Course Overview

This course provides a comprehensive introduction to data science principles and practices. Students will:

• Learn the end-to-end data science workflow
• Gain practical experience with data manipulation tools
• Develop skills in data visualization and communication
• Apply statistical methods to derive insights from data

Prerequisites

• Basic programming knowledge (preferably in Python)
• Introductory statistics
• Comfort with basic algebra

Textbooks

• “Python for Data Analysis” by Wes McKinney
• “Data Science from Scratch” by Joel Grus

Grading

• Assignments: 50%
• Project: 40%
• Participation: 10%