USING DATA TO SHAPE DECISIONS
Chris is a Hackwagon graduate and is also from Singapore Management University doing Business. In this feature, we will be talking to him about his current role at Infineon and his thoughts on how data science is changing the business landscape.
I am a student majoring in operations and analytics, with an interest especially in the field of warehousing. The idea of using a set of instructions to logically solve daily operational problems highly interests me, hence I find the use of general-purpose extremely relevant. Currently, I am a Customer Logistics Management Intern at Infineon Technologies.
I first gained interest in general-purpose programming when I was taking a module called ‘Computational Thinking’. Using Ruby as a medium, the module taught me a way of logical thinking to approach problems. After that module, I decided to take on this course, to reinforce my concepts as well as learn more about Python, a programming language deemed to be highly versatile in its purpose.
Many skills are highly relevant in today’s society. Personally, I find knowledge of data science, effective communication and good initiative are skills key to performing well. The importance of data science cannot be over-emphasised today. As the broadest form of data management, it covers a wide range of scientific methods to manipulate data and obtain insights, which is crucial to the success of any company. After obtaining insights, it is important to be able to communicate them to others. This is equally pertinent to good performance but many people undermine the importance of it. Lastly, it is imperative to take initiative and take up learning opportunities where possible. With the abundance of information today, there is always something new to learn each day, and learning should and must never stop.
Currently, I work mostly with operational data, i.e information related to the delivery of shipment. However, the company is shifting its stance towards greater digitalisation in the future. Many initiatives have already been adopted, and it is only a matter of time before everyone has to deal with more data and sieve out the useful ones at work.
I initially expected Hackwagon to be a mere refreshment of what I learnt in SMU. However, Python is a lot more versatile, with new libraries and easily understood syntaxes that really help a person to understand logical thinking better. It also helped me that the homework each week is carefully crafted to challenge me sufficiently without being overly difficult. I am glad I took this course and I am sure it will help me even further in the near future.
DATA SCIENCE TRACK
DATA SCIENCE 101
Build your foundations in the tools-of-the-trade (python) over 7 weeks.
DATA SCIENCE 102
Learn to perform data exploration, visualisation, and machine learning using advanced python libraries.
DATA SCIENCE 103
Learn to build an enterprise level end-to-end data analytics model with a data pipeline.