Python For Data Science Roadmap

1. Python Fundamentals

Week 1: Introduction to Python & Setup
- Installing Python and IDEs (VS Code)
- Introduction to Python syntax, variables, and data types
- Basic I/O (input(), print())
Week 2: Working with Functions & Loops
- Loops: break, continue, pass
- Defining functions, parameters, and return values
- Understanding local vs. global scope
Week 3: Data Structures
- Lists and Tuples: creation, manipulation, slicing
- Sets and Dictionaries: methods and operations
Week 4: File Handling
- Reading and writing text/CSV files
- Project 1: Expense Tracker

2. Intermediate Python Skills

Week 5: Introduction to Data Science Libraries
- NumPy basics: arrays, slicing, mathematical operations
- Pandas basics: dataframes, series, basic exploration
Week 6: Data Cleaning and Preprocessing
- Handling missing data: dropna(), fillna()
- Data transformation: normalization, type conversion
Week 7: Data Visualization
- Matplotlib basics: line plots, bar charts, histograms
- Seaborn: box plots, heatmaps, pair plots
Week 8: Project 2: Sales Data Analysis
- Clean, analyze, and visualize a sales dataset
- Present insights and findings

3. Advanced Data Analysis

Week 9: Introduction to Statistical Analysis
- Descriptive statistics: mean, median, mode
- Hypothesis testing: t-tests, chi-squared tests
Week 10: Machine Learning Basics
- Introduction to supervised and unsupervised learning
- Building a simple linear regression model
Week 11: Data Visualization and Correlation
- Advanced visualizations with Seaborn
- Performing linear regression analysis
Week 12: Project 3: COVID-19 Data Analysis
- Analyze and visualize global COVID-19 cases
- Generate actionable insights

4. Real-World Data Projects

Week 13: Real-World Data Analysis
- Financial data analysis: trends, predictions
- Customer behavior analysis
Week 14: Advanced Data Processing
- Handling large datasets
- Time series analysis
Week 15: Machine Learning Project
- Predicting house prices
- Improving model performance
Week 16: Capstone Projects
- End-to-end data analysis project
- Final presentations and course wrap-up