also been corroborated by India’s leading job recruitment and online job portal like ‘Indeed’ and ‘Teamlease’. A report from Indeed says, since the start of 2018, employer demand for AI skills has been consistent twice the supply of AI skilled employees.
According to Teamlease, there will be a 25% rise in the roles related to business analysis, big data, and analytics. Alka Dhingra, GM, IT staffing at TeamLease Services said, “The growing opportunities in the digital technology arena including government initiative like Digital India will add jobs in digital technologies, AI, robotics. The IT industry is expected to add around 1.8-2 lakh jobs this year.”
Salaries and perks are nothing in front of being passionate about your work, but the truth is that salary, like passion, is also an important aspect of the career. The same research collected by analytics magazine also reveals the curtain from the salaries of AI professional in India. It says,
i. The average salary of AI professional in India is ₹14.3 lakh per annum across all experience level and skill sets.
ii. Entry-level salary of around 40% of AI professionals is ₹6 lakh per annum onwards.
iii. At the senior level, nearly 4% of AI professionals command a salary of ₹50 lakh or higher annually.
Best cities in India for AI working professionals
The Analytics Magazine survey also gives us an insight into the best Indian cities having considerable potential for the growth of AI professionals. In a city-wise remuneration comparison, Mumbai is at the top with almost ₹15.6 lakh per annum, followed by Bengaluru with almost ₹14.5 lakh. Chennai, with ₹10.4 lakh per annum, is in the third place.
In terms of percentage share of AI working professional, Mumbai holds the first position while Bengaluru is in the second position with 32% of all AI professionals. In the region of Delhi-NCR, there are around 22% of all AI professionals.
Companies (including startups) hiring AI professionals
Amazon, Google, Adobe, IBM, Facebook, Nvidia, UBER, Accenture, and Microsoft, are some of the leading organizations having a high demand for AI professionals all over the world. But remember, other companies are also there than these big tech giants. Just because these big companies are hiring lots of AI professionals, doesn’t mean you would be a perfect fit. There could be lots of smaller companies as well as startups in which you would fit way better. On the demand side, several Indian AI/ML companies are also hunting for talent to overcome the big demand-supply mismatch. Below is the list of top 15 AI and ML companies of India, including startups also, who are looking for AI professionals.
d. Uncanny Vision
e. Innefu Labs
j. Mad Street Den
k. Artivatic Data Labs
l. Fluid AI
n. Iken Personics
How to kick start a career in AI
Are you thinking to start a career in AI? If so, then this is the right time because the AI industry is at the perfect stage to give you a rewarding career. But, before land your dream job in the AI industry, you must come out from the safe bubble of theoretical knowledge and get some practical knowledge. To get practical knowledge in any field, the most useful ways are Projects, Internships, Courses & Certifications. Let’s check out them for AI and ML:
1. Courses & Certifications: Online paid courses have a lot of advantages over free courses. This is because the intensity with which the curriculum is designed and taught is ingenious. Also, it’s always best to do an integrated advanced course online than reading random blog posts from blogs. Fortunately, you don't need to spend many years of your life studying at university to become familiar with complex technology. In recent years, a growing number of online courses have sprung up, covering everything from basics to advanced level. Below is a list of best 6 free online courses available today.
i) Learn with Google AI
ii) Advanced AI Certification
iii) Machine Learning and Data Science Course by Manipal Pro Learn
iv) Standford University-Machine Learning by Andrew Ng
v) MIT-Deep Learning for Self Driving Cars
vi) Amazon Machine Learning
2. Projects: Doing projects is one of the promising ways to let the community know you have technical command over the subject. On the other hand, it helps you to build your own personal brand, makes you worth hiring. Getting into the leader boards of Kaggle is one of the great ways of doing so. It would be very useful, to get you onboard, if you have at least three GitHub projects available for the employer to see.
3. Internships: Internships are proven ways to gain relevant skills as well as experience while establishing important connections in the field. Isn’t it? Internshala is one such platform where you can check about the internship, free as well as paid, openings. Professional networking site, Linkedin, can also be very handy to get an internship. Amazon, GetVocal.ai, Vahan, Haptik.ai are among some top AI/ML companies providing internships for the candidates.
Artificial intelligence is no longer a sci-fi term, it’s a reality now. Industries are deploying AI, ML, and DL for a more practical, profitable and productive solution. The hype surrounding AI’s potential forced us to notice its current utilities. AI applications are in our lives today and are set to be more invasive in the near future. AI, still in its infancy stage, needs to cover the long path to reach the superintelligence level of human.