DATX 6905 - Predictive Modeling Algorithms
Fall 2026 Syllabus, Section 01, CRN 43056,
Credit hours: 3
Course Meeting Times
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Instructor
G. Jay Kerns
Email: gkerns@ysu.edu
Course Description
6905. Predictive Modeling Algorithms. Predictive modeling (also referred to predictive analytics and machine learning) applies statistical techniques in analyzing data to predict outcomes. Through a hands-on approach, this course helps students develop basic skills in predictive analytics. Topics may include (not limited to) k-nearest neighbors, naïve-Bayes, linear and logistic regression models, time-series models, classification and regression trees, Principal Component/Factor Analysis, non-linear models, neural networks, random forests, and cluster analysis among others. Credit will not be given for both DATX 5805 and DATX 6905. Prereq.: Graduate Standing. 3 s.h.
Course Readings
| Group | Title | Author | ISBN |
|---|---|---|---|
| Required | An Introduction to Statistical Learning | Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani | 978-1-0716-1420-4 |
The textbook is freely available at https://www.statlearning.com/.
The course readings are subject to change in the event of extenuating circumstances, research developments, current events, and/or to ensure better learning.
Assignments/Assessments
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Schedule of Topics and Assignments
| Week of | Reading(s) | Proposed Topic | Due/To Prepare for Class |
|---|---|---|---|
| 8/24 | Ch2: Sections 1&2 | Statistical Learning, Assessing Model Accuracy, Introduction to R | Quiz 1 & Assignment 1 |
| 9/7 | Ch3: Sections 1-6 | Linear Regression Models | Quiz 2 & Assignment 2 |
| 9/21 | Ch4: Sections 1-3, 6 | Classification, Logistic Regression, Generalized Linear Models | Quiz 3 & Assignment 3 |
| 10/5 | Ch5: 1-3, excluding 5.3.4 | Cross-Validation, The Bootstrap | Assignment 4 |
| 10/19 | Ch6: Sections 1-5 | Linear Model Selection and Regularization | Quiz 4 & Assignment 5 |
| 11/2 | Ch8: 1-3 excluding 8.2.4, 8.2.5, and 8.3.5 | Tree-Based Methods | Quiz 5 & Assignment 6 |
| 11/16 | Ch12: 1-2, 4-5, excluding 12.5.2 | The Challenge of Unsupervised Learning, Principal Components Analysis, Clustering Methods | Quiz 6 |
The course schedule, policies, procedures, and assignments in this course are subject to change in the event of extenuating circumstances, by mutual agreement, and/or to ensure better learning.