04/11/2020 – Preporuka za danas

04/11/2020 – Preporuka za danas

Top 5 must-have Data Science skills for 2020. Joos Korstanje. Dec 22, 2019

“R, Python, SQL and Machine Learning” has for a long time been the standard job description of a Data Scientist.

To stay competitive, make sure to prepare yourself for new ways of working that come with new tools:

  • Agile way of working based on the Scrum method. It defines several roles for different people and this role definition makes sure that continuous improvement and be implemented smoothly.
  • Git and Github are software for developers that are of great help when managing different versions of software. They track all changes that are made to a code base and in addition, they add real ease in collaboration when multiple developers make changes to the same project at the same time.
  • Industrialization. What is also changing in Data Science is the way we think about our projects: not only think about the accuracy of your model but also take into account time of execution or other industrialization aspects of your project.
  • Cloud. Moving compute resources to external vendors like AWS, Microsoft Azure or Google Cloud makes it very easy to set up a very fast Machine Learning environment that can be accessed from distance. This asks from Data Scientists to have a basic understanding of Cloud functioning, for example: working with servers at distance instead of your own computer, or working on Linux rather than on Windows / Mac.
  • Big Data.  The second aspect of faster IT is using Hadoop and Spark, which are tools that allow for parallelization of tasks on many computers at the same time (worker nodes). This asks for using a different approach to implementing models as a Data Scientist because your code must allow for parallel execution.
  • NLP, Neural Networks and Deep Learning. The use cases for image classification and NLP get more and more frequent even in ‘regular’ business. At current times, it has become unacceptable to not have at least basic knowledge of such models.

Even if you do not have direct applications of such models in your job, a hands-on project is easy to find and will allow you to understand the steps needed in image and text projects”.


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