| WEEK | DATES | TOPIC | TASKS DUE | MATERIALS |
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| 1 | 1/16 | – Course Introduction and Syllabus – The Things You Can Do with Data – The Information Architecture of an Organization |
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| Understanding Database Schemas: Normalization, primary/foreign keys, joins | ||||
| 2 | 1/23 | In-class exercise #01: Creating database schema |
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| Getting data out of RDMS: SQL SELECT, DISTINCT MIN, MAX, COUNT, and WHERE | ||||
| 3 | 1/30 |
In-class exercise #02: Pen and Paper exercise |
Assignment 1: Database schema |
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| Getting data out of RDMS: Joining tables | ||||
| 4 | 2/6 | In-class exercise #03: Working with SQL, part 1 |
Assignment 2: SQL #1 |
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| In-class exercise #04: Working with SQL, part 2 | ||||
| 5 | 2/13 | Review for Exam 1 |
Assignment 3: SQL #2 |
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Introduction to Python In-class exercise #05: Getting familiar with Jupyter, Python Basic, Data types |
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| 6 | 2/20 |
Exam 1 |
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Python Data Structures In-class exercise #06: Python Lists and Dictionaries |
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| 7 | 2/27 |
Python Data Structures In-class exercise #06: Python Lists and Dictionaries
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| 9 | 3/13 |
In-class exercise #07: Working with semi-structured data Python and JSON In-class exercise #08: Working with JSON in Python |
Assignment 4: Python Basics |
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| 10 | 3/20 |
Python Pandas In-class exercise #09: Working with Python Pandas In-class exercise #10: More practice with Pandas Reconciling Data: The extract, transform, load process (ETL) ETL Lecture Recording now posted on Canvas via Zoom>Cloud Recordings |
Assignment 5: Python and JSON
View recording before next class on 3/27 |
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Principles of Data Visualization Lecture Recording
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View recording before next class on 3/27 |
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| 11 | 3/27 |
Principles of Data Visualization In-class exercise #11: Data Visualization Hypothesis Testing In-class exercise #12: Hypothesis Testing and Visualization in Python |
Assignment 6: Pandas |
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| Review for Exam 2 | ||||
| 12 | 4/3 | Exam 2 |
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| 13 | 4/10 |
Introduction to Advanced Analytics and Python Classification using Decision Trees In-class exercise #13: Decision Trees in Python |
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Assignment 7: Decision Trees |
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| 14 | 4/17 |
Analysis Scenario: Identifying similar customers (clustering and segmentation) In-class exercise #14: Clustering and Segmentation in Python |
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Assignment 8: Clustering |
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| 15 | 4/24 |
Analysis Scenario: What products are purchased together? (Association Rules) In-class exercise #15: Computing Confidence, Support, and Lift In-class exercise #16: Computing Confidence, Support, and Lift |
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Assignment 9: Association Rules |
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| 16 |
Exam 3 Review
Final Exam 5/1 5:45 – 7:45 |
PRO points project
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