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MIS2502: Data and Analytics (Section 2)

INSTRUCTOR: JAEHWUEN JUNG

Data and Analytics

MIS 2502.002 ■ Spring 2024 ■ Jaehwuen Jung
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  • Schedule
  • Projects
    • In-Class Activities
    • Assignments
  • About
    • Course details
    • Review and Exam Study Guides
    • softwaretool-instructions

Schedule

 

Day Topics Course Materials Assignments

1/16

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

 

1/18

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

PowerPoint: Relational Data Modeling

 

1/23

In-class exercise: Creating database schema in MySQL Workbench

 

 

1/25

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

 

1/30

In-class exercise: Pen and Paper exercise

 

Assignment 1 Due: Database schema

2/1

In-class exercise: Working with SQL, part 1

Getting data out of RDMS: Joining tables

PowerPoint: SQL 2

 

2/6

In-class exercise: Working with SQL, part 2

 

Assignment 2 Due: SQL #1

2/8

In-class exercise: Working with SQL, part 2

 

 

2/13

Review for Exam 1

 

Assignment 3 Due: SQL #2

2/15

Exam 1

 

 

2/20

Semi-structured data

In-class exercise: Working with semi-structured data

PowerPoint: Semi-structured data & NoSQL

 

2/22

Introduction to Python

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

 

 

2/27

Python Data Structures

In-class exercise: Python Lists and Dictionaries

 

 

2/29

Python and JSON

In-class exercise: Working with JSON in Python

 

Assignment 4 Due: Python Basics

3/5-7

Spring Break – No class

 

 

3/12

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

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

PowerPoint: ETL

 

3/14

Python Pandas

In-class exercise: Working with Python Pandas

 

Assignment 5 Due:  Python and JSON

3/19

Hypothesis Testing

Principles of Data Visualization

In-class exercise: Data Visualization

PowerPoint: Hypothesis Testing
Data Visualization

 

3/21

Review for Exam 2

 

Assignment 6 Due: Pandas

3/26

Review for Exam 2 (by Meixian Wang)

   

3/28

Exam 2

   

4/2

Introduction to Advanced Analytics

Classification using Decision Trees

PowerPoint: Advanced Analytics – Introduction

Classification using Decision Trees

 

4/4

In-class exercise: Decision trees in Python

 

 

4/9

Analysis Scenario: Identifying similar customers (clustering and segmentation) 

PowerPoint: Clustering and Segmentation

Assignment 7 Due: Decision Trees

4/11

In-class exercise: Clustering and Segmentation in Python

 

 

4/16

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

4/18

In-class exercise: Association Rule Mining in Python

 

 

4/23

Review for Exam 3

 

Assignment 9 Due: Association Rules

4/25

Exam 3

 

 

 

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QUICK INFO

  • Time and Locations: 9:30 am – 11:50 am, Tuesday and Thursday, Alter231
  • Instructor: Jaehwuen Jung (jaejung@temple.edu)
    Office hours: 1:30 pm – 2:30 pm, Tuesday and Thursday (Speakman 201E)
  • ITA: AI Tseng (ai.tseng@temple.edu)
  • TA: Meixian Wang (meixian.wang@temple.edu)
    Office hours: 4 pm – 5 pm on the day of the assignment due (Speakman 208H)

LINKS

  • Temple Canvas
  • MySQL Workbench Instruction
  • Jupyter and Anaconda Instruction

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