INFO 523: Data Mining & Discovery

Dr. Greg Chism

This page contains an outline of the topics, content, and assignments for the semester. Note that this schedule will be updated as the semester progresses and the timeline of topics and assignments might be updated throughout the semester.

Week Date Topic Prepare Due
1 Wed, Jan 10 Lec 0
2 Wed, Jan 17 Lec 1
Fri, Jan 19

RQ 1

3 Wed, Jan 24 Lec 2
4 Wed, Jan 31 Lec 3

📝 HW 1

5 Wed, Feb 7 Lec 4

📑 Project 1 proposals for peer review

6 Mon, Feb 12

📑 Project 1 proposals for instructor review

Wed, Feb 14 Lec 5

RQ 2

7 Wed, Feb 21 Lec 6

📝 HW 2

8 Wed, Feb 28 Lec 7

Classification II
Model Evaluation

9 Wed, Mar 6 No Class

Spring Break ☀️

10 Mon, Mar 11
Wed, Mar 13 Midterm

Project 1 Presentations
Final Project Preview

📑 Project 1

11 Wed, Mar 20 Lec 8

Regression I

📝 HW 3
✅ RQ 3

12 Mon, Mar 25
Wed, Mar 27 Lec 9

Final Project Peer Review
Regression II

📑 Project 2 proposals for peer review

13 Mon, Apr 1

📑 Project 2 proposals for instructor review

Wed, Apr 3 Lec 10

Regressions III

📝 HW 4

14 Wed, Apr 10 Lec 11

Support Vector Machines

✅ RQ 4

Fri, Apr 12
15 Wed, Apr 17 Lec 12

Unsupervised Learning Methods I

16 Wed, Apr 24 Lec 13

Unsupervised Learning Methods II

Fri, Apr 26

📝 HW 5

17 Mon, Apr 29
Wed, May 1 Lec 14

Association Rules

✅ RQ 5

Finals Mon, May 6 Final

Final Project Presentations @ 1pm

📑 Final Project
📝 HW 6