About this Course
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다음 전문 분야의 5개 강좌 중 2번째 강좌:

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

완료하는 데 약 18시간 필요

권장: 6 hours/week...

영어

자막: 영어, 한국어

배울 내용

  • Check

    Create a visualization using matplotlb

  • Check

    Describe what makes a good or bad visualization

  • Check

    Identify the functions that are best for particular problems

  • Check

    Understand best practices for creating basic charts

귀하가 습득할 기술

Python ProgrammingData VirtualizationData Visualization (DataViz)Matplotlib

다음 전문 분야의 5개 강좌 중 2번째 강좌:

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

완료하는 데 약 18시간 필요

권장: 6 hours/week...

영어

자막: 영어, 한국어

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 5시간 필요

Module 1: Principles of Information Visualization

In this module, you will get an introduction to principles of information visualization. We will be introduced to tools for thinking about design and graphical heuristics for thinking about creating effective visualizations. All of the course information on grading, prerequisites, and expectations are on the course syllabus, which is included in this module.

...
7 videos (Total 37 min), 6 readings, 2 quizzes
7개의 동영상
About the Professor: Christopher Brooks1m
Tools for Thinking about Design (Alberto Cairo)8m
Graphical heuristics: Data-ink ratio (Edward Tufte)4m
Graphical heuristics: Chart junk (Edward Tufte)5m
Graphical heuristics: Lie Factor and Spark Lines (Edward Tufte)3m
The Truthful Art (Alberto Cairo)8m
6개의 읽기 자료
Syllabus10m
Help us learn more about you!10m
Notice for Coursera Learners: Assignment Submission10m
Dark Horse Analytics (Optional)10m
Useful Junk?: The Effects of Visual Embellishment on Comprehension and Memorability of Charts30m
Graphics Lies, Misleading Visuals10m
2
완료하는 데 7시간 필요

Module 2: Basic Charting

In this module, you will delve into basic charting. For this week’s assignment, you will work with real world CSV weather data. You will manipulate the data to display the minimum and maximum temperature for a range of dates and demonstrate that you know how to create a line graph using matplotlib. Additionally, you will demonstrate the procedure of composite charts, by overlaying a scatter plot of record breaking data for a given year.

...
7 videos (Total 42 min), 2 readings, 1 quiz
7개의 동영상
Matplotlib Architecture6m
Basic Plotting with Matplotlib7m
Scatterplots8m
Line Plots8m
Bar Charts4m
Dejunkifying a Plot3m
2개의 읽기 자료
Matplotlib30m
Ten Simple Rules for Better Figures30m
3
완료하는 데 8시간 필요

Module 3: Charting Fundamentals

In this module you will explore charting fundamentals. For this week’s assignment you will work to implement a new visualization technique based on academic research. This assignment is flexible and you can address it using a variety of difficulties - from an easy static image to an interactive chart where users can set ranges of values to be used.

...
6 videos (Total 39 min), 2 readings, 2 quizzes
6개의 동영상
Histograms9m
Box Plots7m
Heatmaps3m
Animation5m
Interactivity5m
2개의 읽기 자료
Selecting the Number of Bins in a Histogram: A Decision Theoretic Approach (Optional)10m
Assignment Reading10m
4
완료하는 데 5시간 필요

Module 4: Applied Visualizations

In this module, then everything starts to come together. Your final assignment is entitled “Becoming a Data Scientist.” This assignment requires that you identify at least two publicly accessible datasets from the same region that are consistent across a meaningful dimension. You will state a research question that can be answered using these data sets and then create a visual using matplotlib that addresses your stated research question. You will then be asked to justify how your visual addresses your research question.

...
3 videos (Total 18 min), 2 readings, 1 quiz
3개의 동영상
Seaborn8m
Becoming an Independent Data Scientist1m
2개의 읽기 자료
Spurious Correlations10m
Post-course Survey10m
4.5
485개의 리뷰Chevron Right

33%

이 강좌를 수료한 후 새로운 경력 시작하기

38%

이 강좌를 통해 확실한 경력상 이점 얻기

16%

급여 인상 또는 승진하기

Applied Plotting, Charting & Data Representation in Python의 최상위 리뷰

대학: SBNov 3rd 2017

Loved the course! This course teaches you details about matplotlib and enables you to produce beautiful and accurate graphs.. Assignments are challanging, and helps to build a solid foundation.

대학: MLJun 28th 2017

Good course to learned matplotlib and other Graphs libraries, but the course goes further than Python and also encourages the studies to create more meaningful and beautiful Graphic views.

미시건 대학교 정보

The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future....

Python과 함께하는 응용 데이터 과학 전문 분야 정보

The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language. This skills-based specialization is intended for learners who have a basic python or programming background, and want to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through popular python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networkx to gain insight into their data. Introduction to Data Science in Python (course 1), Applied Plotting, Charting & Data Representation in Python (course 2), and Applied Machine Learning in Python (course 3) should be taken in order and prior to any other course in the specialization. After completing those, courses 4 and 5 can be taken in any order. All 5 are required to earn a certificate....
Python과 함께하는 응용 데이터 과학

자주 묻는 질문

  • 강좌에 등록하면 바로 모든 비디오, 테스트 및 프로그래밍 과제(해당하는 경우)에 접근할 수 있습니다. 상호 첨삭 과제는 이 세션이 시작된 경우에만 제출하고 검토할 수 있습니다. 강좌를 구매하지 않고 살펴보기만 하면 특정 과제에 접근하지 못할 수 있습니다.

  • 강좌를 등록하면 전문 분야의 모든 강좌에 접근할 수 있고 강좌를 완료하면 수료증을 취득할 수 있습니다. 전자 수료증이 성취도 페이지에 추가되며 해당 페이지에서 수료증을 인쇄하거나 LinkedIn 프로필에 수료증을 추가할 수 있습니다. 강좌 내용만 읽고 살펴보려면 해당 강좌를 무료로 청강할 수 있습니다.

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