Welcome to my "30 Days of Python" challenge! This project represents a return to fundamentals, a refresher course in the world of software development that I've been passionate about for years.
My journey in software development began four years ago:
- Year 1: Mastering the basics
- Years 2-3: Diving deep into intermediate and advanced concepts
- Recent Years: Honing skills through real-world projects
Despite facing challenges (like my recent hardware setback), my passion for coding remains undiminished. This project is born out of that passion and the understanding that continuous practice is key to maintaining and improving one's skills.
Using only a smartphone, I'm embarking on a 30-day Python coding challenge. This unique constraint adds an extra layer of difficulty, but also demonstrates that with determination, learning can happen anywhere, anytime.
- Daily coding exercises
- Focus on Python fundamentals
- Gradual progression to more complex topics
- Real-world application of concepts
- Insights and reflections on the learning process
Whether you're an aspiring developer, in the early stages of your programming career, or simply looking to refresh your Python skills, I invite you to join me on this challenge.
The repository contains:
- Daily code snippets
- Explanations of concepts
- Practical exercises
- Resources for further learning
Check out the daily folders in this repository to follow along with the challenge. Feel free to fork the repo, try the exercises yourself, and share your progress.
Remember, the goal is not perfection, but consistent improvement and learning. Let's embark on this Python journey together and see how much we can grow in just 30 days!
Happy Coding!
- Python basics: variables, data types, and basic operations
- Control structures: if statements, loops
- Functions and modules
- Lists, tuples, and dictionaries
- File I/O operations
- Error handling and exceptions
- Introduction to object-oriented programming (OOP)
- Introduction to NumPy for numerical computing
- Pandas for data manipulation and analysis
- Data visualization with Matplotlib
- Advanced Pandas operations
- Working with CSV and Excel files
- Basic statistical analysis with Python
- Mini-project: Analyze and visualize COVID-19 data
- Advanced data manipulation with Pandas
- Time series analysis with Pandas
- Data cleaning and preprocessing
- Working with APIs and JSON data
- Introduction to data scraping
- Regular expressions in Python
- Mini-project: Analyze stock market data
- Introduction to machine learning with scikit-learn
- Data preprocessing for machine learning
- Supervised learning: Classification
- Supervised learning: Regression
- Unsupervised learning: Clustering
- Model evaluation and improvement
- Final Project: Day 1 - Project setup and data preparation
- Final Project: Day 2 - Model development and training
- Final Project: Day 3 - Model evaluation and results analysis
For the last three days, we'll work on a comprehensive project that combines data analysis and machine learning. We'll create an application that allows us to perform exploratory data analysis and run machine learning predictions on a chosen dataset.
Features of the application:
- Data loading and basic exploration
- Data visualization dashboard
- Basic statistical analysis of the data
- Machine learning model selection (e.g., classification or regression)
- Model training and evaluation
- Prediction on new data points
- Results analysis and interpretation
This project will utilize Pandas and Matplotlib for data analysis and visualization, and scikit-learn for machine learning. It will tie together all the concepts learned throughout the 30 days.
Remember to commit your progress to GitHub daily, including your code, any datasets you use (if not too large), and documentation of your learning and challenges faced.
Let's embark on this exciting journey of Python mastery!