Data is everywhere. Charts, graphs, and other types of information visualizations help people to make sense of this data. This course explores the design, development, and evaluation of such information visualizations. By combining aspects of design, computer graphics, HCI, and data science, you will gain hands-on experience with creating visualizations, using exploratory tools, and architecting data narratives. Topics include user-centered design, web-based visualization, data cognition and perception, and design evaluation.
제공자:
Vital Skills for Data Science 특화 과정콜로라도 대학교 볼더 캠퍼스이 강좌에 대하여
최근 조회 7,915회
유연한 마감일
일정에 따라 마감일을 재설정합니다.
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 특화 과정의 4개 강좌 중 4번째 강좌:
중급 단계
Python, foundation in Data Science
완료하는 데 약 14시간 필요
영어
자막: 영어
배울 내용
Develop a toolkit for exploring and communicating complex data using visualization
Produce basic data visualizations using a chosen dataset
Compare methods for visualizing data and understand how these methods may guide users towards different conclusions
Evaluate how effectively a visualization conveys target data
귀하가 습득할 기술
- Evaluation Design
- Visualizing data with Altair
- User-Centered Design (Create basic visualizations that match data and user needs)
- Task Analysis (Define elements of a data analysis and/or communication problem)
유연한 마감일
일정에 따라 마감일을 재설정합니다.
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 특화 과정의 4개 강좌 중 4번째 강좌:
중급 단계
Python, foundation in Data Science
완료하는 데 약 14시간 필요
영어
자막: 영어
제공자:
콜로라도 대학교 볼더 캠퍼스
CU-Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.
석사 학위 취득 시작
이 강좌은(는) 콜로라도 대학교 볼더 캠퍼스의 100% 온라인 Master of Science in Data Science 중 일부입니다.
전체 프로그램을 수료하면 귀하의 강좌가 학위 취득에 반영됩니다.
강의 계획표 - 이 강좌에서 배울 내용
완료하는 데 7시간 필요
Basics of Design
In this module, you will learn the foundations of visualization design. You will walk through the key components of a visualization, how we effectively represent data using channels like color, size, and position, and some ground rules for honest and effective visualization. You will also gain preliminary exposure to Altair, a Python library for rapidly generating interactive visualizations. Each week will also include either two readings or one reading and one notebook activity.
완료하는 데 7시간 필요
13개 동영상 (총 156분), 11 개의 읽기 자료, 1 개의 테스트
완료하는 데 4시간 필요
User Needs
In this module, you will learn how to choose the right visualization for a given scenario. You will learn how to reason about the different kinds of questions people ask with visualization and, how to align your design with that task. The module will cover basics of task analysis, methods for task elicitation, and foundational knowledge of visual perception for design. Each week will also include two external readings or one reading and one notebook activity.
완료하는 데 4시간 필요
9개 동영상 (총 110분), 7 개의 읽기 자료, 1 개의 테스트
완료하는 데 3시간 필요
Evaluation
In this module, you will learn how to assess the effectiveness of your visualization. You will learn both qualitative and quantitative approaches for evaluating visualizations as well as how to isolate key elements for assessment and iteration. The module will cover basics of insight-based evaluation, interview studies, and experimental design and analysis. Each week will also include two external readings or one reading and one notebook activity.
완료하는 데 3시간 필요
7개 동영상 (총 80분), 7 개의 읽기 자료, 1 개의 테스트
Vital Skills for Data Science 특화 과정 정보
Vital Skills for Data Science introduces students to several areas that every data scientist should be familiar with. Each of the topics is a field in itself. This specialization provides a "taste" of each of these areas which will allow the student to determine if any of these areas is something they want to explore further. In this specialization, students will learn about different applications of data science and how to apply the steps in a data science process to real life data. They will be introduced to the ethical questions every data scientist should be aware of when doing an analysis. The field of cybersecurity makes the data scientist aware of how to protect their data from loss.
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