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Harnessing LLMs & Text-Embeddings API with Google Vertex AI · LearnSpace
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Harnessing LLMs & Text-Embeddings API with Google Vertex AI

Курс от Packt
Средний≈ 5.3 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Updated in May 2025. This course now features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Unlock the power of Google Cloud’s Vertex AI and take your machine learning projects to the next level with this practical and hands-on course. You’ll explore how to integrate and apply Large Language Models (LLMs) and the Text-Embeddings API to real-world data, enabling smarter search, classification, and summarization applications. By the end of this course, you’ll have built working knowledge of embeddings, vector similarity, and Retrieval-Augmented Generation (RAG) systems. The course begins with environment setup and a primer on API costs, then walks you through deploying and testing text embeddings with Vertex AI. You’ll perform hands-on tasks like generating sentence embeddings and integrating them into your projects using cosine similarity and visualization tools. A deep dive into the Vertex AI Text Embedding API reveals its potential through multimodal embedding concepts, semantic search, and practical use cases. In later modules, you'll transition from theory to powerful applications—building text generators with the Bison model, extracting structured information from unstructured text, and controlling output via temperature and sampling settings. You'll also develop end-to-end solutions like clustering StackOverflow data and implementing ANN search strategies using HNSW versus cosine similarity. This course is designed for data scientists, machine learning engineers, software developers, and cloud practitioners who are interested in building intelligent applications using GenAI. Ideal learners should have a foundational understanding of Python programming, basic knowledge of machine learning, and experience with REST APIs. Familiarity with Google Cloud Platform services and tools is recommended to fully benefit from this intermediate-level course.

Навыки, которые вы освоите

EmbeddingsScalabilityDevelopment EnvironmentGoogle Cloud PlatformRetrieval-Augmented GenerationLarge Language ModelingCloud APIClassification AlgorithmsApplication Programming Interface (API)Unsupervised LearningLLM ApplicationNatural Language Processing

Программа курса

6 модулей · 36 учебных материалов

01Introduction3 материалов

Introduction

Introduction and About the Course - PrerequisitesВидеоFull Course ResourcesЧтениеCourse StructureВидео
02Development Environment Setup & Google Cloud Platform Setup5 материалов

Development Environment Setup & Google Cloud Platform Setup

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Packt - Course Instructors

Преподаватель курса

Harnessing LLMs & Text-Embeddings API with Google Vertex AI
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Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 5.3 ч

6 модулей

Язык: Английский

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

Часть программы вашего университета
Development Environment Setup and API Costs - OverviewВидео
Google Cloud SetupВидео
Hands-on: Testing the Vertex AI - Generated a Sentence EmbeddingВидео
Setting Up Google Cloud with PythonDIALOGUE
Development Environment Setup & Google Cloud Platform Setup - AssessmentЗадание
03Vertex AI Text Embedding API and Embeddings Crash Course - Deep Dive12 материалов

Vertex AI Text Embedding API and Embeddings Crash Course - Deep Dive

Introduction to Vertex AI and Capabilities - OverviewВидеоOPTIONAL: Embeddings Crash CourseВидеоHow are Embeddings Used in GenAI and LLMs and Use CasesВидеоThe Embeddings API - Text vs Multimodal Embeddings - OverviewВидеоTask Types and BenefitsВидеоMultimodal Embeddings DiagramВидеоHands-on: Embeddings Length - DimensionВидеоHands-on: Run Cosine Similarity Search on Different SentencesВидеоHands-on: Visualize EmbeddingsВидеоSummaryВидеоExploring Vertex AI EmbeddingsDIALOGUEVertex AI Text Embedding API and Embeddings Crash Course - Deep Dive - AssessmentЗадание
04Text Generation with Vertex AI Text Embedding API8 материалов

Text Generation with Vertex AI Text Embedding API

TextGenerationModel - Generating Text Using Bison ModelВидеоHands-on: Text Generation - Classification Use CaseВидеоHands-on: Extract Information into Tables and JSON FormatsВидеоHands-on: Controlling Temperature for the ModelВидеоHands-on: TopK and TopPВидеоHands-on: Transcript Summarization and ExtractionВидеоExploring Text Generation with Vertex AIDIALOGUEText Generation with Vertex AI Text Embedding API - AssessmentЗадание
05Hands-on: Application and Real-world Use Cases of Embeddings5 материалов

Hands-on: Application and Real-world Use Cases of Embeddings

Cluster Visualization of StackOverflow Question and Answers in 2DВидеоBuild Your RAG System with the StackOverflow DataВидеоScale with the Approximate Nearest Neighbor Search: HNSW vs Cosine SimilarityВидеоIntegrating BigQuery with Pandas for Real-World Data AnalysisDIALOGUEHands-on: Application and Real-world Use Cases of Embeddings - AssessmentЗадание
06Next Steps3 материалов

Next Steps

Course Summary and Next StepsВидеоFull Course Practice AssessmentЗаданиеFull Course AssessmentЗадание