The rapid development of technology has impacted almost every industry and almost all scientific fields. It is one of the catalysts in the biggest innovation from science to business. From editing a human embryo and growing an organ from a stem cell for donations to making medical robots that are 1000 times smaller than a human hair to suffocate tumors and potentially storing the data in our DNA. All of these are just examples of how far one field can go through the aid of technology.
As a graduate with a Biology background, I know how important it is to learn the new trends of technology and in my case Data science (Artificial Intelligence (AI)), Machine Learning and Deep learning). Many types of researches are already adopting AI to approach big problems such as early detection and diagnosis of diseases like strokes or cancer, drug discoveries, and improving the decisions of the doctors for better treatment by building predictive models to treat diseases. These researches have existed for many years, however, big data and the technical capabilities that we have today allow this research be to be done more rapidly and on a bigger scale.
It is very important for me to be well-versed with the skills involved in AI because of the relevant changes that it has contributed to research and development in the healthcare industry. In fact, AI has the potential to provide huge improvements in healthcare quality while reducing costs.
This will open new challenges and opportunities; therefore, I was motivated to look for ways to be able to develop and improve such skills in order to prepare myself for the incoming changes that these technologies might bring. Hence, I enrolled in the Frankfurt School under the Master in Applied Data Science programme. I chose this school not just because of its reputation but also it openly accepts graduate students who don’t have a data science background. Meanwhile, the programme is a perfect fit for individuals like me who don’t have a computer science and business background. The programme contains a combination of subjects that will equip me and other students to become well-rounded data scientists.
In the first semester, we were introduced to courses such as Quantitative Fundamentals, Computational Semantics, Introduction to Data Analytics, Organizational Strategy and the Language of Business. We were able to dive into a deeper understanding of each topic in the course. Furthermore, the programme doesn’t only teach me the math and the programming, it also taught me to have the business knowledge that I need to enter the corporate world because no matter how technical we can get with all the sciences and math, it all comes down to business.
It is overwhelming at first. Imagine encountering terms that look and sounds foreign to you, Greek letters in the formula that you don’t even know. However, in order to grow, we are all meant to struggle, aren’t we? Thankfully, we are a cohort from very diverse backgrounds consisting of 16 people and we embrace our differences by having small workshops that allow us to share what we know to the others so no one will be left behind. In biology, we always say that there is ‘unity in diversity’, and based on my experience, there truly is!
My shift from a Biology PhD graduate to a master’s programme in Data Science appears to be somewhat of a strange move for most people. But well aware of the opportunities that this field provides, I took the risk with a leap of faith and believed that it would all be worth it.
The Frankfurt School Master in Applied Data Science programme delivers excellent training and it is exceeding my expectations. The programme provided the hands-on experience that we need, together with the chance to network with over one hundred different partner companies the University has in order to expose us to the opportunities this programme offers.