Prerequisites

Please note that all courses offered here are advanced courses. Students are expected to be familiar with undergraduate-level mathematics and programming, and able to implement algorithms in python from mathematical derivations.

• Probability and Statistics (STA1001)

• Calculus (STA1002)

• Linear Algebra (STA2102)

• Python Programming (STA2104)

• Data Structures and Algorithms (STA3135)

• (Optional) Experiences taking other advanced courses (STA3126, STA3109, STA3125, STA3140, STA3141, STA4103, ...)

Graduate courses

STA9131 Deep Learning for Visual Recognition @ Spring 2022-2024

This course is a deep dive into the details of neural network-based deep learning methods for computer vision.

Equivalent to CS231n @ Stanford or EECS498/598 @ UMich (by Justin Johnson)

STA9132 Advanced Deep Learning @ Fall 2022-2024

This course discusses recent research topics in deep learning.

GEV6135 Deep Learning for Visual Recognition and Applications @ Fall 2022, 2024 (for Graduate School of Engineering)

This course is a deep dive into the details of neural network-based deep learning methods for computer vision and their applications, focusing on image classification.

Equivalent to the first half of CS231n @ Stanford or EECS498/598 @ UMich (by Justin Johnson)

Undergraduate courses

STA3142 Statistical Machine Learning @ Spring 2022-2024

This course provides a broad introduction of machine learning for students with statistics background.

Equivalent to CS229 @ Stanford or EECS545 @ UMich

Note: this course is different from statistical machine learning courses in many other universities, in that 1) students are asked to implement core ML algorithms (rather than just using libraries), and 2) about 1/3 of lectures are reserved for deep learning. If you are looking for course equivalency, STA4103 Data Mining would be a better candidate in general.

Here is the list of courses that are previously not accepted for course equivalency:

• DAT 402 Machine Learning for Data Science @ Arizona State University

• STAT 154 Modern Statistical Prediction and Machine Learning @ UC Berkeley

• PSTAT 131/231 Introduction to Statistical Machine Learning @ UC Santa Barbara

• Fundamentals of Machine Learning @ Autonomous University of Barcelona

• STAT 207 Data Science Exploration @ UIUC

• MATH30028 Statistical Machine Learning @ University of Bristol

• STAT C161 Introduction to Pattern Recognition and Machine Learning @ UCLA

STA3143 Computer Vision for Data Science @ Fall 2022-2024

This course provides a broad introduction of computer vision for data science.

Equivalent to  EECS442 @ UMich,

or some topics in CS131 @ Stanford + the first half of CS231n @ Stanford or EECS498/598 @ UMich (by Justin Johnson)