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Data Literacy for Working People by a 17-Year Data Scientist (~Application Deadline 3/13)
"If you chose a place for a company dinner after gathering your colleagues' food preferences, considering whether it's close to your company, and considering the restaurant's reviews, you can naturally say that you used your colleagues' food preference data, map data, and review data to make your decision.
Actually, using data is surprisingly easy. Even deciding whether to take an umbrella with you today after reading the weather forecast can be considered a data-based decision.
The same is true at work. It’s not just data analysts or data scientists who can use data. Data is already being used to make decisions in all occupations to some extent, such as using data to figure out inventory or checking if users are using the app well.
I've been thinking a lot about how to plan my March seminar lecture. In this lecture, I'll focus on 'how to use data better' and 'how to use data correctly.'"
_ Data Scientist Jeongmin Kwon (Kkojet) with 17 years of experience
Go see Kwon Jeong-min's lecture
👉 http://bit.ly/3kmIEjK
The theme of the March monthly Datalian seminar is ‘Data Literacy for Office Workers: Using Data in My Work.’
1️⃣ How Office Workers Use Data
In the first part of the seminar, data scientist Jeongmin Kwon, author of 『Data Scientists, People Who Weave Data』 and 『Data Analysts’ Regrets About Numbers』 and a 17-year veteran data scientist, will give a talk titled ‘How Office Workers Use Data’ about data usage methods that office workers should know.
2️⃣ How can I use data in my work?
In Part 2, a panel discussion will be held under the title, “How can I utilize data in my work?” We will discuss what planners, marketers, and designers can do to better view data in their companies. We will divide the discussion into “companies with data analysts,” “companies without data analysts,” and “companies without even data,” and discuss what each company can do.
If there are still those who feel that ‘big data’ and ‘data analysis’ are too far away from you, don’t miss the March seminar where you can become a little more familiar with data.
⏰ Application deadline: 3/13 (Mon)
(A replay will be provided to all who apply)
http://bit.ly/3kmIEjK
Free