The transition from academia to data science with Mehmet Apsalan
The Data Standard
Being a great data scientist is mostly about the way in which you approach problems. Data scientists apply the scientific method in the commercial environment, which is why scientists can often successfully transition into the field. This sounds simple enough in theory, yet many scientists with superb academic backgrounds find it difficult to make the move into industry. We reached out to Mehmet Alpaslan leader in the data science and analytics communities who made the leap from academia to industry and asked for his advice on how he transitioned out of academia and into the data science industry.
Meet The Host
Podcast Host at The Data Standard
I believe that I can make a difference right now through research and innovation.
Meet The Guest
Clinical Research Scientist at Imagen Technologies
I have over 10 years of experience in performing complex statistical analysis on large data sets using code I write myself in R, Python, C, Fortran, and SQL; as well as in mathematical and statistical methods (including supervised and unsupervised machine learning methods). My current work focuses on building machine learning models using computer vision, NLP, and deep learning. For a full list of my publications, please visit https://bit.ly/2Kra3Mf