Data Science Projects
Explore how data can be collected, analyzed, and visualized to reveal patterns and support decision‑making. These projects help students investigate real‑world datasets, build charts and models, and understand how data science powers modern technology.
Data Collection
- Gather data on school habits (sleep, study time, screen time)
- Track weather conditions over several weeks
- Record environmental data such as temperature or air quality
Data Cleaning & Preparation
- Compare results using raw vs. cleaned datasets
- Investigate how missing data affects conclusions
- Test different methods for removing outliers
Visualization & Graphing
- Create charts to show trends in collected data
- Compare bar charts, line graphs, and scatter plots
- Test how visualization choices affect interpretation
Statistical Analysis
- Calculate averages, medians, and ranges for a dataset
- Investigate correlations between variables
- Test hypotheses using simple statistical tests
Predictive Modeling
- Build a model that predicts future values (weather, scores)
- Compare different prediction algorithms
- Test how dataset size affects prediction accuracy
Real‑World Datasets
- Analyze open datasets (traffic, environment, sports)
- Study trends in global temperature or pollution
- Investigate patterns in public health or demographics
Ethical Data Use
- Explore how biased data affects conclusions
- Investigate privacy concerns in data collection
- Design guidelines for responsible data use
Automation & Tools
- Write a script that organizes or filters data automatically
- Compare spreadsheet tools vs. coding tools for analysis
- Build a dashboard that updates with new data
