Data Science Fundamentals

This course covers the foundational aspects of data science, including data collection, cleaning, analysis, and visualization. Students will learn practical skills for working with real-world datasets.

Instructor: Prof. Data

Term: Spring

Location: Science Building, Room 202

Time: Mondays and Wednesdays, 2:00-3:30 PM

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%