Der Werkzeugkasten des Data Scientist

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Der Werkzeugkasten des Data Scientist

Instructors: Localization Team

Included with

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4 modules

Gain insight into a topic and learn the fundamentals.

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

2 weeks to complete

at 10 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

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

21 assignments

Taught in German

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There are 4 modules in this course

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.

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

5 videos Total 40 minutes

Warum automatisierte Videos? 5 minutes
Was ist Data Science? 9 minutes
Was sind Daten? 7 minutes
Hilfe bekommen 10 minutes
Der Data-Science-Prozess 9 minutes

2 readings Total 7 minutes

Willkommen 5 minutes
Eine Anmerkung zur Erläuterung 2 minutes

5 assignments Total 126 minutes

Was ist Data Science? 6 minutes
Was sind Daten? 30 minutes
Test zur Hilfe 30 minutes
Data-Science-Prozess 30 minutes
Modul eins: Summativer Test 30 minutes

5 plugins Total 75 minutes

Warum automatisierte Videos? 15 minutes
Was ist Data Science? 15 minutes
Was sind Daten? 15 minutes
Hilfe bekommen 15 minutes
Der Data-Science-Prozess 15 minutes

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

5 videos Total 34 minutes

Installation von R 6 minutes
Installation von RStudio 3 minutes
RStudio-Rundgang 7 minutes
R-Pakete 12 minutes
Projekte in R 6 minutes

6 assignments Total 180 minutes

Installation von R 30 minutes
Installation von RStudio 30 minutes
RStudio-Rundgang 30 minutes
R-Pakete 30 minutes
Projekte in R 30 minutes
Modul zwei: Summativer Test 30 minutes

5 plugins Total 75 minutes

Installation von R 15 minutes
Installation von RStudio 15 minutes
RStudio-Rundgang 15 minutes
R-Pakete 15 minutes
Projekte in R 15 minutes

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

4 videos Total 28 minutes

Versionskontrolle 11 minutes
GitHub und Git 9 minutes
Verknüpfung von GitHub und RStudio 4 minutes
Projekte unter Versionskontrolle 4 minutes

5 assignments Total 150 minutes

Versionskontrolle 30 minutes
GitHub und Git 30 minutes
Linking Git/GitHub and RStudio 30 minutes
Projekte unter Versionskontrolle 30 minutes
Modul drei: Summativer Test 30 minutes

4 plugins Total 60 minutes

Versionskontrolle 15 minutes
GitHub und Git 15 minutes
Verknüpfung von GitHub und RStudio 15 minutes
Projekte unter Versionskontrolle 15 minutes

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

4 videos Total 34 minutes

R Markdown 8 minutes
Arten von datenwissenschaftlichen Fragen 10 minutes
Versuchsplanung 9 minutes
Big Data 7 minutes

5 assignments Total 150 minutes

R Markdown 30 minutes
Arten von datenwissenschaftlichen Fragen 30 minutes
Versuchsplanung 30 minutes
Big Data 30 minutes
Modul vier: Summativer Test 30 minutes

1 peer review Total 60 minutes

Zusammenstellung Ihres Werkzeugkastens 60 minutes

4 plugins Total 60 minutes

R Markdown 15 minutes
Arten von datenwissenschaftlichen Fragen 15 minutes
Versuchsplanung 15 minutes
Big Data 15 minutes

Instructors

Localization Team

7 Courses 30,782 learners

Offered by

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