In "Der Werkzeugkasten des Data Scientist," you will gain a comprehensive understanding of the fundamental tools and concepts in data science. This course offers a conceptual and practical introduction, covering topics such as setting up R, R-Studio, Github, and other useful tools, understanding data and study design concepts, and creating a Github repository.
Throughout the course, you will delve into the data science process, installation of R and RStudio, versionskontrolle and GitHub, R Markdown, scientific thinking, and Big Data. By the end of the program, you will have a well-rounded understanding of the essential tools used by data analysts and data scientists.
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This course is comprised of four modules that cover essential topics such as data science fundamentals, R and RStudio installation, versionskontrolle and GitHub, as well as R Markdown, scientific thinking, and Big Data.
Module 1, "Data Science – Grundlagen," provides a foundational understanding of data science, including the data science process, data types, and obtaining help. The module also includes a summativer test to reinforce learning.
Module 2, "R und RStudio," focuses on the installation and usage of R and RStudio, including a guided tour of RStudio, working with R packages, and project management in R.
Module 3, "Versionskontrolle und GitHub," delves into version control, GitHub, linking Git/GitHub and RStudio, and managing projects under version control, all essential for collaborative data science work.
Module 4, "R Markdown, wissenschaftliches Denken und Big Data," covers R Markdown, different types of data science questions, experiment design, and understanding Big Data, culminating in the compilation of your data scientist's toolbox.
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