In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio.
Der Werkzeugkasten des Data Scientist
Der Werkzeugkasten des Data Scientist
Instructors: Localization Team
Sponsored by Coursera Learning Team
Gain insight into a topic and learn the fundamentals.
17 hours to complete
3 weeks at 5 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Set up R, R-Studio, Github and other useful tools
Understand the data, problems, and tools that data analysts use
Explain essential study design concepts
Create a Github repository
Details to know
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Assessments
21 assignments
Taught in German
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There are 4 modules in this course
In diesem Modul werden wir Data Science und die Daten selbst vorstellen und definieren. Wir gehen auch auf einige der Ressourcen ein, die Data Scientists nutzen, um Hilfe zu erhalten, wenn sie nicht weiterkommen.
What's included
5 videos2 readings5 assignments5 plugins
In diesem Modul helfen wir Ihnen, sich mit R und RStudio vertraut zu machen. Nebenbei lernen Sie einige Grundlagen über beide Tools und warum Data Scientists sie verwenden.
What's included
5 videos6 assignments5 plugins
In diesem Modul lernen Sie etwas über Versionskontrolle und warum sie für Data Scientists so wichtig ist. Außerdem lernen Sie, wie Sie mit Git und GitHub die Versionskontrolle in Data-Science-Projekten verwalten können.
What's included
4 videos5 assignments4 plugins
In diesem letzten Modul lernen Sie die Verwendung von R Markdown kennen und erhalten eine Einführung zu drei Konzepten, die für jeden erfolgreichen Data Scientist unglaublich wichtig sind: gute Fragen stellen, Versuchsplanung und Big Data.
What's included
4 videos5 assignments1 peer review4 plugins
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