Data science is becoming one of the hottest professions in the world today, or is it? Most demanding courses in the world now. With the ascension of artificial intelligence in the modern world, we look towards getting other new tools and advancement in technology.
Data Scientist are getting more and more faded as more job opportunities are being created by the ever-growing machine learning tools. Artificial Intelligence is a huge part in the development in the industry for such a short period of time.
“Data Science will probably fade into the background because more tools are becoming available,” said Kathleen Featheringham, director of AI strategy and training at management and IT technology consulting firm Booz Allen Hamilton. “To me, it’s like website design years ago when you had to have people who really like code, but now you can go online and use a tool that will build your website for you.” Experts predict the downfall of data science in the world.
Questions Data Scientists should ask themselves is whether AI and automation will replace data scientists? well predicting the future of Artificial Intelligence requires deep understanding of the past. The infancy of data science which include analytics or stochastics that incorporated probability theory and analysis into programming. The R language emerged as an open-source equivalent of SASS and SRS, two ancient analytics packages that trace their lineage back to Fortran. Python’s incorporation of similar packages made it the go-to language for combining the results of such data analysis with other components and is still the most preferred language for perfecting results for analysis.
These gave way to visual pipeline tools such as Alteryx or Microsoft BI, which reduced the need for programming experience, yet required enough understanding of statistics to know what these packages were doing. It is unlikely that the need for competency will ever go away.
Quantum Computing which is the exploitation of collective properties of quantum states, such as superposition and entanglement, to perform computation and Quantum Information Science is a field that combines the principles of quantum mechanics with information science to study the processing, analysis, and transmission of information and are still at their infancy, but they represent a new market for Data Scientists. “If you’re doing a calculation on a classical computer and you have a bunch of initial inputs, you have to run them one at a time. On a quantum computer, you can run them through at the same time,” said Patty Lee, chief scientist at Honeywell Quantum Solutions.
“You can’t just take a classical computing algorithm and plug it into a quantum computer. You have to come up with new algorithms that take advantage of quantum mechanical properties and then you can extract the information out of your data that way,” she said.
Quantum data scientists must understand quantum mechanics and how to use a quantum algorithm to solve a particular problem. “We need a lot of people to be in that space because there are people in the application side of businesses and quantum theorists who are well-versed in the quantum algorithms. We need someone in the middle to do the translation,” Lee said.