「training」の検索結果

Analyze learning management and training pathway systems for prerequisite mapping, competency-based progression, adaptive sequencing, and credential stacking.

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Audit manufacturing predictive maintenance systems for OPC-UA/MQTT sensor data pipelines, time-series storage retention, ML model lifecycle (training-serving skew, drift detection, retraining triggers), MTBF/MTTF/MTTR reliability calculations, Weibull survival analysis.

日本語の概要は準備中です。原文の説明を表示しています。

Use this skill when building, reviewing, or refreshing a RACI (Responsible / Accountable / Consulted / Informed) matrix for a Salesforce project so that every Salesforce-specific decision — data model change, automation tier choice, security model, integration boundary, deployment, license/edition — has exactly one accountable owner and a documented escalation path that downstream agents can route to. Trigger keywords: RACI matrix salesforce project, stakeholder authority salesforce, escalation path salesforce decisions, who approves data model change, salesforce decision rights, REFUSAL_NEEDS_HUMAN_REVIEW routing. NOT for the change advisory board operating model itself (use admin/change-management-and-deployment). NOT for end-user training rollout plans (use admin/change-management-and-training). NOT for the technical mechanics of permission set assignment authority (use admin/permission-set-architecture). NOT for pure stakeholder requirements elicitation (use admin/requirements-gathering-for-sf). More trigger keywords: who approves a sandbox refresh, who signs off a data load, release update activation owner, delegated admin authority vs RACI, multi-org decision rights, escalation time-box.

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Use when preparing for a Salesforce seasonal release — triaging release notes, reviewing Release Updates, opting into Sandbox Preview, and communicating change impact to stakeholders. Triggers: 'upcoming Salesforce release', 'release notes triage', 'Release Updates', 'sandbox preview opt-in', 'release readiness checklist', 'production upgrade date', 'feature impact', 'critical update', 'roll out the Spring release safely', 'is our org ready for the Spring release', 'release update settings metadata', 'FlowSettings release update field', 'release run sheet', 'preview sandbox refresh freeze', 'settings deploy flipped a release update'. Also covers: which Release Updates are deployable as Settings metadata, the release run sheet artefact, and the preview opt-in refresh-date rule. NOT for planning your own release train — use devops/release-management. NOT for user training and go-live comms — use admin/change-management-and-training.

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Configuring Salesforce In-App Guidance: floating, docked, and targeted prompts, multi-step walkthroughs, audience targeting, scheduling, and adoption analytics. Use when designing user onboarding or feature adoption programs in Lightning Experience. Covers the Prompt metadata type, promptVersions, displayType, uiFormulaRule, stepNumber, isPublished, PromptAction and PromptError. NOT for guidance on a record's Path — use admin/path-and-guidance. NOT for adoption and training — use admin/change-management-and-training.

日本語の概要は準備中です。原文の説明を表示しています。

Use this skill when driving adoption of CRM Analytics (Einstein Analytics) across an org — the Analytics Adoption App for measuring who uses which dashboards, embedding analytics into Lightning pages, pinning dashboards to the Analytics home page, self-service personas, and analytics success metrics. Triggers: analytics adoption, dashboard usage tracking, embedded analytics strategy, self-service analytics enablement, CRM Analytics rollout. NOT for building the dashboards — use admin/analytics-dashboard-design. NOT for the app, datasets and lenses — use admin/crm-analytics-app-creation. NOT for non-analytics rollout training — use admin/change-management-and-training.

日本語の概要は準備中です。原文の説明を表示しています。

Fujitsu iRMC S4 (TX1320 M3 等) の電源・BIOS・RAID 操作 + BIOS 設定リファレンス。Redfish (HTTPS + SECLEVEL=0) 経由の電源/ブート操作 + iRMC Web UI/KVM 経由の手動 BIOS/RAID 操作手順 + 全 BIOS 設定項目の網羅リファレンス (bios/)。training-tx1320 対応。

PXE/netboot 経由で Debian + HW RAID10 を自動インストール (OpenWrt ローカル TFTP + embed ipxe.efi + IPv4 リテラル mirror)。BMC USB redirector が累積劣化した機種 (TX1320 M3 等) や、 cross-site 拠点の install に使う。phase 19 で training-tx1320 で完遂、 物理操作なしで自力 SSH まで到達。

AI compliance analysis for EU AI Act, ISO 42001, NIST AI RMF, GDPR, OECD, financial services regulations (SEC, FCA, FINRA, DORA, MiFID II), and other frameworks. Use when asked to generate a compliance checklist for an AI tool or use case, determine if a risk assessment is required, score an AI tool's risk level, identify where an AI tool or use case could run afoul of regulatory requirements, perform a gap analysis, recommend remediation steps, assess a vendor, draft an acceptable use policy, map training requirements, or review jurisdiction-specific AI rules. Triggers on phrases like "compliance checklist", "risk assessment", "risk score", "does this comply", "EU AI Act", "ISO 42001", "NIST AI RMF", "AI governance", "gap analysis", "vendor assessment", "acceptable use policy", "MNPI", "AI training requirements", or any request to evaluate an AI tool or use case for regulatory compliance or risk.

日本語の概要は準備中です。原文の説明を表示しています。

Create interactive AI role-play training activities as self-contained HTML. Use when the user asks to generate a role-play, persona practice, sales simulation, customer conversation drill, compliance scenario, or any learner-vs-AI-character training exercise.

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Heart rate variability biometrics and emotional awareness training. Expert in HRV analysis, interoception training, biofeedback, and emotional intelligence. Activate on 'HRV', 'heart rate variability', 'alexithymia', 'biofeedback', 'vagal tone', 'interoception', 'RMSSD', 'autonomic nervous system'. NOT for general fitness tracking without HRV focus, simple heart rate monitoring, or diagnosing medical conditions (only licensed professionals diagnose).

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Prepare high-quality datasets for LLM fine-tuning with filtering, deduplication, augmentation, and RLHF data formatting. Activate on: fine-tuning data, training data curation, RLHF dataset, data quality filtering, SFT dataset. NOT for: model training infrastructure (ai-engineer), prompt engineering without fine-tuning (prompt-engineer).

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Introduce people to AI, agentic AI, and AI skills with appropriate pedagogy for any audience. Covers LLM analogies, progressive complexity paths, aha-moment demos, audience-tailored explanations, workshop design, and overcoming emotional barriers to AI adoption. Activate on 'explain AI', 'introduce AI', 'AI workshop', 'AI demo', 'teach AI', 'AI literacy', 'onboard to AI', 'AI evangelism', 'explain agentic', 'explain skills to', 'AI training session', 'AI onboarding'. NOT for teaching ML engineering (use ai-engineer), not for building AI features (use ai-engineer), not for prompt engineering (use prompt-engineer), not for building training data pipelines.

日本語の概要は準備中です。原文の説明を表示しています。

Expert in 3D computer vision labeling tools, workflows, and AI-assisted annotation for LiDAR, point clouds, and sensor fusion. Covers SAM4D/Point-SAM, human-in-the-loop architectures, and vertical-specific training strategies. Activate on '3D labeling', 'point cloud annotation', 'LiDAR labeling', 'SAM 3D', 'SAM4D', 'sensor fusion annotation', '3D bounding box', 'semantic segmentation point cloud'. NOT for 2D image labeling (use clip-aware-embeddings), general ML training (use ml-engineer), video annotation without 3D (use computer-vision-pipeline), or VLM prompt engineering (use prompt-engineer).

日本語の概要は準備中です。原文の説明を表示しています。

Expert in script-to-video production pipelines for Apple Silicon Macs. Specializes in hybrid local/cloud workflows, LoRA training for character consistency, motion graphics generation, and artist commissioning. Activate on 'AI video production', 'script to video', 'video generation pipeline', 'character consistency', 'LoRA training', 'cloud GPU', 'motion graphics', 'Wan I2V', 'InVideo alternative'. NOT for real-time video editing, video compositing (use DaVinci/Premiere), audio production, or 3D modeling (use Blender/Maya).

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Recommends equipping every patient with primary adrenal insufficiency (PAI) with a glucocorticoid injection kit for emergency self‑administration and providing training on its use. Trigger when preparing a PAI patient for stress dosing, adrenal crisis prevention, or when prescribing glucocorticoid replacement and needing to ensure emergency preparedness.

日本語の概要は準備中です。原文の説明を表示しています。

Orientação especializada para ajuste fino com GRPO/RL usando TRL para treinamento de modelos com raciocínio e tarefas específicas

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Fornece orientação para pós-treinamento de LLM com RL usando slime, um framework Megatron+SGLang. Use ao treinar modelos GLM, implementar fluxos de trabalho personalizados de geração de dados, ou precisar de integração estreita com Megatron-LM para escalabilidade em RL.

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Framework PyTorch de alto nível com classe Trainer, treinamento distribuído automático (DDP/FSDP/DeepSpeed), sistema de callbacks e boilerplate mínimo. Escala de laptop para supercomputador com o mesmo código. Use quando quiser loops de treinamento limpos com boas práticas integradas.

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Treinar modelos de Mixture of Experts (MoE) usando DeepSpeed ou HuggingFace. Use ao treinar modelos em larga escala com computação limitada (redução de 5× em custos vs modelos densos), implementar arquiteturas esparsas como Mixtral 8x7B ou DeepSeek-V3, ou escalar capacidade de modelo sem aumento proporcional de computação. Cobre arquiteturas MoE, mecanismos de roteamento, balanceamento de carga, paralelismo de especialistas e otimização de inferência.

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Builds and improves task-specific decision artifacts from application requirements and labeled records. Use for data assembly, primitive and base-model selection, fitting, export/reload, inference policy, or bounded data/model/program improvement. Includes rules and no-training outcomes; does not require a rung ladder or training a general Jev.

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Plan a cyclist's training week as a standalone coaching package with integrated workout building. Use whenever the athlete asks to plan a week or the upcoming week ("plan my week", "build my training week", "week schema", "plan a week workout schedule", or any localized equivalent), or states a goal for the week. The flow reads a per-athlete config, pulls recent Strava data, classifies rider type from the athlete's own power curve, then produces one weekly markdown plan and structured bike workouts (ZWO for Zwift) per structured bike session without relying on another skill. Works for any cyclist, not one fixed person.

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Relajación Muscular Progresiva (PMR) según Jacobson y Entrenamiento Autógeno según Schultz. Formas cortas y versiones completas.

日本語の概要は準備中です。原文の説明を表示しています。

ヤコブソンによる筋弛緩法（PMR）およびシュルツによる自律訓練法。短縮版と完全版。