Upgrade & Secure Your Future with DevOps, SRE, DevSecOps, MLOps!

We spend hours on Instagram and YouTube and waste money on coffee and fast food, but won’t spend 30 minutes a day learning skills to boost our careers.
Master in DevOps, SRE, DevSecOps & MLOps!

Learn from Guru Rajesh Kumar and double your salary in just one year.

Get Started Now!

WHY IT IS RIGHT TIME TO PURSUE A CAREER IN AI, ML AND DATA SCIENCE?

Source: analyticsinsight.net

How are the job demands in AI, Machine Learning And Data Science changed recently in India.

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.

Career Prospects

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.

Related Posts

What is Data Pipelining Tools and that are the Different Types of Data Pipelining Tools?

Introduction to Data Pipelining Tools Data pipelining tools are an essential part of modern data management processes. As companies collect more and more data, they need to Read More

Read More

What are Data Engineering Tools?

Introduction to Data Engineering Tools Data engineering is a crucial component of the data lifecycle that involves collecting, transforming, storing, and managing large datasets. With the increase Read More

Read More

What is a data science platform?

Introduction to Data Science Platforms Data Science Platforms have revolutionized the way businesses operate by providing a comprehensive suite of tools for managing and analyzing large volumes Read More

Read More

What are Data Analytics Tools and Why are Data Analytics Tools Important?

Introduction to Data Analytics Tools Data analytics tools are software solutions designed to collect, process, and analyze large sets of data to extract valuable insights. With data Read More

Read More

What is Data Science Platform and Why Data Science Platform is important?

Introduction to Data Science Platforms In today’s data-driven world, businesses are collecting and processing vast amounts of information to gain insights, make informed decisions, and stay ahead Read More

Read More

GET RECRUITED: TOP DATA SCIENCE JOBS TO APPLY THIS WEEKEND

Source – https://www.analyticsinsight.net/ Data science is an essential part of any industry today, given the massive amounts of data that are produced. Data science is one of Read More

Read More
Subscribe
Notify of
guest
0 Comments
Oldest
Newest Most Voted
Inline Feedbacks
View all comments
0
Would love your thoughts, please comment.x
()
x