βI understand why Iβm doing thisβ
βI can read and explain data on my ownβ
βPython feels like a tool, not a fearβ
βIβm starting to think like a real data scientistβ
β Learn with real datasets teens relate to
β More doing, less memorizing
β Step-by-step growth: guided β semi-guided β independent
β 75β80% hands-on coding & projects
Β
By the end of this course, students can:
β Analyze real datasets using Python
β Clean, filter & visualize data confidently
β Apply statistics & probability logically
β Explain insights clearly
β Understand core ML ideas
β Be ready for Advanced Data Science & AI
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Age Group: 13β16 Years Level: Advanced Total Sessions: 90 Mode: Online / Hybrid π Tools Kids Will Use Python β’ Pandas β’ NumPy β’ Matplotlib β’ Seaborn β’ Scikit-learn (guided) β’ Streamlit (intro) β’ Real-world datasets π Pre-requisite Intermediate Data Science (Python basics, Pandas, charts, statistics, basic ML ideas)
Age Group: 10β12 Years Level: Beginner Total Sessions: 30 Mode: Online / Hybrid Tools Used: Spreadsheet tools, colorful charts & beginner Python (visual-first) Pre-requisite: None β no coding or advanced math needed