Description
🔹 Course Vision
This course provides middle and high school students with a comprehensive introduction to data science, coding, and visual analytics. Through step-by-step instruction in Python, R, Tableau, and Excel, students will develop essential computational thinking, data interpretation, and problem-solving skills.
The course bridges foundational coding and statistics with real-world applications, laying the groundwork for AI, machine learning, and future interdisciplinary pursuits.
🔹 What Students Will Learn
1. Data & Problem-Solving Basics
• What is data? Types of data (qualitative, quantitative)
• Basic statistics: mean, median, mode
• Using math to understand real-world problems
→ Understand the role of data in daily decisions and future industries.
2. Python Programming for Data
• Installing and setting up Python (Google Colab / Anaconda)
• Variables, data types, operators, input/output, and comments
→ Develop confidence in writing basic Python programs.
3. Control Structures & Data Collections
• Conditional statements (if, else, elif)
• Loops (for, while)
• Lists, tuples, dictionaries
→ Learn to build logical and structured programs.
4. Functions & File Handling
• Defining and calling functions
• Parameters, return values, variable scope
• Reading CSV files
• Using Pandas and Matplotlib
→ Students begin visualizing data and writing reusable code.
Sample Projects:
• Grade calculator
• Mini games
• Simple budget tracker
• Plot favorite sports stats
5. Math for Data Analytics (Integrated)
• Ratios, percentages, averages
• Probability foundations
• Reading and interpreting charts
6. R Programming for Statistics
• RStudio setup & environment
• Vectors, data frames
• Importing and cleaning data
• Basic plots: bar, pie, histogram
→ Enhance statistical literacy with R.
7. Data Visualization with Tableau
• Importing data (Excel, CSV)
• Building dashboards
• Creating filters, calculated fields
• Publishing and sharing interactive visuals
→ Learn to tell compelling stories through dashboards.
8. Final Integration Projects
• Analyze real-world datasets
• Combine Python, R, and Tableau
• Present a mini project with data insights
🔹 Who This Course Is For
- Students in Grades 7–10
- Curious about data, coding, statistics, or business
- Planning to explore AI, machine learning, or STEM careers
- Preparing for future school research, competitions, or university majors in tech-related fields
🔹 Integrated Pathways
- Â Academic Enrichment & Future Skills Lab
- Future Readiness & Cross-Disciplinary Application
- Seasonal Camps / AI Projects
- University Planning & Application Support (for students building early STEM portfolios or essays)
🔹 Final Outcomes
- Mastery of coding logic, data structures, and basic visualization
- Fluency in tools like Python, R, and Tableau
- Creation of at least 3 functional mini-projects
- Completion of 1 real-world dataset analysis with dashboard or presentation
- Strong foundation to pursue AI, robotics, or CS competitions and advanced courses
