Data Science Foundations: Programming in R and Python

Choosing between R and Python for data science can feel overwhelming when you are just starting out. This course removes the guesswork by teaching you the fundamentals of both languages, enabling you to use the right tool for any data analysis task. You will transition from a complete beginner to a confident data explorer. You will understand how to set up clean programming environments, read and manipulate datasets, perform statistical analyses, and generate clear visualizations using industry-standard libraries in both ecosystems. What you'll learn: - Understand foundational data science concepts, terminology, and the core differences between R and Python workflows. - Manage programming environments and dependencies using modern tools for both languages. - Manipulate and clean structured data using Pandas and Polars in Python, alongside Tidyverse packages in R. - Perform exploratory data analysis and statistical computing to uncover trends within datasets. - Create clear, informative data visualizations using ggplot2 in R and matplotlib in Python. - Practice writing clean, reproducible code using modern programming conventions and type hints. The course starts with essential definitions and environment setup before guiding you through hands-on code examples in both languages. You will progress from basic syntax to practical data manipulation and visualization techniques through structured reading and written analysis exercises. This course is designed for absolute beginners with no prior programming or data science experience. Start your journey into data science today and master the dual power of R and Python.