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What's inside
Syllabus
生成式 AI 提升工作效率
本單元將說明 Gemini for Google Workspace 的核心功能和商業價值。
為生成式 AI 應用程式撰寫提示詞
本單元將探討如何使用 Gem 和 NotebookLM 等生成式 AI 工具將工作流程自動化，以及透過建立基準，確保語言模型產生準確的回覆。
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Syllabus
生成式 AI 提升工作效率
本單元將說明 Gemini for Google Workspace 的核心功能和商業價值。
為生成式 AI 應用程式撰寫提示詞
本單元將探討如何使用 Gem 和 NotebookLM 等生成式 AI 工具將工作流程自動化，以及透過建立基準，確保語言模型產生準確的回覆。
Read more
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生成式 AI 應用程式: 徹底改變工作方式.
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Learners who complete 生成式 AI 應用程式: 徹底改變工作方式 will develop knowledge and skills
that may be useful to these careers:
提示工程師
提示工程師
提示工程師專注於設計、測試並優化與生成式AI模型互動的指令，以確保輸出符合預期。本課程深入探討了「為生成式 AI 應用程式撰寫提示詞」的藝術與科學，這對於一位傑出的提示工程師至關重要。學員將學習如何有效地構建提示詞，以及如何透過建立基準來確保語言模型回應的準確性。這些技能直接應用於工作中，使學員能夠產出高品質、可靠的AI內容，並推動自動化工作流程的效率。
AI應用專員
AI應用專員
AI應用專員負責探索、實施並管理組織內部的生成式AI工具與應用程式，以提升營運效率與創新。本課程以Google的生成式AI應用程式為核心，例如Gemini for Workspace和NotebookLM，並闡述了Gemini for Google Cloud的核心功能和商業價值。學員將學習如何有效地應用這些工具來「徹底改變工作方式」，理解其如何「提升工作效率」。對於希望成為AI應用專員的學員而言，本課程提供了掌握當前主流AI應用工具與策略的實務知識，幫助他們將理論轉化為實際的業務成果。
自動化工作流程設計師
自動化工作流程設計師
自動化工作流程設計師負責分析現有流程，並透過整合技術來創建高效能的自動化系統。本課程明確涵蓋了「打造自動化工作流程」這一核心概念，並引導學員運用Gemini for Workspace和NotebookLM等生成式AI工具來實踐。學員將理解如何規劃、實施並優化由AI驅動的自動化方案，提升組織的生產力。「生成式 AI 應用程式: 徹底改變工作方式」這門課程正是培養此角色所需實務技能的理想起點，讓學員能夠有效地利用生成式AI來簡化和加速業務營運。
业务流程优化师
业务流程优化师
業務流程優化師致力於識別、分析並改進企業的運營流程，以提升效率、降低成本並改善服務品質。本課程探討了運用生成式AI應用程式來「徹底改變工作方式」和「提升工作效率」的策略。學員將學習如何利用Gemini for Workspace和NotebookLM等工具來「打造自動化工作流程」，並了解這些AI工具的商業價值。這些知識對於業務流程優化師來說至關重要，他們可以藉此設計並實施由AI驅動的創新解決方案，推動組織轉型，實現更精簡、更智慧的營運模式。
解决方案架构师
解决方案架构师
解決方案架構師負責設計和規劃複雜的技術系統，確保它們符合業務需求並可擴展。本課程介紹了Google的生成式AI應用程式，包括Gemini for Workspace和Gemini for Google Cloud，並涵蓋了關鍵概念如檢索增強生成和建構有效的提示詞。這些內容對於解決方案架構師來說非常相關，因為他們需要理解如何將這些AI技術整合到現有或新開發的系統中，以「打造自動化工作流程」。本課程賦予學員建構以生成式AI為核心的創新解決方案所需的知識，實現真正的業務轉變。
數位轉型顧問
數位轉型顧問
數位轉型顧問協助企業客戶評估現有技術，並規劃、實施數位化策略，以應對市場變化並提升競爭力。本課程名為「生成式 AI 應用程式: 徹底改變工作方式」，直接呼應了數位轉型的核心目標。學員將深入了解Google的生成式AI應用程式，如Gemini for Workspace和Gemini for Google Cloud，及其「核心功能和商業價值」。對於數位轉型顧問而言，這門課程提供了評估和整合新興AI工具的知識，使他們能夠提出具體、可行的AI解決方案，幫助客戶利用生成式AI實現業務模式的創新與效率提升。
产品经理
产品经理
產品經理負責產品的生命週期管理，從概念發想、開發到市場發布。本課程深入探討了生成式AI應用程式，例如Gemini for Workspace和Gemini for Google Cloud的「核心功能和商業價值」，這對於產品經理評估新功能或開發新AI產品至關重要。學員將理解如何利用生成式AI來「徹底改變工作方式」，並學習「為生成式 AI 應用程式撰寫提示詞」的概念。這使產品經理能夠更好地定義產品需求、預測市場趨勢，並引導團隊開發出更具創新性和市場競爭力的AI驅動產品。
技術培訓師
技術培訓師
技術培訓師負責向員工或客戶教授特定軟體、硬體或技術系統的使用方法和最佳實踐。本課程詳細介紹了Google的生成式AI應用程式，例如Gemini for Workspace和NotebookLM，並解釋了如何「為生成式 AI 應用程式撰寫提示詞」和「打造自動化工作流程」。對於希望成為技術培訓師的人來說，本課程提供了全面且實用的知識，讓他們能夠有效地向他人傳授如何利用生成式AI工具「提升工作效率」。學員將掌握清晰傳達複雜AI概念所需的專業理解。
內容策略經理
內容策略經理
內容策略經理負責規劃、開發和管理企業內容，確保其符合品牌目標並吸引目標受眾。本課程介紹了生成式AI應用程式，並探討了「為生成式 AI 應用程式撰寫提示詞」的概念。這對於內容策略經理來說可能很有幫助，因為生成式AI是內容生成和優化日益重要的工具。了解如何有效地與這些工具互動，例如透過建立基準來確保語言模型的準確性，可以讓內容策略經理在規劃和執行內容策略時，更具效率和創新性，並利用AI來「提升工作效率」。
行銷自動化專家
行銷自動化專家
行銷自動化專家設計、實施並管理自動化行銷活動，以提升客戶參與度並優化行銷效率。本課程明確探討「打造自動化工作流程」，並介紹了如何使用Gemini for Workspace等生成式AI工具來增強效率。對於行銷自動化專家而言，掌握如何「為生成式 AI 應用程式撰寫提示詞」以生成行銷內容或自動化客戶互動，是極具價值的。本課程使學員能夠將生成式AI應用於行銷自動化策略中，從內容生成到客戶服務機器人，全面提升行銷活動的智慧化與個性化水平。
数据分析师
数据分析师
數據分析師負責收集、處理和解釋數據，以揭示趨勢、發現見解並支持業務決策。本課程介紹了生成式AI應用程式，並涵蓋了「建立基準」以確保語言模型產生準確回覆的概念，這對於數據分析師來說可能很有幫助。雖然本課程不專注於傳統數據分析方法，但理解AI如何處理和生成信息，以及如何評估其準確性，能讓數據分析師在處理由AI生成的數據或應用AI工具輔助分析時，具備更全面的視角。這門課程有助於拓寬數據分析師在AI應用領域的視野。
專案經理
專案經理
專案經理負責規劃、執行與監督專案，確保其按時、按預算完成並達成目標。本課程介紹了生成式AI應用程式，並探討了如何利用這些工具「提升工作效率」和「打造自動化工作流程」的商業價值。對於專案經理而言，了解這些AI應用程式，例如Gemini for Workspace和NotebookLM，可能會有幫助。他們可以識別在專案管理中潛在的AI應用場景，例如自動化報告或溝通，從而優化專案流程。透過這門課程，專案經理或許能夠更好地整合AI工具，提升團隊的生產力，並在AI驅動的專案中做出更明智的決策。
学习与发展专家
学习与发展专家
學習與發展專家負責設計、實施並評估組織的員工培訓和發展計畫。本課程介紹了生成式AI應用程式，以及如何利用這些工具「提升工作效率」和「打造自動化工作流程」。對於學習與發展專家而言，理解這些技術可能會有用。他們可以探索如何將生成式AI整合到培訓材料的開發中，或利用AI工具自動化某些學習管理任務。這門課程讓學員了解AI在工作場域中的應用潛力，可能啟發他們設計更具創新性和效率的學習解決方案，以適應不斷變化的工作環境。
資訊科技支援專家
資訊科技支援專家
資訊科技支援專家負責協助使用者解決軟硬體問題，並提供技術指導。本課程介紹了Google的生成式AI應用程式，如Gemini for Workspace和NotebookLM，以及Gemini for Google Cloud。對於資訊科技支援專家而言，了解這些在組織中日益普及的AI工具可能會有幫助，因為他們未來可能會處理與這些應用程式相關的使用者查詢或問題。本課程提供對AI應用程式功能和商業價值的基礎理解，使他們能夠在支援使用者時，更全面地處理與生成式AI相關的需求，並引導使用者更好地利用這些工具「提升工作效率」。
AI倫理與治理顧問
AI倫理與治理顧問
AI倫理與治理顧問協助組織建立和實施負責任的AI使用政策，確保技術部署符合道德標準和法規。本課程介紹了生成式AI應用程式，並強調了「建立基準」以確保語言模型產生「準確的回覆」的重要性。對於AI倫理與治理顧問而言，理解這些技術的實際操作，特別是輸出準確性與可靠性的管理，可能會有幫助。這門課程雖然不直接教授倫理治理原則，但它提供了對生成式AI應用程式及其限制的實務視角，有助於他們評估這些工具在企業中的負責任部署，並制定更切實可行的治理框架。
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Reading list
We haven't picked any books for this reading list yet.
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Provides a thought-provoking exploration of the future of generative AI, discussing its potential benefits and risks. It is written by Gary Marcus, a leading researcher in the field.
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Explores the potential impact of generative AI on society, discussing how it could be used to solve social problems and improve quality of life. It is written by Kai-Fu Lee, a leading researcher in the field.
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Explores the relationship between generative AI and the creative process, discussing how generative AI can be used to enhance creativity. It is written by Margaret Boden, a leading researcher in the field.
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Explores the potential impact of generative AI on the law, discussing how it could be used to automate legal processes and improve access to justice. It is written by Ryan Abbott, a leading researcher in the field.
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Provides a practical guide to using generative AI, covering the different techniques and tools available. It is written by two leading experts in the field, Josh Patterson and Adam Gibson.
Explores the potential applications of generative AI in climate change, discussing how it could be used to model climate change and develop solutions. It is written by Andrew Ng, a leading researcher in the field.
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Provides a business-oriented perspective on generative AI, discussing its potential impact on industries and how companies can use it to gain a competitive advantage. It is written by three leading experts in the field, Thomas Davenport, Rajeev Ronanki, and Nitin Mittal.
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Explores the philosophical implications of generative AI, discussing how it challenges our understanding of mind and consciousness. It is written by Daniel C. Dennett, a leading philosopher in the field.
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Explores the potential applications of generative AI in healthcare, discussing how it could be used to improve patient care and accelerate drug discovery. It is written by Eric Topol, a leading researcher in the field.
Explores the potential impact of generative AI on the economy, discussing how it could be used to create new jobs and improve productivity. It is written by two leading experts in the field, Erik Brynjolfsson and Andrew McAfee.
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Covers the use of prompt engineering for finance. It is written by Richard Roll, a leading researcher in the field of finance.
Focuses on the use of prompt engineering for recommendation systems. It is written by Masashi Sugiyama, a leading researcher in the field of recommendation systems.
Focuses on the use of prompt engineering for natural language processing. It is written by Thomas Wolf, a leading researcher in the field of NLP.
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Focuses on the use of prompt engineering for education. It is written by Salman Khan, a leading researcher in the field of education.
Focuses on the creative aspects of prompt engineering and generating diverse language outputs. It's a good fit for students and professionals looking to go beyond basic prompting and explore more advanced techniques for creative content generation. It adds breadth by covering applications in areas like creative writing and podcasting.
This guide aims to make prompt engineering accessible with a step-by-step approach. It is well-suited for beginners and those new to the field, including high school students and those in introductory undergraduate programs. It provides practical tips and is useful for gaining a broad understanding of how to formulate effective AI prompts.
While not solely focused on prompt engineering, this book provides a strong foundation in understanding how LLMs work, which is essential for effective prompting. It's suitable for undergraduate and graduate students, offering technical insights into language understanding and generation. It serves as valuable background reading for those wanting to understand the underlying mechanisms of the models they are prompting. Expected publication in September 2024.
Offers a practical, hands-on approach to prompt engineering specifically with ChatGPT. It's an excellent resource for high school and undergraduate students getting started, providing clear examples and exercises. It serves as a useful introductory guide and additional reading to complement foundational AI courses.
Provides a comprehensive guide to prompt engineering, covering techniques for crafting effective inputs to generative AI models. It's particularly useful for understanding how to obtain reliable and predictable results, which is crucial for both beginners and those looking to deepen their practical skills. This book is valuable as a current reference for anyone working with generative AI.
For those who want to understand the mechanics of LLMs deeply, this book guides you through building one from scratch. This is highly technical and suitable for advanced undergraduate students, graduate students, and researchers. A deep understanding of LLM architecture is beneficial for advanced prompt engineering techniques.
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Level
Introductory
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Session
November 3, 2025
- December 8, 2025
Language
zh-TW
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