К содержимому
learnspaceYOUR NEXT CHAPTER
ПРОСТРАНСТВО ОБУЧЕНИЯ
ГлавнаяКаталог курсовМоё обучениеCoursera

Знания без границ

Учитесь у лучших университетов и компаний мира.

Открыть Coursera
Интеграция
Пространство университета
Моё пространствоСтраница курса
↵
ЯЛичный кабинетСтудент
© 2026 LearnSpaceКаждый день — возможность узнать больше.Помощь
Gemini and Vertex AI: Building Intelligent Applications · LearnSpace
Назад в каталог
courseraАнализ данных

Gemini and Vertex AI: Building Intelligent Applications

Курс от Edureka
Начальный≈ 14.7 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

This course introduces the essentials of Gemini AI and Vertex AI, blending architectural insights with hands-on coding, multimodal development, and intelligent agent creation. Designed to give you both theoretical foundations and practical experience, it explores how Google’s most advanced AI systems are transforming software development, data analysis, and real-world applications. Through guided lessons and demonstrations, you’ll learn to work with Gemini’s multimodal architecture, leverage APIs for text and vision, build smarter apps with AI-driven code generation, and design intelligent agents on Vertex AI. You will also explore advanced model tuning, grounding techniques, and deployment strategies to create reliable, production-ready AI solutions. By the end of this course, you will be able to: • Understand Gemini’s multimodal architecture, APIs, and core capabilities. • Implement Gemini for text, vision, and code tasks, including function calling and document understanding. • Apply prompt engineering strategies and best practices for code generation, optimization, and testing. • Develop multimodal applications using Gemini Live API and natural language-to-database techniques. • Explore Vertex AI foundations, model garden, and Google’s foundation models (Gemini, Imagen, Veo). • Build and enhance intelligent agents with the Agent Development Kit and task-specific prompt guidance. • Tune, evaluate, and optimize Gemini and Vertex AI models using LoRA, QLoRA, and evaluation metrics. • Deploy AI systems with strategies to balance cost, latency, throughput, and performance. This course is ideal for developers, data scientists, and AI practitioners who want to build next-generation applications powered by Google Gemini AI and Vertex AI. A basic understanding of Python and machine learning will be helpful, but no prior experience with Gemini or Vertex AI is required. Join us to explore the cutting edge of multimodal AI and discover how to build smarter, more reliable applications with Gemini and Vertex AI!

Навыки, которые вы освоите

Prompt EngineeringGoogle GeminiGeminiGenerative AIModel DeploymentModel OptimizationPrompt PatternsGenerative Model ArchitecturesCloud DeploymentCloud PlatformsApplication DeploymentPython ProgrammingLarge Language ModelingSoftware Development ToolsToken OptimizationArtificial Intelligence and Machine Learning (AI/ML)AI PersonalizationGenerative AI AgentsArtificial IntelligenceGoogle Cloud Platform

Программа курса

5 модулей · 103 учебных материалов

01Gemini AI Essentials: Architecture, APIs & Core Capabilities24 материалов

Understanding Gemini's Architecture

Specialization IntroductionВидеоCourse IntroductionВидеоCourse OverviewЧтениеWhat Do You Already Know about Gemini’s Multimodal Architecture?DIALOGUE

Учитесь у экспертов

Edureka

Преподаватель курса

Gemini and Vertex AI: Building Intelligent Applications
В каталоге вашей программы

Инвестируйте в себя

Новые знания — в удобное для вас время.

Начать на Coursera

Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 14.7 ч

5 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
Gemini's Multimodal ArchitectureВидео
Gemini Pro Vs. Ultra ModelВидео
Comparison with Other LLMsВидео
The Evolution of Multimodal AI: Bridging Text, Image, and BeyondЧтение
Demonstration: Google AI Studio InterfaceВидео
Setting Up Gemini APIЧтение
Demonstration: Gemini API for Text and Vision CapabilitiesВидео
Introduce YourselfОбсуждение
Practice Quiz: Understanding Gemini's ArchitectureЗадание

Gemini Code Capabilities

Understanding AI Studio's Output CapabilitiesВидеоImplementing Function CallingВидеоDocument UnderstandingВидеоGrounding Techniques in GeminiВидеоImproving AI Reliability with Grounding and Contextual AnchoringЧтениеFine-Tuning ModelsВидеоStaying Grounded with GeminiОбсуждениеPractice Quiz: Gemini Code CapabilitiesЗадание

Module Wrap-Up and Assessment

Module 1 Checkpoint: Assessing Your Understanding of Generative AIDIALOGUEModule Summary: Gemini AI Essentials: Architecture, APIs & Core CapabilitiesЧтениеKnowledge Check: Gemini AI Essentials: Architecture, APIs & Core CapabilitiesЗадание
02Building Smarter Apps with Gemini AI: Code, Prompts & Multimodal Power28 материалов

Code Generation with Gemini

Understanding Code Generation CapabilitiesВидеоDemonstration: Python with Gemini on Google AI StudioВидеоDemonstration: C++ with Gemini on Google AI StudioВидеоBest Practices for Code GenerationВидеоAI-Powered Code Assistance: From Autocomplete to Intelligent Pair ProgrammingЧтениеWriting Code the Right WayОбсуждениеPractice Quiz: Code Generation with GeminiЗадание

Prompt Engineering with Gemini

Prompt Engineering in Google AI StudioВидеоUnit Testing for Reliable CodeВидеоDemonstartion: Unit Testing for Reliable CodeВидеоCode Optimization Made EasyВидеоDemonstartion: Code Optimization Made EasyВидеоMastering Regex for DevelopersВидео

Multimodal Development with Gemini

OpenAI CompatibilityВидеоNatural Language to SQLВидеоConverting Natural Language to Database Queries: Challenges and InnovationsЧтениеDemonstration: Document Analysis and Code ExtractionВидеоDemonstration: Gemini Live APIВидеоStream Realtime/ Multimodal Live APIВидео

Module Wrap-Up and Assessment

Module 2 Checkpoint: Assessing Your Understanding of Gemini Code Generation CapabilitiesDIALOGUEModule Summary: Building Smarter Apps with Gemini AI: Code, Prompts & Multimodal PowerЧтениеKnowledge Check: Building Smarter Apps with Gemini AI: Code, Prompts & Multimodal PowerЗадание
03Vertex AI Foundations & Intelligent Agent Development24 материалов

Discovering Vertex AI

Introduction to Vertex AIВидеоSetting Up Your Vertex AI Development EnvironmentЧтениеModel Garden Exploration and Usage on Vertex AIВидеоIntroduction to Google's Foundation Models: Gemini, Imagen, and VeoЧтениеDemonstration: Getting Started with Google Cloud: Login & Billing SetupВидеоBuilding the Right SetupОбсуждениеPractice Quiz: Discovering Vertex AIЗадание

Building Intelligent Agents on Vertex AI

Introduction to AI Agents on Vertex AIВидеоDeveloping Agents with ADKВидеоAgent Tools: Enhancing Agent CapabilitiesЧтениеPrompting for Effective AgentВидеоBuild a Simple Knowledge Chat Agent with Vertex AIЧтениеBuilding with ADK and Agent EngineОбсуждение

Harnessing the Capabilities of Generative AI Models

Text and Code Generation with Vertex AIВидеоMastering Image and Video GenerationВидеоAnalyzing Data with Generative AI ModelsЧтениеGrounding and Translation CapabilitiesВидеоUtilizing AI-Powered Prompt Writing Tools and TokenizersВидеоStaying Grounded and TranslatedОбсуждение

Module Wrap-Up and Assessment

Module 3 Checkpoint: Assessing Your Understanding of Vertex AI FoundationsDIALOGUEModule Summary: Vertex AI Foundations & Intelligent Agent DevelopmentЧтениеKnowledge Check: Vertex AI Foundations & Intelligent Agent DevelopmentЗадание
04Advanced Model Tuning, Evaluation & Deployment on Vertex AI23 материалов

Model Tuning and Optimization on Vertex AI

Introduction to Model TuningВидеоFine-Tuning Gemini Models for Optimal PerformanceВидеоTuning Embeddings, Imagen, and Translation ModelsВидеоTuning Recommendations with LoRA and QLoRAЧтениеMigrating from Google AI to Vertex AI Using the OpenAI LibraryВидеоFine-Tuning a Small Text Model in Vertex AIЧтениеBeyond Text: Imagen and TranslationОбсуждениеPractice Quiz: Model Tuning and Optimization on Vertex AIЗадание

Evaluating and Customizing Generative AI Models

Introduction to Model Evaluation on Vertex AIВидеоPerforming Evaluation with the Python SDKЧтениеDefining Evaluation Metrics and Preparing Your DatasetВидеоRunning and Interpreting Model Evaluation ResultsВидеоCustomizing Judge Models for Enhanced EvaluationВидеоMetrics That MatterОбсуждение

Deploying Generative AI Models for Production

Model Deployment Strategies and Provisioned ThroughputВидеоOptimizing Cost, Latency, and Performance in AI SystemsВидеоEfficiency Boost: Caching, Batching and ThroughputВидеоBalancing the Trade-offsОбсуждениеPractice Quiz: Deploying Generative AI Models for ProductionЗадание

Module Wrap-Up and Assessment

Module 4 Checkpoint: Assessing Your Understanding of Model Tuning and Optimization on Vertex AIDIALOGUEModule Summary: Advanced Model Tuning, Evaluation & Deployment on Vertex AIЧтениеKnowledge Check: Advanced Model Tuning, Evaluation & Deployment on Vertex AIЗадание
05Course Wrap-Up and Assessment4 материалов

Course Wrap-Up and Assessment

End Course Knowledge Check: Gemini and Vertex AI: Building Intelligent ApplicationsЗаданиеBuilding a Multimodal AI-Powered Healthcare Assistant with Gemini and Vertex AIЗаданиеCourse SummaryВидеоDescribe Your Learning JourneyОбсуждение
Demonstration: Mastering Regex for DevelopersВидео
Testing for TrustОбсуждение
Practice Quiz: Prompt Engineering with GeminiЗадание
Demonstration: Starter AppsВидео
Talking to DatabasesОбсуждение
Practice Quiz: Multimodal Development with GeminiЗадание
Practice Quiz: Building Intelligent Agents on Vertex AIЗадание
Practice Quiz: Harnessing the Capabilities of Generative AI ModelsЗадание
Practice Quiz: Evaluating and Customizing Generative AI ModelsЗадание