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Foundations of Responsible AI Strategy · LearnSpace
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Foundations of Responsible AI Strategy

Курс от Coursera
Уровень не указан≈ 9.6 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

The Foundations of Responsible AI Strategy course equips learners with the core knowledge and practical frameworks needed to use Generative AI effectively, safely, and ethically in the workplace. You will build a strong foundation in AI terminology, understand how modern language models learn from large datasets, and learn to determine when GenAI is the right tool for a task. The course also prepares you to navigate essential considerations around data privacy, security, IP protection, and responsible prompting. As you progress, you’ll explore real-world applications—from fine-tuning large language models for business value to embedding GenAI tools into software development workflows. The course concludes with guidance on recognizing bias, ensuring fairness, and applying company-specific AI-usage policies to real scenarios. By the end, you'll be able to confidently evaluate GenAI risks and opportunities, adopt responsible practices, and make informed decisions about AI use in your role. This course benefits from the expertise of LearnKartS, IBM, Coursera, and Microsoft, offering diverse perspectives that strengthen your understanding of responsible AI.

Навыки, которые вы освоите

Data EthicsEthical Standards And ConductArtificial IntelligenceResponsible AIGenerative AIPrompt EngineeringRisk MitigationFine-tuningAI SecurityLarge Language ModelingAI literacyLLM ApplicationNatural Language Processing

Программа курса

6 модулей · 73 учебных материалов

01Start Here: Get Oriented and Check Your Skills2 материалов
Start Here: How This Skill-Based Course WorksЧтениеSkill Diagnostic: Find Your Recommended Starting PointЗадание
02Fundamentals of Generative AI24 материалов

Language Models, Prompt Engineering, and Amazon Q

Learning ObjectivesВидео

Учитесь у экспертов

Professionals from the Industry

Преподаватель курса

Foundations of Responsible AI Strategy
В каталоге вашей программы

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Новые знания — в удобное для вас время.

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Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 9.6 ч

6 модулей

Язык: Английский

Субтитры: Арабский, Французский, Узбекский, Украинский, Китайский (Китай), Греческий, Итальянский, Бразильский португальский, Вьетнамский, Нидерландский, Корейский, Немецкий, Пушту, Русский, Тайский, Индонезийский, Шведский, Турецкий, Азербайджанский, Испанский, Хинди, Японский, Казахский, Венгерский, Польский

Часть программы вашего университета
Key Concepts in Language Models: Part-1Видео
Key Concepts in Language Models: Part-2Видео
Prompts and Prompt EngineeringВидео
Designing a PromptВидео
HyperparameterВидео
Choosing Top-p, Top-k and TemperatureВидео
Language Models and Prompt EngineeringЗадание
Prompt Engineering TechniquesВидео
Optimizing PromptsЧтение
Demo- Prompt Engineering TechniquesВидео
Prompt Engineering RisksВидео
Prompt TemplatesВидео
Demo-Prompt Optimization ParametersВидео
Prompt Engineering TechniquesЗадание
Generative AI Foundation ModelsВидео
Practical Applications of Generative AIВидео
Amazon QВидео
Key Components of Amazon QВидео
Generative AI Foundation Models and Amazon QЗадание
Developer Fundamentals on Amazon QВидео
Demo- Amazon Q WalkthorughВидео
Party Rock - Playground for Gen AI appsЧтение
SummaryВидео
03Introduction and Capabilities of Generative AI8 материалов

Generative AI and Its Capabilities

Introduction to Generative AIВидеоDialogue: Generative AI and Discriminative AIDIALOGUEHistory and Evolution of Generative AIЧтениеCapabilities of Generative AIВидеоExpert Viewpoints: Generative AI CapabilitiesВидеоExpert Viewpoints: Exploring the evolution of generative AIВидеоLesson Summary ЧтениеPractice Quiz: Generative AI and Its CapabilitiesЗадание
04LLM Fine-tuning And Its Applications For Business 20 материалов

Lesson 1: Basics of Large Language Models

Introduction to LLMs ВидеоEvolution of Language AI ВидеоUnderstanding Fine-Tuning ВидеоAn Overview of LLMs ЧтениеBasics of Large Language ModelsDIALOGUE

Lesson 2: LLM Fine Tuning in Business

Customizing AI for Your Business ВидеоCase Studies: Success Stories ВидеоMeasuring Impact ВидеоInsights on LLM Applications in Business ЧтениеLLM Fine Tuning in BusinessDIALOGUE

Lesson 3: Implementing LLM Fine Tuning

Strategy Development ВидеоOvercoming Challenges ВидеоTools and Resources ВидеоA Practical Guide to LLM ЧтениеImplementing LLM Fine TuningDIALOGUE

Lesson 4: The Future of LLMs in Business

Predicting Trends ВидеоStaying Ahead ВидеоEthics and Considerations ВидеоExploring the Future of AI in Business ЧтениеThe Future of LLMs in BusinessDIALOGUE
05Ethical and Safe Use of GenAI17 материалов

Identifying ethical concerns

Addressing ethical issues in generative AI: Bias, privacy, and misuseВидеоThe ethical landscape of generative AI: A data analyst's perspectiveЧтениеGarbage in, garbage out: How bias persists in GenAIВидеоEthical dilemmas in action: Case studies from the data analysis fieldЧтениеIdentifying ethical concernsЗадание

The importance of responsible AI

Beyond compliance: Why responsible AI is a competitive advantageЧтениеAI as a double-edged sword: Power, responsibility, and consequencesВидеоThe role of an AI ethicist: Balancing innovation and responsibilityВидеоBuilding an ethical AI framework: A guide for data teamsЧтениеThe importance of responsible AIЗадание

Evaluating GenAI use in scenarios

Before you deploy: Evaluating GenAI use cases for ethical risksЧтениеEthical challenges: Addressing issues in generative AIВидеоBuilt-in safeguards: Comparing GenAI tools for ethical useВидео Evaluating GenAI use in scenariosЗадание

Developing guidelines for ethical GenAI use

Why your organization needs custom ethical AI guidelinesВидеоImplementing ethical GenAI: Best practices for data teamsЧтениеThe future of ethical AI: Challenges and opportunities for data analystsЧтение
06Skill Assessment 2 материалов

Lesson

Learner Expectations for Skill AssessmentЧтениеThe Responsible AI Task Force SimulationЗадание