enthalten
Master the essentials of data science with the Data Science with R Specialization. Designed for beginners and professionals, this series provides the foundational skills to transform, visualize, and ethically analyze data with the R programming language. Whether you're exploring a career in data analysis, expanding your professional toolkit, or seeking to understand how your data analysis choices touch on ethics, this Specialization equips you with the technical and practical skills to thrive in today’s data-driven world. With no prior programming experience needed, this series is accessible to learners with diverse educational and work backgrounds, including analysts, researchers, and aspiring data scientists.
Through three courses, you’ll explore foundational topics in data science, including data visualization, statistical analysis, and advanced data transformation. You'll gain hands-on experience with real-world datasets, mastering doing data science with R and essential tools like Tidyverse, RStudio, Quarto, Git, and GitHub. The learning experience emphasizes practical application, offering engaging live-coding experiences and guided exercises to build confidence and competence in data science workflows. By the end of the series, you’ll be able to confidently tidy and transform data, create compelling visualizations, communicate insights that drive decisions, and apply ethical principles to address algorithmic bias, data privacy, and misrepresentation in your analyses.
Praktisches Lernprojekt
Throughout this Specialization, you’ll apply your skills to solve authentic data challenges using real-world datasets and industry-standard tools such as R, RStudio, Tidyverse, Quarto, and Git/GitHub. You’ll gain hands-on experience transforming raw data into meaningful insights, crafting compelling visualizations, and producing reproducible analyses that can be shared confidently with others. Each course emphasizes practical applications, from cleaning and preparing messy datasets to exploring ethical dilemmas in data usage, such as algorithmic bias and privacy concerns. By working through programming companions and guided exercises, you’ll develop the technical and ethical expertise to tackle real-world data problems and communicate results that inform decisions in any professional or research context.
