關於 data visualization techniques ，我們在網路上蒐集到這些相關的討論、資訊與評價

《倒數計時》
Countdown to a new semester
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八月的熱風只剩下倒數兩個星期，久違的秋季跟忙碌的學期就在眼前了。
或許一個人的時間有限，在工作與夢想之間、在年紀與現實之間、在飄泊與安定之間，只能奮力拍打水花往前方游去，找尋一個失衡卻跨越時間與空間的立體座標，把那摸不著、如虹似霓的夢想，在擠壓的時間裡真真實實地雕塑出來。
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拜託神明保佑江老師，這學期也能順順利利，在這堂課教給學生更多的東西。老師會全力以赴🔥🔥🔥
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◆ Class: Interface Design﹣From Ideation to Realization
◆ Code: SCG-5837
◆ Time: Tuesdays 6:00–8:00pm
◆ Instructor: Meng Chih Chiang
◆ School: SVA MFA Computer Arts
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◆ Course Description
This course will investigate user experience and user interface with a variety of useful techniques to quickly build up students’ skills. It is divided into three parts. First, we will learn how design can accomplish by essential and futuristic user experience principles, such as the method to create a rapid wireframe and to make an interactive prototype. Second, with fundamental programming syntax, we will explore HTML5 animations, 3D Javascript libraries and interactive effects on the internet. Last but not least, we will focus on data visualization and infographic to enable every individual to transform a large data set into meaningful and beautiful information presentation. Software included: Sketch, InVision, Proto.io, WebGL, HTML5 language tool set, as well as a broad range of data visualization tools that can be extensively used for digital art. The course consists of lectures and presentations, with a short assignment after each session.
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Photograph by Vick

Over the last few weeks, we’ve talked a lot about AI and how it could affect different industries. This week, let’s take a look at the emerging field of data science — a field that is often confused with AI.

“Data science” is attracting a lot of attention these days, so much so that the Harvard Business Review dubbed it the sexiest career of the 21st century! But was exactly is data science? According to Dr Hsuan-Tien Lin, simply put, data science aims at using data to creatively raise questions and answer them. To do this, data scientists use a variety of techniques — from statistics to visualization and outlier detection — to generate valuable insights to questions like “what seasonal trends does my sales data show?” Answering questions like these is the realm of data science.

Data science is often a good first step towards AI. For example, once we know what seasonal trends a company’s sales data shows, we could deploy techniques like machine learning to process these trends and automatically make decisions on when to build up or draw down inventory. Or in other words — AI-powered decision-making.

Interested in connecting the dots between data science and AI? Take a look below for Hsuan-Tien’s thoughts on what it takes to be a good data scientist!