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The AI Optimization Playbook · LearnSpace
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The AI Optimization Playbook

Курс от Packt
Средний≈ 17.6 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

This practical guide empowers AI and tech leaders to bridge the business–technology divide by optimizing the full AI lifecycle, from strategy and prototyping to scaling and governance, using proven frameworks and enterprise case studies. This resource equips leaders with the tools to align AI initiatives with business strategy, ensuring impactful and responsible implementation. It provides actionable guidance on scaling AI solutions, integrating ethical practices, and driving measurable outcomes. Designed for professionals seeking to bridge the gap between technology and business, it offers insights from industry experts who have shaped AI strategies at scale. This resource is ideal for AI/ML leaders, CTOs, CIOs, CDAOs, and CAIOs who are responsible for driving AI innovation and operational efficiency. A foundational understanding of AI and enterprise technology is recommended to fully benefit from the content. Hands-on approach towards optimizing your AI workflows for business use-cases This course is based on The AI Optimization Playbook, by Dr. Chun Schiros, Supreet Kaur, Rajdeep Arora and Dr. Usha Jagannathan. Packt is one of the world's most prolific publishers of cutting-edge technical content. For over two decades we've made it our mission to curate and publish the knowledge of only the very best technical experts. We focus on real-world courses that help our customers get the job done, with coverage that extends across a wide range of established and cutting-edge technical topics. If you're an individual or an organisation that embraces learning by doing, Packt is the perfect fit for you.

Навыки, которые вы освоите

AI Product StrategyStakeholder CommunicationsModel EvaluationModel DeploymentGenerative AI AgentsLeadershipProject Portfolio ManagementMLOps (Machine Learning Operations)RiskingAgentic systemsGenerative AIArtificial IntelligenceData ScienceLLM ApplicationData StrategyAI WorkflowsResponsible AIAgentic WorkflowsEnterprise ArchitectureStrategic Leadership

Программа курса

16 модулей · 129 учебных материалов

01Understanding the Perils of AI Products7 материалов

Navigating AI Pitfalls: From Concept to Production

OverviewВидеоIntroductionЧтениеSiloed DevelopmentЧтениеAddressing Siloed Development in AI ProjectsDIALOGUE

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Преподаватель курса

The AI Optimization Playbook
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Обучение на Coursera

≈ 17.6 ч

16 модулей

Язык: Английский

Часть программы вашего университета
AI Is Not DeterministicЧтение
Lack of Production-ReadinessЧтение
Navigating AI Implementation ChallengesЗадание
02Building the Enterprise AI Strategy8 материалов

Crafting a Sustainable AI Roadmap for Enterprise Growth

OverviewВидеоIntroductionЧтениеGovernance and ComplianceЧтениеAligning AI Strategy with Business GoalsDIALOGUEData Strategy - The Differentiator for Your AI SystemsЧтениеAI Platform Scalable Infrastructure for Experimentation and DeploymentЧтениеOrganizational Structure and Change ManagementЧтениеBuilding a Strategic Approach to Enterprise AIЗадание
03Selecting High-Impact AI Projects10 материалов

Strategic AI: Choosing Projects for Maximum Impact

OverviewВидеоIntroductionЧтениеCase Study 2 (AI is a Gray Area)ЧтениеTech StackЧтениеSelecting a High-Impact AI InitiativeDIALOGUEOpportunity SizingЧтениеPerformance Cost Versus Benefit AnalysisЧтениеAnalyze the Risk Level of the Use CaseЧтениеCase Study - Choosing the Right BattleЧтениеEvaluating AI Project Viability and PrioritizationЗадание
04Beyond the Build: Gaining Leadership Support for AI Initiatives6 материалов

Mastering Leadership Buy-In for AI: Strategies and Stories

OverviewВидеоIntroductionЧтениеAligning AI Strategies with Business GoalsDIALOGUECrafting the AI Narrative - From Vision to Buy-inЧтениеHow AI Got the CXO Support - A Hypothetical ScenarioЧтениеLeadership and Strategy in AI ImplementationЗадание
05Building an AI Proof of Concept and Measuring Your Solution9 материалов

From Concept to Impact: Building and Evaluating AI Proof of Concept

OverviewВидеоIntroductionЧтениеCritical Tactical Decisions Post-PoC for AI AdoptionЧтениеBest Practices for Building a Successful AI PoCЧтениеValidating an AI Proof of ConceptDIALOGUEMeasuring the Performance of a PoCЧтениеSafety MetricsЧтениеFrom Pilot to Proof - A Success StoryЧтениеBuilding and Evaluating AI SolutionsЗадание
06Beyond Accuracy: A Guide to Defining Metrics for Adoption5 материалов

Balancing Metrics and Performance in Machine Learning Systems

OverviewВидеоIntroductionЧтениеDefining ML Success MetricsDIALOGUEOperational LatencyЧтениеMeasuring Impact Beyond AccuracyЗадание
07From Model to Market: Operationalizing ML Systems13 материалов

From Experiment to Enterprise: Building Scalable ML Systems

OverviewВидеоIntroductionЧтениеFrom Sandbox to Real-World Success: The Need for ProductizationЧтениеUnsupervised Learning AlgorithmsЧтениеCode Reproducibility: The Bedrock of Reliable SystemsЧтениеCode and Data Versioning in MLЧтениеImplementing Reproducible ML PipelinesDIALOGUEPipelines: Ensuring Scalability and StabilityЧтениеInfrastructure and Architecture Choices for AI/ML DeploymentsЧтениеOther MLOps Design Considerations Required to Support Model DeploymentЧтениеSystematic Feedback: Continuous Learning in ML SystemsЧтениеWhat's Next in ML SystemsЧтениеOperationalizing Machine Learning SystemsЗадание
08From Metrics to Measurement: Experimentation and Causal Inference6 материалов

Unveiling Causal Insights: From A/B Testing to Observational Analysis

OverviewВидеоIntroductionЧтениеUnderstanding Causal Inference in ML EvaluationDIALOGUEWhy Can't We Just Use Machine Learning?ЧтениеObservational Methods - Statistical ApproachesЧтениеExploring Causality and Experimentation in Data ScienceЗадание
09Generative AI in the Enterprise: Unlocking New Opportunities6 материалов

Harnessing Generative AI for Enterprise Transformation

OverviewВидеоIntroductionЧтениеProposing a Generative AI Use CaseDIALOGUEMeasuring the Business Value of Your GenAI SolutionЧтениеScenario Building a Chat with the Data Use CaseЧтениеExploring Generative AI in Business ContextsЗадание
10Understanding GenAI Operations9 материалов

Mastering the Lifecycle of Generative AI Systems

OverviewВидеоIntroductionЧтениеLife Cycle of GenAI OpsЧтениеBest Practices for the Building PhaseЧтениеUnderstanding GenAI Evaluation StrategiesDIALOGUEBest Practices for EvaluationsЧтениеCase Study - Behind the Scenes of an Enterprise LLM SolutionЧтениеCase Study - Intelligent Claims Processing PlatformЧтениеGenAI Operations FundamentalsЗадание
11AI Agents Explained9 материалов

Building Intelligent Agents for Enterprise Solutions

OverviewВидеоIntroductionЧтениеAI Agents - When to Apply Them and When to Avoid ThemЧтениеAgentic FrameworksЧтениеEvaluating AI Agent Implementation in Travel BookingDIALOGUEBest Practices for Agent ObservabilityЧтениеEnterprise Agent AI Use CasesЧтениеBest Practices for Implementing Agentic AIЧтениеAI Agents and Their Role in Modern SystemsЗадание
12Introduction to Responsible AI9 материалов

Building Ethical AI: Principles, Practices, and Real-World Impact

OverviewВидеоIntroductionЧтениеThe Pillars of RAI and Ethical Business PracticesЧтениеThe Significance of RAI in Business PracticesЧтениеUnderstanding the Pillars of Responsible AIDIALOGUEWho Is Responsible for Making "AI Responsible"?ЧтениеCollaborative Effort in RAIЧтениеEarning Trust Through RAI - Real-World Case StudiesЧтениеResponsible AI FundamentalsЗадание
13Implementing RAI Frameworks, Metrics, and Best Practices8 материалов

Building Ethical AI Systems: From Risk to Compliance

OverviewВидеоIntroductionЧтениеEthical Risk Assessment Checklist: Quantifying RiskЧтениеEvaluating Ethical Risks in AI System DeploymentDIALOGUERegulatory Compliance in a Global ContextЧтениеMetrics for RAIЧтениеKey Takeaways: Cultural IntegrationЧтениеResponsible AI Implementation and GovernanceЗадание
14Building Trustworthy LLMs and Generative AI8 материалов

Ethical Foundations and Safety Practices in AI Development

OverviewВидеоIntroductionЧтениеAddressing Biases and Maintaining Fairness in AI Application OutputsЧтениеUnderstanding Bias Mitigation in LLMsDIALOGUEStrategies to Mitigate Bias in LLMsЧтениеPrivacy and Data Security in LLMsЧтениеGuidelines for Developing Responsible AI ApplicationsЧтениеEthical and Technical Challenges in Generative AIЗадание
15Regulatory and Legal Frameworks for Responsible AI8 материалов

Mastering AI Compliance and Ethical Governance

OverviewВидеоIntroductionЧтениеNavigating Cross-Border AI ComplianceЧтениеNavigating Cross-Border AI ComplianceDIALOGUEImplementing the KYAI System Registration TemplateЧтениеLiability, Accountability, and Risk Management in the Age of GenAIЧтениеAddressing Regulatory Challenges Case StudiesЧтениеRegulatory and Legal Frameworks for Responsible AIЗадание
16The Future of AI Optimization: Trends, Vision, and Responsible Implementation8 материалов

Navigating the Ethical and Technical Frontiers of AI in 2030

OverviewВидеоIntroductionЧтениеData Storage and AccessibilityЧтениеExploring AI Optimization Trends and Ethical ImplementationDIALOGUEThe Societal Impact of AI - People and SustainabilityЧтениеInnovAIte LLC - AI-Driven Enterprise EmbodimentЧтениеResponsible AI and Future Technological TrendsЗаданиеThe The AI Optimization Playbook Final AssessmentЗадание