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Generative AI Foundations in Python · LearnSpace
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Generative AI Foundations in Python

Курс от Packt
Средний≈ 11.3 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

This course provides a clear and practical foundation in generative AI and large language models, combining theory with real-world application. It equips learners with the skills to implement and fine-tune models effectively, while emphasizing ethical and responsible AI use. Designed for professionals looking to harness the power of AI in their work, it simplifies complex concepts and offers actionable insights. Learners will explore foundational elements of transformer-based LLMs and diffusion models, gaining hands-on experience with Python projects to implement their knowledge. The course highlights how to fine-tune models and adapt them for various domains, giving learners the tools to deploy AI solutions responsibly. What sets this course apart is its combination of theoretical understanding with practical application, guiding learners through real-world challenges while maintaining an ethical focus. Ideal for developers, data scientists, and machine learning engineers, this course is designed for those with a basic understanding of machine learning and Python who wish to explore generative AI.

Навыки, которые вы освоите

Natural Language ProcessingPrompt EngineeringGenerative Adversarial Networks (GANs)Generative Model ArchitecturesResponsible AIFine-tuningTransfer LearningGenerative AIModel OptimizationDeep LearningModel TrainingPython ProgrammingLarge Language ModelingMachine LearningArtificial IntelligenceModel DeploymentData EthicsPrompt Patterns

Программа курса

8 модулей · 66 учебных материалов

01Understanding Generative AI An Introduction6 материалов

Lesson 1

Course OverviewВидеоUnderstanding Generative AI An Introduction - Overview VideoВидеоIntroductionЧтениеChoosing the Right ParadigmЧтение

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Packt - Course Instructors

Преподаватель курса

Generative AI Foundations in Python
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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

≈ 11.3 ч

8 модулей

Язык: Английский

Субтитры: Арабский, Французский, Итальянский, Бразильский португальский, Корейский, Немецкий, Индонезийский, Испанский, Японский

Часть программы вашего университета
Looking Ahead at Risks and ImplicationsЧтение
Exploring Generative AI FundamentalsЗадание
02A Closer Look at GANs10 материалов

Lesson 1

A Closer Look at GANs - Overview VideoВидеоIntroductionЧтениеAdvancement of GANsЧтениеPractice: Choosing the Right Generative AI ModelDIALOGUEA Closer Look at Diffusion ModelsЧтениеLimitations and Challenges of Diffusion ModelsЧтениеGenerative Modeling Paradigms with TransformersЧтениеLimitations and Challenges of Transformer-Based ApproachesЧтениеScoring with the CLIP ModelЧтениеExploring Generative AI Models and Ethical ImplicationsЗадание
03Tracing the Foundations of Natural Language Processing and the Impact of the Transformer13 материалов

Lesson 1

Tracing the Foundations of Natural Language Processing and the Impact of the Transformer - Overview VideoВидеоIntroductionЧтениеTransfer LearningЧтениеRise of CNNsЧтениеThe Emergence of the Transformer in Advanced Language ModelsЧтениеPractice: Analyze Context in NLP ModelsDIALOGUESelf-Attention MechanismЧтениеSoftMaxЧтениеModel TrainingЧтениеRegularizationЧтениеInferenceЧтениеMulti-head Self-AttentionЧтениеExploring the Evolution of NLP and Transformer ArchitectureЗадание
04Applying Pretrained Generative Models From Prototype to Production13 материалов

Lesson 1

Applying Pretrained Generative Models From Prototype to Production - Overview VideoВидеоIntroductionЧтениеTransitioning to ProductionЧтениеApplication CodeЧтениеModel Selection Choosing the Right Pretrained Generative ModelЧтениеPractice: Evaluate Gen AI Model Trade-offsDIALOGUEModel Size and Computational ComplexityЧтениеLoading Pretrained Models with LangChainЧтениеQuantitative Metrics EvaluationЧтениеInterpreting OutcomesЧтениеTransparency and ExplainabilityЧтениеEvaluating and Deploying Generative AI ModelsЗаданиеDiscussion: Selecting the Best Generative ModelОбсуждение
05Fine-Tuning Generative Models for Specific Tasks7 материалов

Lesson 1

Fine-Tuning Generative Models for Specific Tasks - Overview VideoВидеоIntroductionЧтениеIn-context LearningЧтениеFine-tuning Versus In-Context LearningЧтениеPractice: Compare AI Customization StrategiesDIALOGUEImplementation in PythonЧтениеAdapting Generative Models for Specific TasksЗадание
06Understanding Domain Adaptation for Large Language Models5 материалов

Lesson 1

Understanding Domain Adaptation for Large Language Models - Overview VideoВидеоIntroductionЧтениеEvaluation and Outcome Analysis ROUGE MetricЧтениеDomain Adaptation for Language ModelsЗаданиеDiscussion: Evaluating Domain AdaptationОбсуждение
07Mastering the Fundamentals of Prompt Engineering8 материалов

Lesson 1

Mastering the Fundamentals of Prompt Engineering - Overview VideoВидеоIntroductionЧтениеGuiding Principles for Model InteractionЧтениеEffect of PersonasЧтениеPractice: Design and Compare Prompting StrategiesDIALOGUEAdvanced Prompting in Action Few-Shot Learning and Prompt ChainingЧтениеPractice Project Implementing RAG with LlamaIndex Using PythonЧтениеMastering Prompt Engineering FundamentalsЗадание
08Addressing Ethical Considerations and Charting a Path Toward Trustworthy Generative AI4 материалов

Lesson 1

Addressing Ethical Considerations and Charting a Path Toward Trustworthy Generative AI - Overview VideoВидеоIntroductionЧтениеUnderstanding Jailbreaking and Harmful BehaviorsЧтениеEthical Foundations of Generative AIЗадание