生成式人工智慧
Generative Artificial Intelligence
| 節 | 週二 |
|---|---|
5 13:20–14:10 | 生成式人工智慧 EE105（光復） 3 節連堂 |
6 14:20–15:10 | |
7 15:30–16:20 |
* 根據陽明交大上課時間表所列
本課程介紹生成式人工智慧領域的最新技術，重點涵蓋大規模語言模型（LLM）、視覺-語言模型（VLM）及各種影像生成模型（如VAE、GAN、FLOW和擴散模型）。學生將學習這些模型的理論基礎、訓練方法及應用，並透過實作深入了解如何使用這些模型解決各類生成問題。
Introduction to Artificial Intelligence/Deep Learning/Machine Learning, Probability
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Homework *6 (75%) Class participation (25%)
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| 週次 | 主題 |
|---|---|
| 第 1 週 | Introduction to Generative AI 2026-02-24(二) |
| 第 2 週 | Large Language Models (I)-Fundamentals 2026-03-03(二) |
| 第 3 週 | Large Language Models (II)-Prompt Engineering with ICL and Fine-tuning [HW1: Prompt Engineering] 2026-03-10(二) |
| 第 4 週 | Large Language Models (III)-Different LLMs (from T5 to Llama 3) 2026-03-17(二) |
| 第 5 週 | Large Language Models (IV)-Text Generation [HW2: Paper Abstract Generation] 2026-03-24(二) |
| 第 6 週 | Large Language Models (V)-Retrieval-Augmented Generation 2026-03-31(二) |
| 第 7 週 | Large Language Models (VI)-Complex Reasoning in Natural Language 2026-04-07(二) |
| 第 8 週 | Large Language Models (VII)-LLM meets Real World Models [HW3: RAG for Specific Domains] 2026-04-14(二) |
| 第 9 週 | Data Crawling for Generative Models 2026-04-21(二) |
| 第 10 週 | Generative Computer Vision (I)-Introduction to Image Generation [HW4: Crawling Releases] 2026-04-28(二) |
| 第 11 週 | Generative Computer Vision (II)-VAE and FLOW 2026-05-05(二) |
| 第 12 週 | Generative Computer Vision (III)-Generative Adversarial Nets [HW5: Unconditional Image Generation Releases] 2026-05-12(二) |
| 第 13 週 | Generative Computer Vision (IV)-Diffusion Models 2026-05-19(二) |
| 第 14 週 | Generative Computer Vision (V)-Advanced Image Generation 2026-05-26(二) |
| 第 15 週 | Generative Computer Vision (VI)-Generative Models to Other Tasks [HW6: Conditional Image Generation Releases] 2026-06-02(二) |
| 第 16 週 | Vision-Language Pretrained Models 2026-06-09(二) |
Shivam R Solanki and Drupad K Khublani. Generative Artificial Intelligence-Exploring the Power and Potential of Generative AI. Springer, 2024. https://link.springer.com/book/10.1007/979-8-8688-0403-8
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