Schedule

1/13

Course Introduction and Syllabus

The Things You Can Do with Data.

The Information Architecture of an Organization

PowerPoint: Course Introduction

The Things You Can Do with Data

Information Architecture

1/15

Understanding Database Schemas: Normalization, primary/foreign keys, joins

PowerPoint: Relational Data Modeling

1/20

In-class exercise: Creating database schema in MySQL Workbench

1/22

Getting data out of RDMS: SQL SELECT, DISTINCT MIN, MAX, COUNT, and WHERE

Make sure you’ve reviewed the guide for setting up a connection in MySQL Workbench

PowerPoint: SQL 1

1/27

In-class exercise: Pen and Paper exercise

Assignment 1 Due: Database schema

1/29

In-class exercise: Working with SQL, part 1

2/3

Getting data out of RDMS: Joining tables

In-class exercise: Working with SQL, part 2

PowerPoint: SQL 2

Assignment 2 Due: SQL #1

2/5

In-class exercise: Working with SQL, part 2

2/10

Review for Exam 1

Assignment 3 Due: SQL #2

2/12

Exam 1

2/17

Semi-structured data

In-class exercise: Working with semi-structured data

PowerPoint: Semi-structured data & NoSQL

2/19

Introduction to Python

In-class exercise: Getting familiar with Jupyter, Python Basic, Data types

2/24

Python Data Structures

In-class exercise: Python Lists and Dictionaries

2/26

Python and JSON

In-class exercise: Working with JSON in Python

Assignment 4 Due: Python Basics

3/2-6

Spring Break – No class

3/10

In-class exercise: Working with JSON in Python (continued)

Reconciling Data: The extract, transform, load process (ETL)

PowerPoint: ETL

3/12

Python Pandas

In-class exercise: Working with Python Pandas

Assignment 5 Due:  Python and JSON

3/17

Hypothesis Testing

Principles of Data Visualization

In-class exercise: Data Visualization

PowerPoint: Hypothesis Testing
Data Visualization

3/19

Review for Exam 2 

Assignment 6 Due: Pandas

3/24

Additional practice for Exam 2 (by Shuhua Wu)

3/26

Exam 2

3/31

Introduction to Advanced Analytics

Classification using Decision Trees

PowerPoint: Advanced Analytics – Introduction

Classification using Decision Trees

4/2

In-class exercise: Decision trees in Python

4/7

Analysis Scenario: Identifying similar customers (clustering and segmentation) 

PowerPoint: Clustering and Segmentation

Assignment 7 Due: Decision Trees

4/9

In-class exercise: Clustering and Segmentation in Python

4/14

Analysis Scenario: What products are purchased together? (Association Rules) 

In-class exercise: Computing Confidence, Support, and Lift

PowerPoint: Association Rule Mining

Assignment 8 Due: Clustering

4/16

In-class exercise: Association Rule Mining in Python

4/21

Review for Exam 3

Assignment 9 Due: Association Rules

4/23

Exam 3