学术报告-what should be avoided when working in data science

发布时间:2018-03-26浏览次数:10

摘要:

The presentation will focus on 'what should be avoided when working in data science'. Instead of describing more concrete state-of-art methodology and techniques related to advanced data analytics, the topic will mainly cover the easily missed-out things/blind points when working in data science area. All the arguments will be discussed with the combination of with working experience in the reality. It is often the case that before reaching the conclusion, the general process of data analytics normally involves some frustration and mistakes to some degree since there are always some misleading factors, which could be easily generated by inappropriate estimation, lack of domain knowledge or sample bias etc. Thus, the purpose of the presentation will provide the audience a slightly different view of how to think and what are the common mistakes need to be taken care of to avoid a misleading result in a real working context. The second half part of the presentation will use a real use case from the work to demonstrate how theory and empirics work when conducting a data analytics project. 

  

主讲人简介:

Zhixian Bao was enrolled in Donghua University the year 2009 and accomplished a bachelor degree in Mid-Sweden University. She got master study degree in Telematics department in Norwegian University of Science and Technology in Trondheim afterward. Currently she is working as a software developer in Spectrum Acquisition and Analytical Decision Support in Telenor Group. She works in the Group Finance function, mainly responsible for spectrum investment analysis and strategic decision support across all the operational markets. Formerly, she was working as a data scientist/big data consultant in Sigma ITM. During such 1.5 years, she dedicated a lot into data science/analytics for industries such as media, adtech, fintech, etc. She has been responsible as the project lead for several projects from the leading industrial companies at that time.


时间:329日下午100

地点:一号学院楼140报告厅