Fall 2016
1. Introduction to Object Oriented Programming (2 Combined Sessions with labs)
Spring 2017
1. Introduction to Object Oriented Programming (2 Combined Sessions w/o labs)
2. Machine Learning (Undergraduate Session and Graduate Session)
Fall 2017
1. Introduction to Object Oriented Programming (2 Combined Sessions with labs)
Spring 2018
1. Introduction to Object Oriented Programming (2 Separate Sessions with labs)
Fall 2018
1. Introduction to Object Oriented Programming (1 Session with lab)
2. Introduction to Machine Learning (Undergraduate)
Spring 2019
1. Introduction to Object Oriented Programming (1 Session with lab)
2. Machine Learning (Graduate)
3. Advanced Programming Workshop - Matlab
Fall 2019
1. Introduction to Object Oriented Programming - Honors (1 Session with lab)
2. Machine Learning (Undergraduate)
Spring 2020
1. Introduction to Object Oriented Programming (1 Session with lab)
2. Machine Learning (Graduate)
3. Advanced Programming Workshop - Matlab
Fall 2020
1. Machine Learning (Undergraduate)
2. Machine Learning I (Graduate)
3. Concepts in Artificial Intelligence (Graduate)
Spring 2021
1. Machine Learning (Undergraduate)
2. Machine Learning I (Graduate)
3. Data Mining I (Graduate)
Fall 2021
Introduction to Data Mining (Undergraduate)
Data Mining 1 (Graduate )
Machine Learning II (Graduate/Undergraduate)
Spring 2022
1. Machine Learning (Undergraduate)
2. Machine Learning I (Graduate)
Fall 2022
Introduction to Data Mining (Undergraduate)
Data Mining 1 (Graduate )
Spring 2023
Data Mining 1/Introduction to Data Mining (Graduate/Undergraduate Cross-listed)
Machine Learning 1/Machine Learning (Graduate/Undergraduate Cross-listed)
Fall 2023
Data Mining 1 (Graduate )
Machine Learning II (Graduate)
Spring 2024
1. Machine Learning I (Graduate)
Fall 2024
Data Mining 1 (Graduate)
Spring 2025
1. Machine Learning I (Graduate)
Fall 2025
Data Mining 1 (Graduate)
Previously at NTU:
2011/2012 Semester 2:
1. CZ1001 Discrete Mathematics (2 Example Classes)
2. CSC304 Artificial Intelligence and Intelligent Systems (2 Tutorial Classes)
2012/2013 Semester 1:
1. CZ1001 Discrete Mathematics (2 Example Classes)
2. CSC304 Artificial Intelligence and Intelligent Systems (Lecture: Week 8-14; 1 Tutorial Class)
2012/2013 Semester 2:
1. CE9004/CM104 Reasoning with Objects (Lecture: Week 1-7; Tutorial Class: Week 1-7)
2. CSC304/CPE406/CZ3005 Artificial Intelligence and Intelligent Systems (3 Tutorial Classes)
2013/2014 Semester 1:
1. BI6104 Biostatistics (Lecture: Week 1-13)
2. CZ3002 Advanced Software Engineering (2 Tutorial Classes)
2013/2014 Semester 2:
1. CE9004/CM104 Reasoning with Objects (Lecture: Week 1-7; Tutorial Class: Week 1-7)
2. CZ4033/CPE490/CSC490 Advanced Data Management (Lecture/Tutorial: Week 10-12 – 5 Lectures)
3. CSC304/CPE406/CZ3005 Artificial Intelligence and Intelligent Systems (2 (+2) Tutorial Classes)
2014/2015 Semester 1:
1. CSC304/CPE406/CZ3005 Artificial Intelligence and Intelligent Systems (Lecture: Week 8-14; 1 Tutorial Class)
2. CZ3002 Advanced Software Engineering (2 Tutorial Classes + 2 labs)
2014/2015 Semester 2:
1. CSC304/CPE406/CZ3005 Artificial Intelligence and Intelligent Systems (Lecture: Week 1-7; 3 Tutorial Classes; 3 Labs)
2015/2016 Semester 1:
1. CZ3005 Artificial Intelligence (Lecture: Week 8-13; 1 Tutorial Class)
2. CE/CZ1008 and CE/CZ1011 Engineering Mathematics (3 Example Classes)
2015/2016 Semester 2:
1. CZ3005 Artificial Intelligence (Lecture: Week 1-7; 2 Tutorial Classes; 1 Lab)
2. CE/CZ1008 and CE/CZ1011 Engineering Mathematics (2 Tutorials; 2 Labs)