Data science and AI are two powerful tools that can help decision makers in many different ways.
AI can be used to predict future outcomes, which is very useful for decision makers. It can also be used to optimize the process of making decisions, by reducing the time it takes to make a decision and improving the accuracy of those decisions.
Data science can also be used for decision-making purposes. It is often applied in marketing, where it is used to study customers’ preferences and make predictions about their behavior.
Just how smart AI is? I had the opportunity to participate in an interview on BloxLive recently, about whether we should fear AI or not. Interestingly enough, this topic is becoming more and more popular in the media. Netflix recently released a film called I AM MOTHER where a robot Read more…
This post is coming from Yasmin Chamchoun. A career in data science is becoming highly sought after. With more and more people entering the field, what is that makes ‘data scientist’ such an appealing profession nowadays? Undoubtedly, the field can be very rewarding both financially and through the practical application Read more…
Every year I am teaching social media analytics at the Cyprus International Institute of Management. The course includes topics such as natural language processing, and how to extract insights from social media. Last year I was lucky to have Valerios Paris Mitsakis in my classroom, who did a very impressive Read more…
It is impossible to become a data scientist without programming. However, you don’t have to be a data scientist to use data science! The market around data science, machine learning and analytics has matured enough to the point where there are many products out there to run data science algorithms Read more…
Coaching in business We all know about business coaching. Business coaches help entrepreneurs and executives develop skills and improve their planning and decision making. This help takes place because of two reasons: The business coach has more immediate experience in business, hence is able to provide advice on business planning, Read more…
Black boxes in machine learning I was reading Kaggle’s No Free Hunch blog the other day. It had an interview from Josef Slavicek who ranked 3rd place on the “Flavours of Physics” competition. Something that clearly stood out was that Josef is not a data scientist and he managed to Read more…
Data science and entrepreneurship I have worked with many startups of all stages during my career. This has given me a very good understanding of the various ways that data science and machine learning can be used in an entrepreneurial setting. I’ve seen data science and machine learning being used Read more…
Data science can be a difficult endeavour Data science can be difficult to understand. It is a field that spans a history of more than 100 years, and encapsulates artificial intelligence, machine learning, statistics and other disciplines that tried to solve the problem of extracting useful insights from data. Decision Read more…
Why be data-driven? Data-driven organizations are far more successful than their lagging peers. According to the McKinsey Global Institute, a data driven organization is 23 times more likely to turn prospects into customers, six times more likely to retain them, and 19 times more likely to generate a profit as Read more…
Many ways to become a data scientist Something that many employers are not aware of is that there is more than one path to become a data scientist. Data science, after all, is an umbrella term that encapsulates other fields, such as AI, machine learning and statistics. Since the rise Read more…
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