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Transformers in Action: A Practical Approach to NLP and AI · LearnSpace
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Transformers in Action: A Practical Approach to NLP and AI

Курс от Board Infinity
Средний≈ 18.9 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

"This intermediate-level course takes you beyond AI theory into the practical world of Natural Language Processing (NLP) powered by Transformer architectures. You’ll trace the evolution of language models—from traditional statistical methods and recurrent networks to attention-based systems like BERT, GPT, and T5—through engaging demos and real-world case studies. Across four modules, you’ll gain a deep understanding of how Transformers work, why they outperform previous models, and how to use them for NLP tasks such as classification, summarization, translation, and sentiment analysis. Through guided coding labs and hands-on exercises with Hugging Face tools, you’ll learn how to tokenize data, fine-tune pretrained models, evaluate results, and deploy applications efficiently. Whether you’re a developer, data scientist, or AI enthusiast, this course bridges the gap between concept and implementation—helping you turn complex architectures into tangible, working AI systems. By the end of this course, you will be able to: - Understand and explain how Transformer architectures process and generate human language. - Fine-tune and deploy pretrained models using Hugging Face tools and APIs. - Apply NLP techniques to real-world use cases such as summarization and classification. - Evaluate and interpret model performance using key metrics and visualizations. - Design and deliver an end-to-end NLP project, from training to deployment." Disclaimer: This is an independent educational resource created by Board Infinity for informational and educational purposes only. This course is not affiliated with, endorsed by, sponsored by, or officially associated with any company, organization, or certification body unless explicitly stated. The content provided is based on industry knowledge and best practices but does not constitute official training material for any specific employer or certification program. All company names, trademarks, service marks, and logos referenced are the property of their respective owners and are used solely for educational identification and comparison purposes.

Навыки, которые вы освоите

Hugging FaceFine-tuningModel OptimizationEmbeddingsModel DeploymentRecurrent Neural Networks (RNNs)Model EvaluationData PreprocessingGenerative Model ArchitecturesModel TrainingLLM ApplicationTransfer Learning

Программа курса

4 модулей · 97 учебных материалов

01Foundations of Transformers29 материалов

Introduction to the Course

Introduction to the CourseВидеоGlossaryЧтение

How Machines Read Text

What Is NLP?ВидеоFrom Text to TokensВидео

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Board Infinity

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Transformers in Action: A Practical Approach to NLP and AI
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Обучение на Coursera

≈ 18.9 ч

4 модулей

Язык: Английский

Субтитры: Венгерский

Часть программы вашего университета
Word EmbeddingsВидео
How Machines Understand LanguageЧтение
Breaking Down Language: The First Step in NLPDIALOGUE
Practice Quiz : How Machines Read TextЗадание

Sequence Models Before Transformers

Sequential Thinking in RNNsВидеоLSTMs and GRUsВидеоThe Sequential BottleneckВидеоSequence Models Before TransformersЧтениеPractice Quiz: Sequence Models Before TransformersЗадание

The Attention Idea

Why Do We Need Attention?ВидеоQueries, Keys, and ValuesВидеоSelf-Attention in ActionВидеоThe Rise of Attention MechanismsЧтениеPractice Quiz : The Attention IdeaЗадание

Enter the Transformer

Anatomy of a TransformerВидеоEncoder vs. DecoderВидеоWhy Transformers WonВидеоInside the Transformer ArchitectureЧтениеLab : Fundamentals of Tokenization & EmbeddingЛабораторнаяSolution Breakdown & ExplanationЧтениеFoundations of TransformersPLUGINFoundations of Understanding: How NLP Models Learn LanguageDIALOGUEPractice Quiz : Enter the TransformerЗаданиеGraded Quiz : Foundations of TransformersЗаданиеQuick Course Check-InPLUGIN
02Transformer Architectures and Pretraining24 материалов

Types of Transformer Models

Architecture FamiliesВидеоPretraining TasksВидеоDesign Trade-offsВидеоTypes of Transformer Models: Architectures and Pretraining ObjectivesЧтениеPractice Quiz : Types of Transformer ModelsЗадание

Working with Pretrained Models

Inside a Hugging Face ModelВидеоContext and Hidden StatesВидеоHands-On InferenceВидеоGetting Under the Hood: Hugging Face Model Components and InferenceЧтениеPractice Quiz : Working with Pretrained ModelsЗадание

Fine-Tuning Basics

What Is Fine-Tuning?ВидеоLoss Functions and RegularizationВидеоFine-Tuning DemoВидеоFine-Tuning Transformers: Workflow, Loss Functions, and Best PracticesЧтениеPractice Quiz : Fine-Tuning BasicsЗадание

Compare and Reflect

Architecture RecapВидеоPretraining Objective ReviewВидеоChoosing the Right ModelВидеоLab - Transformer Architectures and PretrainingЛабораторнаяSolution Breakdown & ExplanationЧтениеFine-Tuning Transformers: Workflow, Loss Functions, and Best PracticesЧтение
03Hugging Face Transformers in Action22 материалов

Pipelines and Datasets

Exploring PipelinesВидеоUnderstanding DatasetsВидеоPreparing Data for TrainingВидеоHugging Face Pipelines and Datasets: Fast-Tracking NLP DevelopmentЧтениеPractice Quiz : Pipelines and DatasetsЗадание

Model Training Workflow

Trainer API OverviewВидеоEvaluating ModelsВидеоMonitoring TrainingВидеоTraining and Evaluating Transformers: Trainer API, Metrics, and TrackingЧтениеPractice Quiz : Model Training WorkflowЗадание

Improving and Debugging Models

Common Training IssuesВидеоHyperparameter TuningВидеоDebugging in PracticeВидеоImproving and Debugging Transformers: Training Challenges and Hyperparameter TuningЧтениеPractice Quiz : Debugging in PracticeЗадание

Share and Deploy

Versioning and Model CardsВидеоPublishing to Hugging Face HubВидеоInference APIsВидеоSharing and Deploying Transformers: Model Cards, Hugging Face Hub, and Inference APIsЧтениеFrom Lab to Launch: Building NLP Systems with Hugging FaceDIALOGUEPractice Quiz : Share and DeployЗадание
04Applications and Extensions22 материалов

Working with Embeddings

Sentence EmbeddingsВидеоMeasuring SimilarityВидеоVisualizing EmbeddingsВидеоSemantic Similarity and Embeddings: Using SBERT, Cosine Search, and VisualizationsЧтениеPractice Quiz : Visualizing EmbeddingsЗадание

Real NLP Applications

Summarization and TranslationВидеоQuestion Answering and ClassificationВидеоZero-Shot and Multi-Task LearningВидеоReal-World NLP with Transformers: Summarization, QA, Translation, and Zero-Shot ClassificationЧтениеPractice Quiz : Real NLP ApplicationsЗадание

Optimization and Deployment

Model CompressionВидеоExporting ModelsВидеоDeployment StrategiesВидеоOptimizing and Deploying Transformers: Compression, Export, and Inference StrategiesЧтениеPractice Quiz : Optimization and DeploymentЗадание

Capstone Projects

Project OverviewВидеоBuilding Your NLP ApplicationВидеоPresenting and ReflectingВидеоPractice Quiz : Capstone ProjectsЗаданиеTransformers in the Wild: Real-World NLP and OptimizationDIALOGUEGraded Quiz : Applications and ExtensionsЗадание
Inside the Mind of Transformers: Pretraining, Purpose, and PerformanceDIALOGUE
Practice Quiz - Compare and ReflectЗадание
Graded Quiz : Transformer Architectures and PretrainingЗадание
Graded Quiz : Hugging Face Transformers in ActionЗадание
Closure VideoВидео