R is a programming language and environment designed for statistical computing, data analysis, and graphical representation, widely used by statisticians, data scientists, researchers, and analysts. This course guides learners through R programming, from foundational concepts to advanced techniques. It covers R fundamentals, data types, variables, structures, custom functions, control structures, and data manipulation.
Learners will master data visualization with leading packages, statistical analysis, hypothesis testing, and regression modeling. The course also includes advanced data manipulation, outlier handling, missing data strategies, and text manipulation using regular expressions. Additionally, it covers machine learning with regression, classification, and clustering algorithms, as well as deep learning, neural networks, image classification, and semantic segmentation.
The course concludes with the creation of dynamic web apps using Shiny. Designed for aspiring and established data scientists, analysts, programmers, researchers, and professionals, it accommodates various experience levels. Prerequisites include prior programming experience, but the course can accommodate learners with varying levels of data science and R programming familiarity.
Applied Learning Project
The included projects in "R Ultimate 2023 - R for Data Science and Machine Learning" are designed to provide hands-on experience with real-world data analysis and machine learning tasks. Learners will apply their skills to solve authentic problems, such as creating dynamic web apps with Shiny, building predictive models, and performing advanced data manipulations, enabling them to transform raw data into actionable insights and interactive applications.
