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UiPath UiPath-SAIv1題庫介紹
從 UiPath-SAIv1 考試資訊、大綱解析到 213 道練習題，NewDumps 把 UiPath Certified Professional Specialized AI Professional v1.0 所需的備考資源一次備齊。選定適合自己的產品形式，接下來只要專心刷題就好。
UiPath UiPath-SAIv1 考試概覽:
| 認證廠商: | UiPath |
|---|---|
| 考試名稱: | UiPath 認證專業人員 - 專精人工智慧專家 v1.0 |
| 考試代碼: | UiPath-SAIv1 |
| 證照有效期限: | 3 年 |
| 考試時間: | 120 分鐘 |
| 實際考試題數: | 45 - 60 |
| 支援語言: | English |
| 考試費用: | USD 300 |
| 及格分數: | 70% |
| 相關認證: | UiPath Certified Specialized AI Associate UiPath Certified Professional |
| 考試形式: | 單選題, 情境題, 複選題 |
| 推薦課程: | UiPath Academy - 專精人工智慧專家學習課程 |
| 考試報名: | Pearson VUE 報名方式 |
| 範例考題: | UiPath UiPath-SAIv1 範例考題 |
| 考試方式: | 可透過線上監考模式應考，或於 Pearson VUE 考場實地應考 |
| 必備條件: | 無強制先修條件；建議具備 UiPath 平台操作經驗與人工智慧基礎概念 |
| 官方大綱網址: | https://www.uipath.com/learning/certification/specialized-ai-professional |
UiPath UiPath-SAIv1 考試大綱主題:
| 章節 | 權重 | 目標 |
|---|---|---|
| 人工智慧驅動自動化設計 | 20% | - 設計具擴充性與穩定性的人工智慧整合自動化解決方案 - 應用人工智慧治理與安全原則 - 依商業需求選擇合適的人工智慧功能 |
| 通訊內容探勘 | 25% | - 分類體系設計與管理 - 模型訓練、標註與最佳化 - 分析預測結果並提升執行效能 |
| 人工智慧中心與機器學習整合 | 25% | - 將人工智慧模型與 Studio 流程整合 - 模型生命週期管理 - 部署與監控機器學習模型 |
| 文件理解技術 | 30% | - 文件理解相關活動
|
UiPath-SAIv1 考試必讀：考生最常問的幾個問題
UiPath-SAIv1（UiPath 認證專業人員 - 專精人工智慧專家 v1.0）是 UiPath 舉辦的認證考試，通過後可取得 UiPath 認證專業人員 - 專精人工智慧專家 v1.0 認證，認證等級屬於 專業級。本考試與 UiPath Certified Professional、UiPath Certified Specialized AI Associate 等認證相關，是規劃 UiPath 認證路徑時的重要一環。準備 UiPath Certified Professional Specialized AI Professional v1.0 時，建議搭配 NewDumps 的 213 道練習題，熟悉題型與出題方向。
依官方資訊，UiPath-SAIv1 考試的題量為 45 - 60 題，考試時間為 120 分鐘。以這樣的題量與時間來看，平均每題可分配的作答時間相當有限，遇到沒把握的題目建議先標記、跳過，把時間留給有把握的部分，最後再回頭檢查。平時可用 NewDumps 的測試引擎做限時模考，提前適應時間壓力，正式上場才不會慌。
UiPath-SAIv1 的通過分數為 70%，官方報名費為 USD 300。需要特別留意的是，一旦未通過，重考必須再次全額繳交報名費，時間與金錢成本都不低。建議在正式報名前，先用 NewDumps 的 213 道模擬試題自測，成績穩定達標後再預約考試。
報考 UiPath-SAIv1 的前置條件為：無強制先修條件；建議具備 UiPath 平台操作經驗與人工智慧基礎概念。官方的報考規定可能隨時調整，建議報名前再到官方考試說明頁面確認最新資訊。
以下是官方為 UiPath Certified Professional Specialized AI Professional v1.0 推薦的培訓資源：
完成官方培訓後，再搭配 NewDumps 的 213 道 UiPath-SAIv1 練習題反覆演練，能把課程所學轉化為實際的答題能力。
可以。NewDumps 提供 UiPath-SAIv1 免費範例試題（Free PDF Demo），下載後即可檢視實際題型與解析品質，滿意再購買完整版。購買後享有 365 天免費更新，期間內題庫內容隨官方考綱同步修訂；更新期滿後若需續更，可享 50% 折扣優惠。
NewDumps 提供「退款保證」：購買後 60 天內參加 UiPath-SAIv1 對應考試未通過，可申請全額退款。申請時需於考後 2 天內提交報名證明（准考證）影本與官方成績單（Score Report）PDF，考生姓名須與付款人姓名一致，我們會在 7 天內處理完成；購買後 3 天內應考、未實際參加考試、免費資料與過期訂單不適用。若不想退款，也可選擇免費更換兩個等值考試資料，並保留原購產品的更新服務。交付方面，付款成功後系統會在一分鐘內將產品寄至您的電子郵件信箱，可立即下載使用；若 2 小時內未收到，請聯絡客服協助。產品不限制安裝的電腦數量。
根據官方大綱，UiPath-SAIv1 考試共分為 4 個領域，主要包括 人工智慧驅動自動化設計（20%）、文件理解技術（30%）、人工智慧中心與機器學習整合（25%） 等。各領域的詳細子主題與配分，請參考上方的考試大綱區塊，那裡有最完整的說明。
最新的 UiPath Certified Professional UiPath-SAIv1 免費考試真題：
問題 #1
What are the out-of-the-box model types available in AI Center?
A. Pre-trained, fine-tunable, and reviewed.
B. Custom training, fine-tunable, and reviewed.
C. Pre-trained, custom training, and reviewed.
D. Pre-trained, custom training, and fine-tunable.
問題 #2
For an analytics use case, what are the recommended minimum model performance requirements in UiPath Communications Mining?
A. Model Ratings of "Good" or better and individual performance factors rated as "Good" or better.
B. Model Ratings of "Good" and individual performance factors rated as "Excellent".
C. Model Ratings of "Excellent" and individual performance factors rated as "Excellent".
D. Model Ratings of "Excellent" and individual performance factors rated as "Good" or better.
問題 #3
What fields are available when creating an Al Center project?
A. Name and description.
B. Name and labels.
C. Name, description, and labels.
D. Name, description, and permissions.
問題 #4
What does the Label Trends table in UiPath Communications Mining show?
A. How the top 10 senders for a given time period perform compared to the previous period and their change in rank.
B. How the top 10 labels for a given time period perform compared to the previous period and their change in rank.
C. How the top 10 entities for a given time period perform compared to the previous period and their change in rank.
D. How the top 10 labels and entities for a given time period perform compared to the previous period and their change in rank.
問題 #5
What is supervised learning?
A. Supervised learning is a machine learning paradigm in which algorithms try to solve a problem in an uncertain, potentially complex environment only by trial and error and using a system of rewards and punishments.
There are no correct answers, but feedback is given in the form of rewards and penalties.
B. Supervised learning is a machine learning paradigm with the goal of learning a function that maps input variables with output variables.
In every case there is a correct answer, so the aim is to train the model until it reaches an acceptable level of performance in predicting the outcome, at which point the learning stops.
C. Supervised learning is a machine learning paradigm in which algorithms try to solve a problem only by trial and error and using a system of rewards and punishments.
There is no need for labeled input/output pairs to be presented. Instead, the focus is on finding a balance between exploration (of uncharted territory) and exploitation (of current knowledge).
D. Supervised learning is a machine learning paradigm that refers to algorithms that learn patterns from unlabeled data.There are only input variables, but no corresponding output variables. The goal of the algorithm is to model the underlying structure of the data, but there are no correct answers and no teachers.
問題與答案：
| 問題 #1 答案： D | 問題 #2 答案： A | 問題 #3 答案： A | 問題 #4 答案： B | 問題 #5 答案： B |
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你們軟件版本的題庫模擬了真實的考試情景，讓我做好了充足的準備。很開心，因此，我的UiPath-SAIv1考試衣順利的通過了。