About Artificial Intelligence

Artificial intelligence is all around us, and its dominance is spreading fast, and across various industries. Without even knowing about it, you are being exposed to Artificial Intelligence in one way or the other!

Who is an Artificial Intelligence Engineer?

‘Metaverse’ was among the top 10 most-used words in 2022 all over the world.

Hey Alexa, turn off the air conditioning”

“Ok Google, call Mom on WhatsApp”

“Hey Siri, when is the Commonwealth Games starting?”

“Recommended movies since you watched Riverdale!”

Artificial intelligence is all around us, and its dominance is spreading fast, and across various industries. Without even knowing about it, you are being exposed to Artificial Intelligence in one way or the other!

What is Artificial Intelligence?

Artificial Intelligence is the ability of a system to replicate the capabilities of human intelligence.

What does an AI Engineer do?

An AI engineer builds AI models using machine learning algorithms and deep learning neural networks to draw business insights, which can be used to make business decisions that affect the entire organization.

From your home appliances to healthcare, to education, entertainment, transportation, and many other industries, most products today are powered by artificial intelligence.

However, to ‘crack the code’, you must dig a little deeper. Similarly, to understand Artificial Intelligence in detail, you must know the types of Artificial Intelligence.

  • Artificial Narrow Intelligence
  • Artificial General Intelligence
  • Artificial Super Intelligence

But is Artificial Intelligence a good career?

Yes, it is!

Artificial intelligence has been an integral part of the industries in every sector from search engines like Google and Bing, to telecom, to automobiles, social media such as Facebook, Twitter, and more.

The industries hire researchers and professionals that can apply machine learning, computer vision, and data analysis to the existing data to work out the overall growth.

Many of you may get confused between Artificial Intelligence and Machine Learning. They are not the same, and more so, Machine Learning is a subset of Artificial Intelligence.

The International Data Council forecasts that the AI software market in India will rise from USD 2767.5 million in 2020 to USD 6358.8 million in 2025.

Related Departments

Computer Science & Information Technology 14677 Students Shortlisted

Career Prospects

Research Scientist

“Data really powers everything that we do” - Jeff Weiner (Ex-CEO - LinkedIn)

An Artificial Intelligence Research Scientist is an expert in applied maths, machine learning, deep learning, and computational statistics. They spearhead the efforts in performing extensive research dealing with applications of machine learning and machine intelligence.

To be a research scientist in Artificial Intelligence, a PhD degree or an advanced master’s degree in mathematics or computer science is a must. Along with this, you must have significant knowledge of Natural Language Processing (NLP) and Reinforcement Learning.

As a research scientist in AI, you must have adequate problem-solving skills along with critical thinking, and communication skills.

Data Analyst

“Data is like Garbage. You better know what you’re going to do with it before you collect it” - Mark Twain

According to a report by the World Economic Forum in 2021, Data science was identified as the skill with the largest skill gap.

Let’s look at what Data Analytics is and how a data analyst comes into the picture!

Data analytics is the process of finding meaningful patterns in the data acquired in the past to make predictions for the future.

What does a data analyst do?

The major function of an AI data analyst is to perform data mining, data cleaning, and data interpretation. By cleaning data, the requisite data is collected to be interpreted and unnecessary data is discarded to not hamper the interpretation process.

You as a data analyst will work with various statistical tools and methods to draw inferences from the data given.

Machine Learning Engineer

“Artificial Intelligence is in a Golden Age and solving problems that were once in the realm of Sci-fi” - Jeff Bezos (Executive Chairman - Amazon)

Machine learning engineers are involved in building and maintaining self-running software that facilitates machine learning initiatives.

As an ML engineer, you would be working in the areas of image and speech recognition, prevention of frauds, customer insights, and management of risks. Becoming a machine learning engineer means having sound command in applying predictive models dealing with magnificent data. 

Everyone remembers Benedict Cumberbatch playing the famous mathematician Alan Turing in ‘The Imitation Game’. It shows how Alan Turing, the father of modern computer science, used machine learning to break the infamous ‘Enigma’ code of the German Army.

Keeping that in mind, as a Machine Learning Engineer, mathematical and analytical skills come at the forefront. Apart from that, you must also have the capability of handling large datasets and offering a predictive analysis for them.

Data Scientist

How many of you remember the movie - Moneyball?

With the help of a never-been-used mathematical model called Sabermetrics, a baseball manager changed the player-selection process. Data mining and data scientists played an integral role in finding the best-fit players and winning a championship.

Data scientists assist in gathering relevant data from multiple sources to assess it to obtain inferences. The inferences gained help in tackling various issues concerned with the business. Depending upon different data patterns, past and present information, data scientists make various predictions.

To become a data scientist, you must be proficient with modern tools like Spark, Hadoop, Pig or Hive. You must be comfortable using programming languages like Python, Scala or SQL.

Core skills are not the only prerequisite to become a data scientist. Soft skills such as communication skills, and analytical skills are equally important to thrive in this career.

Big Data Engineer

As the name suggests, Big Data is a large amount of unstructured data that adds up after being processed by Big Data Engineers.

To sort the data that is sourced from data lakes (yes lakes, many of them), a big data engineer’s primary function is to manage and maintain big data infrastructures. They also have to carry out the function of obtaining outcomes from big data in a robust manner.

A big data engineer is a professional who is responsible for developing, maintaining, testing, analyzing, and evaluating a company's data.

Big data refers to extremely large data sets. In the modern economy, it is common for companies to collect large volumes of data throughout conducting their business operations.

To become a Big Data Engineer, programming languages like Python, R and Java are essential in building your career in AI. Apart from these, having skills related to SQL and Apache Spark enhances your chances of grabbing the relevant career opportunity.

Similar Careers

Jobs & Salary

Top Industries that provide a scope for Artificial Intelligence -

  • Media and Entertainment
  • BFSI
  • Healthcare
  • Telecommunications
  • Automobile

At the entry-level, the annual average AI engineer salary in India is around Rs.8 Lakh Per Annum and is significantly higher than the average salary of any other engineering graduate. At high-level positions, the AI engineer salary can be as high as 50 lakhs. However, that comes with a certain level of experience, usually more than 8-9 years.

Famous Personalities

Alan Turing - Founding Father of AI

Alan Turing was a British mathematician, logician, and cryptographer. He is often revered as one of the “founding fathers of artificial intelligence and theoretical computer science.”

Alan Turing is best known for his work in breaking the Nazi Enigma code during the height of the Second World War. This, eventually, led to the creation of the computer.

Elon Musk - Founder, Tesla

Elon Musk has been a pioneer in the AI Industry and its growth. Open AI, his non-profit organisation, aims in creating safe artificial general intelligence (AGI) in a manner that enhances humanity, despite the possible risks of AI. The company does groundbreaking research and develops open-source tools for experimentation, such as OpenAI Universe.

Fei-Fei Lee - Chief Scientist, Google Cloud

Fei-Fei Lee is a well-known computer vision professor, and is on a mission to “democratise AI''. This guarantees that talent and expertise are shared outside large corporations to increase diversity, creativity, and innovation. AI4ALL, her non-profit, trains the next generation of AI technologists, philosophers, and entrepreneurs.

Timeline

1942 The Enigma Machine was decoded through AI by Alan Turing.

1950 Test to test released for AI by Alan Turing.

1955 John McCarthy coins the term ‘Artificial Intelligence.

1961 Unimate, the first industrial robot is introduced.

1964 The first chatbot was introduced by Joseph Weizenbaum.

1969 Shakey, the first general-purpose mobile robot was introduced.

1997 Chess Grandmaster Garry Kasparov is beaten by Supercomputer, ‘Deepblue’.

1998 Kismet, the first robot with emotions introduced.

2002 Roomba, the first AI-powered vacuum cleaner is launched.

2011 IBM Watson, a question-answering computer system is released.

2014 Alexa is introduced by Amazon.

Know which career is best for you?

Take Psychometric Test