Disruptive technologies– an umbrella term for technical disciplines that are currently said to transform the digital landscape. The spearheads of this transformation are artificial intelligence (AI), data science, and machine learning (ML). The best part is these technologies are also interrelated. In technical parlance, machine learning is a dynamic application of AI that empowers the machines to learn from data provided and improve the model accuracy levels. And data scientists mine data to extract insights and forecast future trends based on the data collected from machine learning or AI models. However, these technologies seem very complex to a layman. And sometimes a business executive too. Even when setting up to make a career in these fields, it does cause confusion and trepidation about which branch will suit them best. So today, we are going to help you with that.
What are they?
Artificial intelligence is a multidisciplinary technology that involves an attempt to enable machines to execute reasoning by replicating human intelligence. Meanwhile, machine learning is a subsection of AI by virtue of which systems can automatically learn and improve from experience without being programmed by humans. Lastly, data science is the extraction of relevant insights from data. It uses several techniques from many fields like mathematics, machine learning, computer programming, statistical modeling, data engineering and visualization, pattern recognition and learning, uncertainty modeling, data warehousing, and cloud computing. The key difference between these fields lies in the applications. At the same time, AI and machine learning help businesses and other sectors in attaining faster and more error-proof outcomes across different fields. Whereas, data science is used to detect and solve problem points for organizations.
The Talent Supply Index (TSI) study by Belong found out that the demand for data science professionals across varied industry sectors has grown up by 400 percent, in India. In its 2018 edition of the index that data science, Belong noticed that there are more business operations such as product recommendations, targeted advertising, and forecasting demand where the demand for data scientists has shot up by 417% from the previous year. Meanwhile, another report by the ed-tech company Great Learning states that India doubled its artificial intelligence (AI) workforce to 72,000 in 2019 from 40,000 in 2018, witnessing a growth of 200% over 2018.
However, both the studies mentioned that though the demand for these technologies based jobs has catapulted, there is also a deficiency in the market. This implies that now is the perfect opportunity to seek a career in either Data Science or AI or even subsets of AI like machine learning. Even Gartner is suggesting that AI technologies such as AI platform as a service (PaaS), Artificial General Intelligence, autonomous driving, conversational AI platform, deep neural nets, and virtual assistants will be mainstream in the next two to five years. Further, with the rise of AI and Machine learning, the demand for data science roles with proliferate. Let us not forget that candidates in these streams are paid lucrative salaries thanks to the high level of skills it requires to achieve proficiency. In India, the national average salary for a Data Scientist is INR 9,00,000 (US$ 12254.00) while it is INR 5,09,145 (US$ 6932.29) and INR 11,01,531 (US$ 14997.96) for AI and Machine learning respectively.
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