CSCI 479: Fall 2026
Course Schedule

Dates and topics are approximate and are subject to change.
 
Dates Topics Labs Assignments/Quizzes Exams
Week 1 Introduction(Sept. 9) - - -
Week 2 Data(Sept. 14)
Information based learning I(Sept. 16)
Lab 1 - Data preprocessing A1 - Decision tree application -
Week 3 Information based learning II(Sept. 21)
Information based learning III(Sept. 23)
Lab 2 - Information based binning algorithm - -
Week 4 Similarity based learning I(Sept. 28) Lab 3 - data transformation and distance function A2 - Similarity application -
Week 5 Similarity based learning II(Oct. 5)
Probability based learning I(Oct. 7)
Lab 4 - Probability algorithms - -
Week 6 Probability based learning II(Oct. 13)
Error based learning I(Oct. 14)
Lab 5 - Bayesian Belief Network A3 - Probability applications -
Week 7 Midterm (Oct. 19)
Error based learning II(Oct. 21)
- - Midterm
Week 8 Error based learning III(Oct. 26)
Deep Learning(Oct. 28)
Lab 6 - Neural network algorithm A4 - Regression model -
Week 9 Error based learning IV(Nov. 2)
Predictive Model Evaluation(Nov. 4)
Lab 7 - Model evaluation - -
- November 9-13
Fall Study Week
- - -
Week 10 Predictive Model Evaluation(Nov. 16)
Cluster Analysis I(Nov. 18)
Lab 8 - Model and Evaluation A5 - Clustering application -
Week 11 Cluster Analysis II(Nov. 23)
Outliers(Nov. 25)
Lab 9 - Linear Regression Model - -
Week 12 Association I(Nov. 30)
Association II(Dec. 2)
Lab A - Association Analysis algorithm - -
Week 13 Association III(Dec. 7)
Summary/Final Review(Dec. 9)
(Optional) Presentation - -

Last updated: September 3, 2026