| 1 |
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Course Information (Syllabus) and Introduction to Data Analytics and R Programming |
Lecture & Discussion & Practice |
| 2 |
Literature Review, Assignment |
Basic Data Structures in R |
Lecture & Discussion & Practice |
| 3 |
Literature Review, Assignment |
Control Statements and Loops in R |
Lecture & Discussion & Practice |
| 4 |
Literature Review, Assignment |
Functions in R |
Lecture & Discussion & Practice |
| 5 |
Literature Review, Assignment |
Data Visualization with R |
Lecture & Discussion & Practice |
| 6 |
Literature Review, Assignment |
Data Preprocessing with R |
Lecture & Discussion & Practice |
| 7 |
Literature Review, Assignment |
Simple and Multiple Regression Models |
Lecture & Discussion & Practice |
| 8 |
Literature Review, Assignment |
K-Means Clustering Algorithm |
Lecture & Discussion & Practice |
| 9 |
Literature Review, Assignment |
K-Nearest Neighbors (KNN) Algorithm |
Lecture & Discussion & Practice |
| 10 |
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MID-TERM EXAM |
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| 11 |
Literature Review, Assignment |
Decision Trees: Regression and Classification |
Lecture & Discussion & Practice |
| 12 |
Literature Review, Assignment |
Random Forests: Regression and Classification |
Lecture & Discussion & Practice |
| 13 |
Literature Review, Assignment |
Q&A Session on Final Projects |
Lecture & Discussion & Practice |
| 14 |
Literature Review, Assignment |
Q&A Session on Final Projects |
Lecture & Discussion & Practice |
| 15 |
FINAL |
FINAL |
Lecture & Discussion & Practice |
| 16 |
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FINAL EXAM |
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| 17 |
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FINAL EXAM |
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