Advance concept in R programming

Goals

• Master Advanced Data Structures: Understand and manipulate complex data structures such as lists, data frames, and matrices efficiently in R.

• Advanced Functional Programming: Learn advanced techniques for writing functions, using closures, and applying functional programming principles to streamline your code.

• Efficient Data Manipulation: Develop skills in data manipulation using dplyr and data.table for faster and more efficient data processing.

• Advanced Statistical Methods: Explore advanced statistical techniques including Bayesian statistics, time series analysis, and multivariate analysis using R.

• Advanced Data Visualization: Create compelling visualizations using ggplot2 and other packages, mastering techniques for customization and interactivity.

• Advanced R Programming Best Practices: Adopt best practices for writing efficient, readable, and maintainable R code, including debugging techniques and package development.

Prerequisites

• Basic R Programming Proficiency: Participants should have a solid understanding of fundamental R programming concepts such as data types, functions, loops, and conditional statements.

• Data Manipulation Skills: Familiarity with data manipulation tasks using packages like dplyr and data.table is essential.

• Statistical Knowledge: Basic understanding of statistics including hypothesis testing, regression analysis, and data distributions.

• Data Visualization Basics: Experience with creating basic plots using ggplot2 or similar packages.

• Command Line and Scripting: Comfortable working with RStudio or another R environment, and proficient in writing and executing R scripts.

• Mathematics and Algebra: Basic understanding of algebra and mathematical concepts involved in statistical and machine learning algorithms.