CS 504 - Principles of Data Management and Mining

Dr. Jessica Lin

Spring 2014

 

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 News & Announcements
2/3: Office hours for this week will be changed to 3-4pm on both Tuesday and Thursday.
2/4: HW1 posted. "Due date" 2/11. You don't need to submit this one, but be prepared to discuss your solution on the due date.
2/4: Update ER slides posted (see below). Slides #40 and #45 are new.
2/4: Sample Quiz 1
2/12: HW2 posted. There are two parts: part(a) due 2/18, part(b) due 2/25. You only need to submit part(b).
2/27: HW3 and the testbed posted.  "Due date" 3/4. You don't need to submit this one, but be prepared to discuss your solution on the due date.
3/5: Practice questions for the midterm, and the solutions.
4/9: HW5 posted. "Due date" 4/15. You don't need to submit this one, but you'll need to learn it for the next homework.
4/17:
HW6 Parts 1 & 2 are posted. Final write-up is due on 5/3, but please do Parts 1 & 2 by 4/29 for class discussion. I may quiz you on the homework on 4/29. The datasets are here.
4/29: HW6 Part 3 is added. The new dataset is here. The deadline is extended to 5/5 (Monday).
5/11: HW6 solutions posted.

Course Description (From Catalog)

Techniques to store, manage, and use data including databases, relational model, schemas, queries and transactions. On Line Transaction Processing, Data Warehousing, star schema, On Line Analytical Processing. MOLAP, HOLAP, and hybrid systems. Overview of Data Mining principles, models, supervised and unsupervised learning, pattern finding. Massively parallel architectures and Hadoop.

Instructor

Dr. Jessica Lin

Office: Engineering Building 4419
Phone: 703-993-4693
Email: jessica [AT] cs [DOT] gmu [DOT] edu
Office Hours:  Tuesday/Thursday 2-3pm

Classes

Tuesday
4:30-7:10pm
Robinson Hall B220

Prerequisites

Graduate Standing

Note: This course cannot be taken for credit by students of the MS CS, MS ISA, MS SWE, MS IS, CS PhD or IT PhD programs.

Grading

Quiz: 20%
Homework/Class Participation: 20%
Midterm: 25%

Final: 35%

Exams

There will be 4 or 5 quizzes, a midterm exam and a final exam covering lectures and readings (in class, closed book). The final exam is comprehensive. With the exception of the quizzes, which must be taken at the time they are given, prior arrangement needs to be made with the instructor if you cannot make it to the exam. Missed exams cannot be made up.

Honor Code Statement

Please be familiar with the GMU Honor Code. In addition, the CS department has its own Honor Code policies. Any deviation from this is considered an Honor Code violation. 

Disability Accommodations

If you are a student with a disability and you need academic accommodations, please see me and contact the Office of Disability Services (ODS) at 993-2474, http://ods.gmu.edu. All academic accommodations must be arranged through the ODS.

Textbooks

Required (both available in Safari Books):

Data Science for Business: What You Need To Know About Data Mining and Data-Analytic Thinking (Foster Provost and Tom Fawcett)

Making Sense of NoSQL: A Guide for Managers and the Rest of Us (Dan McCreary and Ann Kelly)

Various reading materials will also be given in class.

Tentative Schedule 
  
No Dates Topics Slides Notes
1
1/21
Class Cancelled (Snow day)


2
1/28
Introduction to Database Management
Intro

3
2/4
ER Model
ER
  HW1 posted
4
2/11
Relational Model 1
Relational Model
  Quiz 1
  HW1 due
  HW2 posted
5
2/18 Relational Model 2

  HW2 part(a) due
6
2/25 SQL
SQL
  HW2 part(b) due
  HW3 posted
  Quiz 2
7
3/4
Midterm Review

  HW3 due
8
3/11 Spring Break
 
9
3/18 Midterm

 
10
3/25 Post-midterm Review
Data Warehouse
Data Warehouse
11 4/1 NoSQL / MapReduce
NoSQL   HW4 posted
12 4/8 Data Mining 1
Data Mining: Intro   Quiz 3
  HW4 due
  HW5 posted
13 4/15 Data Mining 2
DM: Classification
(updated at 1:55am, 4/15, slides 62, 63, 65)
  HW5 due
  HW6 posted
14 4/22 Data Mining 3
DM: Model Evaluation
DM: Clustering
  Reading: Ch. 5 and Ch.
  6 in Data Science book
  Quiz 4
15 4/29 Data Mining 4
DM: Association Rules   Quiz 5
  HW6 due 5/5

16 5/6 No Class

 
17 5/13 Final Exam (4:30-6:30pm)