Data Science with Python

"Python has become a cornerstone of data science, offering a rich ecosystem of libraries and tools that streamline data analysis, machine learning, and data visualization tasks. Its readability, flexibility, and extensive community support make it an ideal choice for both beginners and experienced data scientists."- Gemini 2024

Data Science with Python

Python Fundamentals (Documentation):
- Basics - syntax and data structures
- Control flow statements (if, for, while)
- Functions and modules
NumPy and Pandas:
- NumPy arrays and operations
- Pandas DataFrames and Series
- Data manipulation and cleaning
Data Visualization:
- Matplotlib and Seaborn
- Creating various types of plots (line, bar, scatter, etc.)
- Data storytelling
Machine Learning (Scikit Learn):
- Supervised learning (regression, classification)
- Unsupervised learning (clustering, dimensionality reduction)
- Model evaluation and tuning
Statistical Concepts (Stats module):
- Probability distributions
- Hypothesis testing
- Statistical inference
Data Cleaning and Preprocessing:
- Handling missing values
- Outlier detection and treatment
- Feature engineering