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✅ Section 1: Python + Machine Learning

• Dataset: Student Performance Dataset.
• Performed data cleaning, EDA using matplotlib and `seaborn".
• Created a binary pass/fail target column for it.
• Trained and evaluated Logistic Regression and Random Forest.
• Evaluated using Accuracy, Confusion Matrix, and F1-score.

📎 See my file: Student_Performance_Project.ipynb

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✅ Section 2: SQL

• Database: Chinook Music Store
• SQL queries include:
  1. Top 5 customers by purchase
  2. Most popular genre
  3. Managers and their subordinates
  4. Most sold album per artist
  5. Monthly sales trends for 2013

📎 See: chinook_queries.sql

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✅ Section 3: Tableau

• Dataset: NYC Airbnb Open Data
• Dashboard contains:
  • Listings count by neighborhood group
  • Price distribution by room type
  • Availability trends
• Interactive filters for neighborhood and room type

🔗 Tableau Public Link: CLICK HERE

📎 See My Tableau: Tableau_Dashboard_Link.txt

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✅ Section 4: Excel

• Dataset: Online Retail Dataset
• Tasks completed:
  • Cleaned data (nulls, duplicates)
  • Added TotalSales column (Quantity × UnitPrice)
  • Created Pivot Table (Sales by Country and Month)
  • Calculated Average Order Value & % contribution
  • Highlighted top 5 countries by revenue
  • Charted monthly revenue trend

📎 See: OnlineRetail_Analysis.xlsx ar here [https://docs.google.com/spreadsheets/d/1CdaYRAuo1UTDXpTn5AuoZdW5PLg-QLOr/edit?usp=sharing&ouid=115343273173524923923&rtpof=true&sd=true]

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✅ Section 5: Bonus (Optional)

📎 See: Bonus_Response.docx

I explained how I would support struggling students and how I'd simplify the concept of Gradient Descent for beginners using analogies and visuals.

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✅ Section 6: AI Tools & LLMs

📎 See: Section6_AI_Tools.txt

• I used ChatGPT to help with SQL logic and formula suggestions.
• Shared the exact prompt and AI response
• Added a short reflection on what the AI did well and what I tweaked

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📹 Video Walkthrough (Mandatory)

🎥 Link to 10–15 min Screen Recording: [https://drive.google.com/file/d/18O7NETXnWbVdlpTta4WQnLhMpCXabPik/view?usp=drive_link]

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🙌 Thank You

Thank you for this opportunity! I look forward to the possibility of supporting students as a Teaching Assistant.

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