Tidyverse (R Package)

Tidyverse is a collection of R packages designed for data science. Coursera's Tidyverse catalogue teaches you to effectively handle and manipulate data using the Tidyverse ecosystem. You'll learn everything from data importation, tidying, transformation, modelling, visualisation, to programming in R, leveraging libraries such as ggplot2, dplyr, tidyr, readr, purrr, and tibble among others. This will enable you to streamline your data science projects and enhance your problem-solving capabilities, making you a proficient data scientist, statistician, or a researcher.

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Results for "Tidyverse (R Package)"

  • From the course: R Programming for Statistics and Data Science·Lesson: Data Frames

  • From the course: Data Analysis with R·Lesson: Introduction to Data Analysis with R

  • From the course: Data Manipulation and Cleaning in R·Lesson: Introduction to the Course

  • From the course: Data Analysis with R Programming·Lesson: Learning about R packages

  • From the course: Exploratory Data Analysis and Visualization·Lesson: Data Preprocessing for EDA

  • From the course: Exploratory Data Analysis and Visualization·Lesson: Understanding EDA

  • From the course: Data Manipulation and Cleaning in R·Lesson: Separating and Uniting Columns

  • From the course: Reshaping Data with tidyr·Lesson: Separating and Uniting Columns

  • From the course: Data Analytics and Visualization with Tableau and more·Lesson: R Programming for Beginners: Includes R Mini-Project!

  • Skills you'll gain: Data Cleansing, Data Manipulation, Data Preprocessing, Data Transformation, Data Quality, Tidyverse (R Package), R Programming, Data Import/Export, Generative AI, Data Validation, Data Pipelines, Anomaly Detection

  • Skills you'll gain: Persona Development, Market Intelligence, Dashboard Creation, Dashboard, Data Visualization, Qualitative Research, Competitive Intelligence, Competitive Analysis, Tidyverse (R Package), Data Storytelling, Data Presentation, Trend Analysis, Market Research, Data Ethics, Power BI, LinkedIn, Business Intelligence, Data Analysis, R Programming, Strategic Thinking

  • From the course: Statistical Analysis and Advanced Techniques·Lesson: Fundamentals of Statistical Analysis