PyData Yerevan 2022

How to start critical thinking in Data Science
08-13, 16:15–16:55 (Asia/Yerevan), 213W PAB

The aim of the presentation is to address issues concerning bias in data, misleading statistics, issues in testing and other matters that are prevalent in the field of data science.

The field of data science deals with large amounts of data, requires research and experimentation. The tasks of a data scientist includes conducting data analysis, rigorous testing of multiple experiments, reading research papers and other tasks require analytical skills and critical thinking. This presentation will be divided into 3 main topics: bias in data, misleading statistics and issues in testing. For each topic examples, definitions and in some cases solutions will be discussed.

Prior Knowledge Expected

No previous knowledge expected

Arpine Sahakyan is a Machine learning engineer with a Mathematics background. Specializing in the Computer Vision branch herself, she works in SmartClick LLC. Arpine Sahakyan enjoys working with state of the art models and keeping up with the latest research. Her education background gives her a good foundation for statistical analysis and intuition about data.