Introduction to Data Science

About the course: 

CSE 180 is a survey course introducing the essential elements of data science: data collection, management, curation, and cleaning; summarizing and visualizing data; basic ideas of statistical inference, machine learning. Students will gain hands-on experience through computing labs.

Lectures: M/W/F   10:30 - 11:20am

Location: Odegaard Undergraduate Library 136 

Section: Thursday various times (AA/AB/AC/AE)

Week 1

• Course Introduction

• Introduction to Data

• Finding and Describing Datasets

• Credible and In-credible Data

• Finding Credible Data Articles

Week 2

• Intro to Statistics

• Asking Exploratory Questions of Data

• Activity - Data Exploration

• Presenting Results of an Analysis

Week 3

• Exploratory Data Analysis

• Installing and Registering for Tableau Desktop

• Intro to Data Visualization

• Data Exploration with Tableau

Week 4

• Trend Lines and Data Vis Best Practices

• Visualization Best Practice Summary

• Case Study - Covid Response

• Confidence Intervals

Week 5

• Hypothesis Testing

• Analyzing Least Square Regression Lines

• Simulating Data with Excel and Tableau

Week 6

• Intro to ML

• Cleaning data and finding correlations

• In-class Project (Details and Group Formation)

Week 7

• Intro to Decision Trees

• Categorical Prediction (Classification)

• In-class Project (Dataset and Visualizations)

Week 8

• BigML Intro

• BigML Practice - Housing Prices

• In-class Project (Visualizations and Predictions)

• BigML Practice - Housing Prices 

Week 9

• Neural Networks (Deep Learning)

• Neural Networks vs. Random Forests in BigML

• In-class Project (Finishing Slide Preparation)

Week 10

• Data Science Ethics and Wrap Up

• In-class Project (Presentations)