### 2021

#### Fall

- Programming Methodology (Undergraduate)

#### Spring

- Adaptive Machine Learning and Explainable AI (Graduate)

### 2020

#### Fall

- Introduction to Machine Learning (Undergraduate)
- Learning Theory (Graduate)

### 2019

#### Fall

- Convex Optimization (Graduate)

#### Spring

- Neural Networks (Deep Learning) (Graduate)
- Advanced Machine Learning (Undergraduate)
- Introduction to Programming with Python (Undergraduate)

### 2018

#### Fall

- Introduction to Machine Learning (Undergraduate)
- Probability and Random Processes (Undergraduate)

#### Spring

- Neural Networks (Deep Learning) (Graduate)
- Advanced Machine Learning (Undergraduate)

### 2017

#### Fall

- Circuit Theory (Undergraduate)
- Probability and Random Processes (Undergraduate)

#### Spring

- Neural Networks (Deep Learning) (Graduate)
- Introduction to Machine Learning (Undergraduate)

### 2016

#### Fall

#### Spring

- Data Structure and Algorithms (Undergraduate)
- Introduction to Machine Learning (Undergraduate)

### 2015

#### Fall

- Probability and Random Processes (Graduate)