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  • Subjects Covered in the Class

IDIS 450 — Syllabus

Subjects Covered in the Class

Week Topic Reading Laboratory
1 Introduction to Business Analytics Intro. to Python
2 Probability and Statistics Review KJ Chapters 1–2 Intro. to Python
3 Data Pre-processing KJ Chapter 3 Data Pre-processing
4 Descriptive Analytics and Visualization KJ Chapter 4 Data Visualization (MS Power BI)
5 Sampling and Estimation KJ Chapter 5
6 Statistical Inference KJ Chapter 6 Statistical Inference
7 Linear Regression KJ Chapter 7 Linear Regression
8 Logistic Regression KJ Chapter 8 Logistic Regression
9 Classification and Regression Tree Models KJ Chapter 11 Decision Trees and Random Forest
10 Artificial Neural Network KJ Chapter 12 Artificial Neural Network
11 Support Vector Machine KJ Chapter 13 Support Vector Machine
12 K-Nearest Neighbor KJ Chapter 14 K-Nearest Neighbor
13 K-Means Clustering K-Means Clustering

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