Course Syllabus

Course Information：

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Spring Semester Year 2024	328215	Building Deep Learning Applications	1	3.0	3	★	Kuan-Ting Lai	ECE IEECSG GEECS MSAI	65	0	電子所、電資、創新AI和電資外生所合開

Course Plan：

Instructor	Kuan-Ting Lai　Office Hours
Email	ktlai@ntut.edu.tw
Last Updated	2024-05-16 11:07:31
Course Objective	The goal of this course is to give students a broad overview of state-of-the-art deep learning algorithms, and teach students how to develop deep learning applications by hands-on coding examples. Most examples taught in this class are based on the TensorFlow framework. We will cover many different fields including image classification, object detection, natural language processing, reinforcement learning and generative adversarial networks.
Course Schedule	Course website: http://www.aiotlab.org/teaching/dl_app.html 1. Introduction to Deep Learning 2. Applied Math (Linear Algebra, Probability, Calculus) 3. Machine Learning Basics 4. TensorFlow & Keras 5. Convolutional Neural Networks (CNN) 6. Advanced Keras API & PyTorch 7. Natural Language Processing (NLP), Word Embedding, Self-supervised Learning 8. Midterm exam 9. Recurrent Neural Networks (RNN) & Long Short-term Memory (LSTM) 10. Attention is all you need! Attention and Transformer 11. Foundation Models, ChatGPT, and Hugging Face 12. Object Detection and Segmentation 13. Generative Adversarial Networks (GAN) 14. Diffusion is all you need? Stable diffusion, midjourney, DALL-E 15. Deep Reinforcement Learning and Stable Baseline 16. Graph Convolution Networks (GCN) 17. Final project demo 18. Final exam
Evaluation and grading policy	Homework (40%), Midterm and Final Exam (35%), Final Project (15%), Quizzes and attendance (10%)
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes 1. Francois Chollet, “Deep Learning with Python, 2nd edition” Manning, 2021 2. Ian Goodfellow, Yoshua Bengio, and Aaron Courville, “Deep Learning,” MIT Press, 2017 3. Latest publications on CVPR, NIPS, ICML, AAAI, ICLR Website: http://www.aiotlab.org/teaching/dl_app.html
The access to curricular consultation	FB Group: https://www.facebook.com/groups/2231151677158713 Email: ktlai@ntut.edu.tw NOTE: About week 17 & 18, we will have online final project presentation. Please upload your final project videos to YouTube.
The course corresponds to the SDGs
Note	All quizzes, exams and homework will be made online using Microsoft Teams. For final project, students will need to submit a YouTube video. Any announcements will be posted in Microsoft Teams. Website: http://www.aiotlab.org/teaching/dl_app.html FB Group: https://www.facebook.com/groups/2231151677158713