This two week one to one Python data analytics program teaches students to work with real datasets, use Python basics, NumPy, Pandas, statistics, and data visualization. They complete hands on mini projects, learn to analyze patterns, clean data, create charts, and present insights. By the end, they gain confidence, practical skills, and readiness for advanced data learning.
In this 2-week 1:1 immersive journey of 2 hours per day, students dive into Python-based data analytics with real-world datasets, learning to extract insights, manipulate data, and visualize findings.Guided by a YoungGates Mentor, learners get hands-on experience from Day 1 — making coding interactive, fun, and practical.By the end of Module 1, students will confidently explore data, analyze patterns, and create visually appealing reports.
What Students Will LearnPython Basics Variables, data types, loops, functions applied to datasets
NumPy Perform array operations, calculations, and data manipulation
Pandas Load, clean, filter, and aggregate data from CSV or Excel datasets
Data Analysis Apply basic statistical measures: mean, median, mode, standard deviation
Data Visualization Create charts and plots using Matplotlib and Seaborn
Problem-Solving Skills Learn to ask the right questions and extract actionable insightsMentors ensure concepts are applied immediately in mini-projects, making learning interactive and engaging.
Week-by-Week BreakdownWeek 1 –
“Getting Hands-On with Data”• Introduction to Python for analytics and environment setup• Learn NumPy arrays, basic operations, and data manipulation• Practice with guided datasets
Mini Projects:
1 Store Sales Analyzer — Analyze daily sales data to calculate totals and averages
2 Student Grades Processor — Load and clean student score data to find performance trends
3 Mini Data Exploration — Practice filtering, sorting, and aggregating datasets
Mentor Role:
Live coding sessions with mentors who debug, explain logic, and guide exploration, ensuring students understand data workflows.
Week 2 – “Visualize & Extract Insights”• Learn Pandas advanced operations: groupby, pivot tables, and filtering• Explore Matplotlib & Seaborn for visualization• Apply statistical analysis to draw meaningful conclusions
Mini Projects:
1 Sales Trend Visualizer — Plot weekly sales trends and highlight insights
2 Product Performance Dashboard — Create charts showing top-selling products3 Custom Visualizations — Design colorful, interactive plots using Seaborn
Mentor Role:Students get daily guidance, mentor-led problem-solving, and encouragement to add creativity to their analytics outputs.
Project Showcase (End of Module 1)
Students present their favorite analytics project (e.g., Store Sales Analyzer) to peers and parents.Parents can see their teen explain insights, charts, and trends — a proud “mini-data scientist moment.”
Outcome & Certification
At the end of Module 1, students earn: YoungGates Certified Python Data Explorer Personalized Mentor Feedback Report Star Rating & Eligibility for Level 2 – Data Analyst Creator
Mentorship Promise
“We don’t just teach data — we teach insight and confidence.”Each learner receives:• 1:1 mentor guidance for every mini-project• Daily progress check-ins and challenge reviews• Hands-on exercises with real-world datasets• Motivation to explore independent data questions
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