- The course uses real-world datasets to practice data cleaning, visualization, and modeling.
- Learners perform statistical analyses and exploratory data analysis (EDA) in R.
- Projects simulate scenarios similar to those in professional data science roles.
- Guided labs reinforce concepts through practical application.
- Hands-on work helps learners build a portfolio to demonstrate their skills.
