Welcome to the Python Bootcamp Code Repository! This repository contains all the code files and exercises covered during the Python bootcamp sessions.
This repository is organized into separate folders, each corresponding to a specific day or topic covered during the bootcamp. Below is a brief overview of each folder:
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Day1: Introduction to Python basics, variables, data types, operators, and data structures like lists and tuples.
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Day2: Exploration of advanced Python concepts including sets, dictionaries, comparison operators, conditional statements, loops, functions, and interactive quizzes.
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Day2 Assignment: The Assignment include: Word Guessing Game: A simple word guessing game where the computer selects a random word and the player tries to guess it by suggesting letters. Temperature Converter: A program that converts temperatures between Celsius and Fahrenheit. Quiz Solver: A quiz solver project where the user can attempt a quiz with predefined questions and get instant feedback on their answers.
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Day3: Dive into advanced Python concepts, including data science and numerical computing. Explore data manipulation, NumPy fundamentals, and interactive projects like building a Tic Tac Toe game. Engage in quizzes for deeper understanding.
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Day3 Assignment: The Assignment include: Tic Tac Toe Game: A fully working Tic Tac Toe Game. It features a user-friendly interface and allows two players to take turns playing against each other
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Day4: Dive into advanced data science with pandas, exploring real-world datasets like Spotify's. Master data manipulation, delve into DataFrames, and learn essential data cleaning techniques. Engage in practical exercises and quizzes for a comprehensive learning experience.
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Day4 Extraction: Dive into the cleaned and processed Spotify dataset, providing an organized view of track, artist, album, and genre information. Perfect for data analysis and visualization, offering real-world insights for data science projects.
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Day5: Master visualization techniques with matplotlib and seaborn, including line graphs, scatter plots, bar graphs, and heat maps. Explore real-time data with interactive charts and elegant visualizations to enhance data analysis and interpretation.
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Day6: Exploring machine learning basics, data gathering, cleaning, and analysis, regression models, relationship modeling, scikit-learn, training and testing data, using heatmaps and plots on car data, and evaluating accuracy with R² score.