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Decision Sciences

Decision Sciences or decision-making is one of the branches of advanced management science, and it focus on making decisions and defining suitable policies for various companies and institutions. It also cares about developing the knowledge, machine learning, statistical decision theory, operations research, forecasting, behavioral decision theory and cognitive psychology, tools, and methodologies necessary for projects management, in a way that provides economic and moral addition to the companies or institutions.

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Introduction to Machine Learning

Machine Learning is relatively new field of study that draws on, intersects and overlaps with other fields such as artificial intelligence. It is a technique that relies primarily on data analytics to train computers to learn from experience as much as humans or animals do, or even better.

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The Internet of Things

The Internet of Things (IoT) refers to the fact that billions of physical devices around the world are now connected with the internet. Connecting different objects and adding sensors to them adds a level of digital intelligence to devices that would otherwise be stupid, allowing them to transmit data in real-time without human intervention.

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What Role Has Technology in the Fights Against COVID19?

The spread of the coronavirus globally has been a call to reorganize our priorities and focus on and invest in the fields and industries that will help the human race continue and prosper. Clearly, the coronavirus put the medical and pharmaceutical fields on the spotlight, but not many have recognized the indispensable role that technology played in saving lives.

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Automation

Automated Science is the practice of scientific research without the need for significant human intervention. The goal is to develop “self-driving instruments” along similar lines to self-driving cars. Self-driving cars were enabled by the development of “drive-by-wire” technologies for automobiles combined with advances in machine learning. Drive-by-wire instruments have been increasingly used in science over the past few decades; readily available laboratory automation systems can carry out large numbers of experiments by themselves and such instruments have been critical in areas like genome sequencing and drug screening. However, the choice of what experiments to do using such instruments is typically left to a human scientist. Advances in artificial intelligence and machine learning now make it possible to instead have experiments chosen by an intelligent system in order to improve the accuracy and efficiency with which science is advanced.

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