Course Syllabus

Course Information：

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Spring Semester Year 2026	357410	Building Deep Learning Applications	1	3.0	3	★	Kuan-Ting Lai	ECE IEECSG SSRT MSAI	17	0	Jointly offered by Electronic Engineering department and Smart Railway Program.

Course Plan：

Instructor	Kuan-Ting Lai　Office Hours
Email	ktlai@ntut.edu.tw
Last Updated	2025-12-19 13:38:49
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. Large Language Models (LLMs), ChatGPT, Gemini, DeepSeek 12. Retrieval Augmentation Generation (RAG) 13. Object Detection and Segmentation 14. Generative Adversarial Networks (GAN) and Diffusion models 15. Deep Reinforcement Learning and Stable Baseline 16. Graph Convolution Networks (GCNs) 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
The course corresponds to the SDGs	SDG3：良好健康和福祉（Good Health and Well-being） SDG4：優質教育（Quality Education） SDG8：尊嚴就業與經濟發展（Decent Work and Economic Growth） SDG10：減少不平等（Reduced Inequalities）
Does the course incorporate AI	● 使用生成式AI作為教學過程的輔助工具（Use generative AI tools as an aid to the teaching process） ● 鼓勵學生使用生成式AI工具（Encourage students to use generative AI tools） ● 使用生成式AI進行課堂即時互動（Use generative AI for real-time classroom interaction） ● 簡單介紹AI的基本概念（Briefly introduce the basic concept of AI） ● 深入探討AI的原理與應用（Explore the principles and applications of AI in depth）
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