教學大綱與進度

課程基本資料：

學年期	課號	課程名稱	階段	學分	時數	修	教師	班級	人	撤	備註
114-1	357744	智慧專利分析	1	3.0	3	★	邱弘緯	AI雙聯專班	11	0	碩二修, 9/14.21,10/19,11/2.9.16.30,12/7.14

教學大綱與進度：

教師姓名	邱弘緯　教師諮商時間(Office Hours)
Email	hwchiu@ntut.edu.tw
最後更新時間	2025-09-01 19:59:18
課程大綱	Course Description: This course offers an in-depth exploration into patent analytics. Participants will traverse topics such as research methodologies specific to patents, foundational aspects of patent law, the pivotal role of semiconductors in patenting, keyword-centric patent searches complemented by pertinent case studies, the integration of linguistics and logic in understanding patents, the practical applications of ChatGPT, and the utility of Natural Language Processing in patent data analysis. Course Topics: 1. Research Methodology in Patent Analytics: • Overview of innovation trends • Analyzing McKinsey and Gartner reports for patent insights 2. Basics of Patent Law: • Intellectual Property: Understanding the Basics • What makes an invention patentable? • Constructing and analyzing a patent claim • Understanding patent structures • The thin line between innovation and non-obviousness • Crafting an effective patent strategy 3. Semiconductors and Their Importance in Patenting: • Introduction to semiconductor processes, manufacturing, and devices • Deep dive into VLSI design, IP, MCU, CPU, GPU, firmware, OS, and software • A look at solid-state devices • Advanced Process Technologies (Refer to Advanced-Process-Technologies.pdf for detailed insights) 4. Keyword-driven Patent Search & Case Studies: • Patent cases on advanced devices: Planar FET, FinFET, GAA • Patent cases involving AI methodologies 5. Language, Logic, and Meaning in Patent Analysis: • Introduction to linguistics in patent analysis (Reference: https://chowkafat.net/Lingtopic.html) • Basics of semantics and its importance in patent comprehension • Deep dive into formal semantics and generalized quantifier theory • Deciphering the logical form and structure in patents • Introduction to propositional logic and its application in patent analysis • Unraveling predicate logic in patent contexts 6. Practical Applications using ChatGPT: • Using ChatGPT for instructional language and problem-solving in patent analytics • Case study: Constructing a GAA using ChatGPT • ChatGPT in research methodologies and patent search 7. Natural Language Processing (NLP) in Patent Analysis: • Understanding word embedding and word vectors • Techniques for determining similarity in patent documents using NLP
課程進度	W1 Research Methodology in Patent Analytics W2,3 Basics of Patent Law W4 Semiconductors and Their Importance in Patenting W5 Keyword-driven Patent Search & Case Studies W6 Language, Logic, and Meaning in Patent Analysis W7 Practical Applications using ChatGPT W8,9 Natural Language Processing (NLP) in Patent Analysis
評量方式與標準	1. Homework assignments - 40% 2. Mid-term project 30% 3. Final proejct 30%
使用教材、參考書目或其他	【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】 使用外文原文書：否 • https://twpat.tipo.gov.tw/ • https://patents.google.com/ • Python Data Science Handbook by Jake VanderPlas, O'Reilly Media, Inc. (ebook available on https://jakevdp.github.io/PythonDataScienceHandbook/ ) • Data science from scratch by Joel Grus, O’Reilly Media, Inc., 2019 ISBN: 9781492041139 • Natural Language Processing Specialization https://github.com/amanjeetsahu/Natural-Language-Processing-Specialization
課程諮詢管道	Course Line and Teams group
課程對應SDGs指標	SDG4：優質教育（Quality Education） SDG8：尊嚴就業與經濟發展（Decent Work and Economic Growth） SDG9：產業創新與基礎設施（Industry, Innovation and Infrastructure） SDG16：和平正義與有力的制度（Peace, Justice and Strong Institutions）
課程是否導入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）
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