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Curriculum Designed by Experts
The Tidyverse Corporate Training by Multisoft Virtual Academy is tailored for organizations seeking to enhance data analysis capabilities using R. This course covers core Tidyverse packages such as dplyr, ggplot2, tidyr, and readr, focusing on efficient data cleaning, transformation, and visualization. Delivered through interactive live sessions, the training includes real-world use cases, practical exercises, and expert mentoring. It is ideal for data analysts, data scientists, and business teams looking to make data-driven decisions with confidence.
Tidyverse training is a structured program that teaches learners how to use the Tidyverse, a collection of powerful R packages designed for data manipulation, analysis, and visualization. The training covers essential tools like dplyr, ggplot2, tidyr, readr, and purrr, enabling participants to clean, transform, and interpret data efficiently. Through hands-on exercises and practical examples, learners develop strong analytical skills and the ability to create insightful visualizations. It is ideal for data analysts, researchers, and aspiring data scientists.
- Overview of R programming
- What is the Tidyverse ecosystem
- Benefits of using Tidyverse in data analysis
- Installing and loading Tidyverse packages
- Understanding tidy data principles
- Introduction to tibble vs data.frame
- Creating and converting tibbles
- Viewing, subsetting, and modifying tibbles
- Best practices for handling tabular data
- Introduction to readr package
- Importing CSV, TSV, and other structured files
- Parsing and transforming data types
- Writing data back to files
- Handling large datasets efficiently
- Grammar of data manipulation
- Using verbs: select, filter, mutate, arrange, summarise, group_by
- Handling missing values
- Working with pipelines using %>%
- Combining datasets with joins (inner, left, right, full, semi, anti)
- Using case_when, across, and advanced transformations
- Understanding tidy vs untidy data
- Reshaping data: pivot_longer, pivot_wider
- Nesting and unnesting datasets
- Separating and uniting columns
- Dealing with messy or inconsistent data
- Grammar of Graphics overview
- Creating basic plots: scatter, bar, line, histogram, boxplot
- Aesthetic mappings: color, size, shape, facets
- Themes, labels, and annotations
- Building advanced multi-layered visualizations
- Exporting and saving charts
- Introduction to functional programming concepts
- Using map(), map_df(), map_chr(), and other map variants
- Iterating efficiently without loops
- Automating repetitive operations
- Applying functions over lists and complex objects
- Using stringr for text cleaning and manipulation
- Handling dates and times with lubridate
- Managing categorical data with forcats
- Creating efficient data analysis workflows
- Using pipes and modular coding techniques
- File organization and project structure
- Version control basics (optional)
- Improving readability and reproducibility
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Tidyverse Corporate Training Certification
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