EC-COUNCIL CAIPM 試験概要:
| 認定ベンダー: | EC-Council |
|---|---|
| 試験名: | 認定AIプログラムマネージャー |
| 試験番号: | CAIPM |
| 対応言語: | 英語 |
| 認定の有効期間: | 3年 |
| 試験形式: | 多肢選択式 |
| 試験時間: | 120 分 |
| 合格点: | 70% |
| 出題数: | 100 |
| 受験料: | $400 |
| 関連資格: | CND CISO CEH |
| サンプル問題: | EC-COUNCIL CAIPM サンプル問題 |
| 受験方法: | オンライン監督付き試験 |
| 前提条件: | プロジェクト管理の基本原則に関する基礎知識。プロジェクト管理の実務経験があると望ましいですが、必須ではありません |
| 公式シラバスのURL: | https://www.eccouncil.org/certified-ai-program-manager/ |
EC-COUNCIL CAIPM 試験シラバストピック:
| セクション | 比重 | 目標 |
|---|---|---|
| AIチームのリーダーシップとマネジメント | 20% | - AIチームの構築 - 人材管理と育成 - AIプロジェクトにおける対立解決 - 部門横断的な連携 |
| AIプログラムの評価と最適化 | 10% | - 継続的改善 - KPIと成功指標 - パフォーマンス測定 |
| リスク管理とコンプライアンス | 10% | - AIリスクの特定と評価 - AIに関するセキュリティ上の考慮事項 - 規制遵守(GDPR, CCPA) |
| AIプロジェクトライフサイクル管理 | 25% | - 監視と保守 - データの準備と管理 - モデル開発とテスト - AI開発手法(CRISP-DM, Agile) - デプロイメントと運用(MLOps) |
| AIの基礎と戦略 | 15% | - AIビジネス戦略との整合性 - AIの概念と用語 - AI倫理とガバナンスの枠組み |
| AIプログラム計画 | 20% | - リソース計画と予算策定 - AIプロジェクトの要件収集 - ステークホルダーの特定と分析 - AIプロジェクトの範囲設定と実現可能性分析 |
EC-COUNCIL Certified AI Program Manager (CAIPM) 認定 CAIPM 試験問題:
問題 #1
An enterprise is considering deploying an AI solution that will be used across multiple business domains to support various knowledge and language-based tasks. Instead of developing separate AI models for each domain, the solution will be based on a common core capability, with domain-specific adjustments made where necessary. As the AI Portfolio Owner, your role is to ensure that this approach aligns with the company' s broader AI strategy and long-term investment priorities. You must assess the correct classification for this AI model to support future scalability and integration across the organization's diverse functions. Which AI model classification best fits this strategy?
A. Large Language Models
B. Foundation Models
C. Machine Learning
D. Generative AI
問題 #2
An enterprise has approved multiple pilots and early-stage AI use cases across different functions. Adoption teams are still evaluating which workflows deliver consistent productivity and quality improvements. At this stage, leadership wants to avoid creating administrative overhead that could slow experimentation or discourage participation. Financial monitoring is being handled centrally while usage patterns and business impact are still being analyzed, and individual business units are not yet being asked to account for their own consumption. Which cost accountability approach is being applied in this phase?
A. Chargeback model
B. Showback model
C. Team-based budgeting
D. Centralized model
問題 #3
Mr. Garp, Head of Revenue Analytics, is reviewing a decision-support system used by pricing teams in the organization. The system evaluates various pricing scenarios and provides likelihood estimates to guide decision-making. Over time, improvements in the system's performance are driven by refining the way business data is represented during model updates. The system remains stable unless explicitly updated through structured, planned revisions.
As part of strategic planning, Mr. Garp must determine which type of AI technology this system uses, to decide on future investments and align them with business goals.
A. Deep Learning
B. Agent Technologies
C. Machine Learning
D. Generative AI
問題 #4
A shipping organization has formally transitioned its route optimization AI from limited operational use into day-to-day enterprise operations. Manual routing procedures have been formally decommissioned, and dispatch decisions are now executed directly through the AI system. While the organization no longer treats the system as experimental or supplementary, leadership has retained active performance dashboards to observe reliability, drift, and operational health over time. At this stage of deployment - where the AI is neither running alongside legacy processes nor operating unchecked - how is the workflow best described?
A. AI handles routine cases while humans manage exceptions
B. AI operates with complete autonomy and no monitoring
C. AI is embedded in the standard workflow with monitoring
D. AI runs parallel to existing process for validation
問題 #5
At a global engineering firm, the AI Enablement Manager, Lucas Meyer, reviewed adoption data several weeks after employees received access to a newly deployed AI tool. Completion rates for the initial learning sessions were high, and users demonstrated competence with the tool's core features. However, usage analytics showed that the tool was infrequently applied during day-to-day work, with many teams continuing to rely on established processes despite having access to the AI capability. Which type of training was most likely insufficient or missing in this rollout?
A. Foundational
B. Awareness
C. Role-specific
D. Advanced
解説:
| 問題 #1 正解: B | 問題 #2 正解: D | 問題 #3 正解: C | 問題 #4 正解: C | 問題 #5 正解: C |














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