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Avipsha Dash

Python Full Stack Developer · Data Analyst

Balasore, Odisha, India

@avipsha_dash

GitHub

0 followers

🎓 M.Tech in Computer Science & Engineering at GITA Autonomous College · Graduated 2025

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About

Aspiring Python Full Stack Developer and Data Analyst currently pursuing an M.Tech in Computer Science & Engineering. Has experience with Python-based development, data cleaning and analysis, and data visualization using modern web and analytics tools.

Experience

  • Part-Time Instructor — C Programming

    Taught C programming fundamentals to beginner-level students, simplifying complex programming concepts into clear, structured lessons. Guided coding practice, debugging, and problem-solving exercises, fostering a supportive and effective learning environment.

Education

  • M.Tech
    GITA Autonomous College
    Computer Science · 2025 – 2027
  • B.Tech
    Gandhi Institute for Education and Technology
    Computer Science · 2021 – 2025
  • Higher Secondary
    DAV Public School
    2019 – 2021

Skills

3 to 6 months 3 to 6 months A few months of practice with it.
C Debugging
<3 months <3 months Just getting started - under three months. This is also what shows when a level has not been set.
R CSS Oop HTML SDLC NumPy React Flask Python Django Pandas MS SQL Anaconda Bootstrap JavaScript Matplotlib Data Structures REST API Design Exploratory Data Analysis

Tools / apps / platforms

<3 months <3 months Just getting started - under three months. This is also what shows when a level has not been set.
Git SAS MySQL GitHub MongoDB PyCharm Tableau Microsoft Excel Jupyter Notebook

Projects

  • Employee Salary Analysis
    R, SAS, Advanced Excel, MS SQL, Tableau

    Cleaned, filtered, and analyzed San Francisco employee compensation data (FY 2014–15) to identify salary patterns, compensation trends, and outliers. Performed SQL-based analysis and built Tableau visualizations to present compensation insights.

  • Google Play Store
    Python, Pandas, NumPy, Matplotlib, Jupyter Notebook

    Cleaned, preprocessed, and analyzed a Kaggle dataset of about 10,000 Android applications to identify trends in app categories, ratings, reviews, and installs. Built visualizations comparing free vs. paid applications by size, price, and category.

  • E-Commerce Customer Purchase Data Analysis
    Python, Pandas, NumPy, Jupyter Notebook

    Performed exploratory data analysis on an e-commerce dataset of 10,000 records and 14 attributes to uncover customer purchasing patterns, payment methods, and transaction timings. Applied data inspection, null-value checking, filtering, conditional analysis, aggregation, and statistical calculations to extract meaningful insights.

Courses & certifications

  • Design and Analysis of Algorithms · Udemy
  • Python Development · Udemy

🎯 Hobbies & interests

  • Dance

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