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Data Science as a Field

Курс от University of Colorado Boulder
Средний≈ 10.9 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

This course provides a general introduction to the field of Data Science. It has been designed for aspiring data scientists, content experts who work with data scientists, or anyone interested in learning about what Data Science is and what it’s used for. Weekly topics include an overview of the skills needed to be a data scientist; the process and pitfalls involved in data science; and the practice of data science in the professional and academic world. This course is part of CU Boulder’s Master’s of Science in Data Science and was collaboratively designed by both academics and industry professionals to provide learners with an insider’s perspective on this exciting, evolving, and increasingly vital discipline. Data Science as a Field can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.

Навыки, которые вы освоите

Data AnalysisData ScienceAnalysisData PresentationStatistical ReportingComputer ScienceStatisticsApplied MathematicsData StorytellingTechnical CommunicationData Literacy

Программа курса

4 модулей · 59 учебных материалов

01Introduction to Data Science: the Past, Present, and Future of a New Discipline10 материалов

Course Overview

Course Updates and Accessibility SupportЧтениеEarn Academic Credit for your Work!ЧтениеCourse SupportЧтениеAssessment ExpectationsЧтение

Учитесь у экспертов

Jane Wall

Faculty Director of Data Science Programs

Data Science as a Field
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Обучение на Coursera

≈ 10.9 ч

4 модулей

Язык: Английский

Субтитры: Арабский, Французский, Украинский, Китайский (Китай), Греческий, Итальянский, Бразильский португальский, Нидерландский, Корейский, Немецкий, Русский, Тайский, Индонезийский, Шведский, Турецкий, Испанский, Хинди, Японский, Казахский, Польский

Часть программы вашего университета
Data Science as a Field Course Introduction Видео
Introduce Yourself!Обсуждение

What is Data Science?

Where Does Data Science Come From?ВидеоThe Current State of the FieldВидеоWhere is Data Science Going?Видео

Week 1 Assessment

Data Science and Privacy ConcernsОбсуждение
02Data Science in Industry, Government, and Academia19 материалов

Week 2 Overview

Introduction to "Data Science in Business, Industry, and the Professional World"ВидеоApplications of Data ScienceОбсуждение

Data Science in Industry and Government

Introducing Brian Brown and Rinaldo MalderaЧтениеBrian Brown & Rinaldo MalderaВидеоIntroducing Natalie JacksonЧтениеNatalie JacksonВидеоData Science at AirBnBОбсуждение

Data Science in Academia

Introducing Vilja HuldenЧтениеVilja HuldenВидеоIntroducing Robin BurkeЧтениеRobin BurkeВидеоIntroducing Seth SpielmanЧтениеSeth SpielmanВидеоIntroducing Katharina Kann

Week 2 Assessment

Data Science in Industry, Government, and AcademiaВзаимная проверка
03Data Science Process and Pitfalls23 материалов

Reproducibility

Importance and Process of ReproducibilityВидеоReproducibilityОбсуждениеBefore You Watch The Next Video...ЧтениеKnit to PDFВидеоKnit the TemplateЧтениеIntro to R MarkdownВидеоUse R Markdown to Create a DocumentЧтение

Steps in the Data Science Process through Data Cleaning

Overview of Steps in the Data Science ProcessВидеоFor More Info On Tidyverse Packages...ЧтениеFile Unlocking QuizЗаданиеProject FilesЧтениеImporting DataВидеоProject Step 1: Start an Rmd DocumentЧтение

Visualizing, Analyzing, and Modeling Data

Visualizing DataВидеоAnalyzing DataВидеоModeling DataВидеоProject Step 3: Add Visualizations and AnalysisЧтение

Pitfalls

Bias SourcesВидеоIntro to Data Ethics Course with Bobby SchnabelВидеоProject Step 4: Add Bias IdentificationЧтение

Submit Your Project

NYPD Shooting Incident Data ReportВзаимная проверка
04Communicating Your Results7 материалов

Communicating Your Results

Do’s and Don’ts for Good Reports and PresentationsВидеоElevator PitchОбсуждение

Course Conclusion

CU Boulder’s MS in Data Science: Where to Go from Here?ВидеоAttend a MeetupОбсуждениеImposter SyndromeЧтениеImposter SyndromeОбсуждение

Week 4 Assessment

Communicating your ResultsВзаимная проверка
Чтение
Katharina KannВидео
Introducing Dan LarremoreЧтение
Dan LarremoreВидео
Application Areas and SkillsОбсуждение
Tidying and Transforming DataВидео
Project Step 2: Tidy and Transform Your DataЧтение