Python for Data Science

Master NumPy arrays, vectorized operations, broadcasting, and advanced indexing

• ○Introduction to NumPy Arrays15m
• ⌖Create and Inspect Arrays15m
• ○Array Operations and Broadcasting15m
• ⌖Vectorized Operations Practice15m
• ○Indexing and Slicing15m
• ?NumPy Fundamentals Quiz10m

Work with DataFrames and Series to load, filter, group, and analyze tabular data

• ○Series and DataFrames15m
• ○Indexing and Filtering15m
• ⌖DataFrame Filtering Practice15m
• ○GroupBy and Aggregation15m
• ⌖GroupBy Aggregation Practice15m
• ?Pandas Essentials Quiz10m

Handle missing data, convert types, merge datasets, and reshape tables

• ○Handling Missing Data15m
• ○Data Types and Conversion15m
• ⌖Clean a Messy Dataset20m
• ○Merging and Reshaping Data15m
• ?Data Cleaning Quiz10m

Create informative plots with Matplotlib and Seaborn to communicate data insights

• ○Matplotlib Basics15m
• ○Common Plot Types15m
• ⌖Create Visualizations20m
• ○Introduction to Seaborn15m
• ?Data Visualization Quiz10m

Apply statistical methods to understand distributions, correlations, and outliers in data

• ○Descriptive Statistics15m
• ○Correlation Analysis15m
• ○Distributions and Outlier Detection15m
• ⌖EDA Practice20m
• ?EDA Concepts Quiz10m

Analyze a real-world dataset end-to-end, from data loading and cleaning to visualization and insights

• ○Project Overview: Analyze a Real Dataset15m
• ⌖Generate and Load the Dataset15m
• ⌖Clean and Explore the Data20m
• ⚒Build a Visualization Dashboard30m
• ?Data Analysis Insights Quiz10m

Comprehensive assessment covering NumPy, Pandas, data cleaning, visualization, and exploratory data analysis

• ?Python for Data Science Final Exam30m