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data-speaker [2023/05/30 18:27] – yu.leedata-speaker [2023/06/07 19:44] (current) – scott.chen
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-====== Learning about Data Analysis ======+====== Learning about Data Analysis 學習數據分析====== 
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 Increasingly our world is influenced, shaped, and even controlled by data, specifically data that can be quantified and calculated. From energy efficiency, work KPIs, to Youtube algorithms, data is everywhere. Data gives feedback on current developments and makes predictions about the future. Data shapes and feeds the reality in which we currently live. Increasingly our world is influenced, shaped, and even controlled by data, specifically data that can be quantified and calculated. From energy efficiency, work KPIs, to Youtube algorithms, data is everywhere. Data gives feedback on current developments and makes predictions about the future. Data shapes and feeds the reality in which we currently live.
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 As part of the learning project of this period, the students further practiced utilizing (and collecting) data in scientific ways to discover more information about more accurately understand "reality". We invited Julian Zhan of Deep Insight to speak to us regarding the topic of data analysis. The students learned about where and how data comes from, what it can and can't data show us, the tools and skills necessary to perform data analysis, the programs and code involved in the process, and the difference between "clean" and "dirty" data. More importantly, the students discussed how data can be used to bend or distort reality and the ethics behind the the applications of data analysis, both seen and unseen, in our daily lives. As part of the learning project of this period, the students further practiced utilizing (and collecting) data in scientific ways to discover more information about more accurately understand "reality". We invited Julian Zhan of Deep Insight to speak to us regarding the topic of data analysis. The students learned about where and how data comes from, what it can and can't data show us, the tools and skills necessary to perform data analysis, the programs and code involved in the process, and the difference between "clean" and "dirty" data. More importantly, the students discussed how data can be used to bend or distort reality and the ethics behind the the applications of data analysis, both seen and unseen, in our daily lives.
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