|
Date
|
Topic
|
Homeworks/Labs |
Readings
|
Handouts |
| 09/01 |
Intro, schedule, logistics |
|
Provost Ch. 1 |
dataScienceIntro |
| 09/03 |
Compoenents and tasks |
|
Provost Ch. 2 |
componentsTasks |
| 09/08 |
Data types |
project 1 out |
Aggarwal: Ch. 2.2 |
dataTypes |
| 09/10 |
Statistics foundations, intro to R |
|
|
statistics
R-tutorial |
| 09/15 |
Visual analytic, intro to D3 |
|
|
visualAnalytics
d3Intro |
| 09/17 |
Data preparation and reduction: data reduction |
|
Aggarwal: Ch. 2.3-2.4 |
dataPrep1 |
| 09/22 |
Project 1 presentations |
project 1 due |
|
|
| 09/24 |
Data preparation and reduction: transformation |
project 2 out |
Aggarwal:
Ch. 2.3-2.4 |
dataPrep2 |
| 09/29 |
Harvest Moon -- no class |
|
|
|
| 10/01 |
Data preparation and reduction: dimension reduction, LDA |
|
Aggarwal: Ch. 2.3-2.4 |
LDA |
| 10/06 |
Similarity and distance metrics |
|
Aggarwal: Ch. 3 |
similarity |
| 10/08 |
Cluster analysis I |
|
Aggarwal: Ch. 5.1-5 |
clusterAnalysis1 clustering |
| 10/13 |
Project 2 preparation |
|
|
|
| 10/15 |
Project 2 presentations |
project 2 due |
|
|
| 10/20 |
Cluster analysis II |
|
Aggarwal: Ch. 6.6-7 |
clusterAnalysis2 DBSCAN |
| 10/22 |
Pattern mining |
|
Aggarwal: Ch. 4 |
patternMining |
| 10/27 |
Final project prosposal prepartion |
final project proposal due |
|
|
| 10/29 |
Midterm |
|
|
|
| 11/03 |
Midterm discussion |
|
|
|
| 11/05 |
Outlier analysis |
|
Aggarwal: Ch. 8, 9 |
outlierAnalysis |
| 11/10 |
Classifiers |
|
Aggarwal: Ch. 10 |
classifiers |
| 11/12 |
Classifiers: advanced concepts
|
|
Aggarwal: Ch. 11 |
see above |
| 11/17 |
Optimization methods |
|
|
optimization |
| 11/19 |
Final project progress presentation |
final project preliminary report due |
|
|
| 11/24 |
Tine series |
|
Aggarwal: Ch. 14 |
timeSeries |
| 11/26 |
Final project session |
|
|
|
| 12/01 |
Streaming Data |
|
Aggarwal: Ch. 12 |
streamData |
| 12/03 |
Graph data mining |
|
Aggarwal: Ch. 17 |
graphMining |
| 12/08 |
Data journalism |
|
|
|
| 12/15 |
Final project presentations (3:15-5:45pm) |
|
|
|
