What is Data Science

Data science combines math and statistics, specialized programming, advanced analytics, artificial intelligence (AI), and machine learning with specific subject matter expertise to uncover actionable insights hidden in an organization’s data. These insights can be used to guide decision-making and strategic planning. from IBM 'What is Data Science'

Data science = statstics + informatics + computing + communication + sociology + management

data + environment + thinking (Data Science: A Comprehensive Overview, ACM Computing Surveys, 2017)

Data product is the output of data science

Improving your academic talk

데이터 사이언스 실험실의 주요 목적 중의 하나는 지식과 아이디어를 전달하기 위한 여러분의 academic talk 활동을 향상시키는 것입니다. 국내외 전문가를 위한 Academic talk는 다음과 같은 요소를 시간과 장소에 따라 적절하게 포함되어야 합니다.

• Title: This is the first item somebody will check if your talk is worth their while. A title should be short and still capture the essence of your presentation. Detailed presentation can be expressed in a subtitle.
• Abstract: People interested in your title will read your abstract to figure out if your talk is worthwhile. Therefore the abstract needs to be well crafted, interesting and to the point. It should include the following information:
  1. Introduction: What is the underlying problem? Characterize the state of the art.
  2. Motivation: What are the challenges? What makes it worthwhile for people to listen to you?
  3. Sketch Results: What is the core of your solution idea? Quantitative results?
  4. Conclusion: What is your conclusion? (Is the problem solved?)
• Your biography: potential listeners will want to know if the person is experienced in the field and has something interesting to say. Your biography should capture this information.

Source: Stepan Decker의 How to announce academic talk

What is hot topics in Data science

• the whole lifecycle of the data from the past to the present and the future
• the analytics from explicit (known) analytics and reactive understanding to implicit (unknown) analytics and proactive early prediction and intervention
• the journey from data exploration (by descriptive and predictive analytics) to the delivery of actionable insights and decisions through prescriptive analytics and actionable knowledge delivery

Source code

This site is based on the Bedford lab website, which makes available the codes from their site in GitHub. In that site there is a good description of how it works and a list of derived sites, such as ours.