Generative AI From Beginner to Paid Professional, Part 2

Master Prompt Design, Gemini Multimodal in Vertex AI Studio, LangChain, Launching & Deploying Generative AI ProjectsBy Bolakale Aremu

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Length5h 30m

About this audiobook

Unlock the Future of Generative AI and Skyrocket Your Career. This book is your comprehensive roadmap from grasping the fundamentals of AI to mastering the tools and techniques that will set you apart in today’s AI-driven world. Perfect for anyone serious about a career in AI, this book bridges the gap between knowledge and action, giving you the tools to earn, build, and innovate with generative AI technologies. Whether you’re building your first AI project or refining your professional skills, this is the guide you’ve been waiting for. Packed with hands-on projects and practical exercises, this book empowers you to build and launch your very own generative AI solutions. By the end, you’ll not only be equipped with in-demand AI skills but also be prepared to launch your AI projects in the real world. Welcome to Generative AI from Beginner to Paid Professional, Part 2: Master Prompt Design, Gemini Multimodal in Vertex AI Studio, LangChain, Launching & Deploying Generative AI Projects. In Part 2 of this transformative guide, you'll delve deep into powerful AI frameworks and cutting-edge technologies, including Gemini Multimodal, Vertex AI Studio, and LangChain, gaining the expertise needed to design custom AI solutions and deploy scalable AI projects. Whether you’re an aspiring professional or a seasoned developer, this book is your step-by-step companion to navigating the evolving landscape of generative AI. What You’ll Learn: Master Prompt Design: Craft perfect prompts that make your AI work for you, no matter the use case. Gemini Multimodal & Vertex AI Studio: Learn to integrate multimodal models into your AI pipeline, revolutionizing how you build intelligent systems that understand and generate both text and images. LangChain for Real-World AI Projects: Leverage LangChain to create robust, API-powered workflows that bring your AI projects to life. Launching & Deploying AI Projects: From conceptualization to deployment, turn your AI ideas into real-world applications with proven strategies.

Artificial Intelligence Futuristic

Audiobook details

GenreTechnology, Science and Nature

Length5 hrs 30 mins

Narrated byListen with 1,000+ voices

FormateBook with Audio

Publish dateNov 10, 2024

LanguageEnglish

10. About The Series

21. Introduction: 1.1. Learning Objectives

32. Generative AI Workflow

42.1. Introduction to the Vertex AI Studio

52.2. Generative AI

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62.3. Foundation Models: 2.3.1. How Foundation Models Power Your Applications

73. The Gemini Multimodal

83.1. Gemini Business Use Cases

93.2. How to Interact with Gemini Multimodal

103.2.1. Starting with a Prompt

113.2.2. Anatomy of a Prompt

123.3. Language Capabilities: Prompt Design Modes

133.3.1. Free-form Prompt Design: Hands-on Practice 1

143.3.2. Structured Prompt Design: Hands-on Practice 2

153.3.3. Practical Examples for Understanding Model Parameters (Temperature, Top K & Top P)

163.4. Model Tuning

173.4.1. How to Customize & Tune a GenAI Model

183.4.2. How to Start a Tuning Job in the Vertex AI Studio

193.5. Wrap up

204. LangChain for Generative AI

214.1. Introduction to LangChain and Generative AI: 4.1.2. Setting Up Your Environment for LangChain Development

224.2. Core Concepts and Architecture

234.2.1. Understanding Chains in LangChain

244.2.2. Modules: The Building Blocks of LangChain

254.2.3. Key Components: Models, Prompts, and Parsers

264.3. Models and Prompt Design

274.3.1. Choosing the Right Model for Your Needs

284.3.2. Prompt Design Fundamentals

294.3.3. Advanced Prompting Techniques for Custom Responses

304.4. Building Chains and Workflows

314.4.1. Creating Simple Chains

324.4.2. Designing Multi-Step Workflows

334.4.3. Handling Errors and Fallbacks in Chains

344.5. Integrating APIs with LangChain

354.5.1. API Integration Basics

364.5.2. Leveraging External APIs for Enhanced Functionality

374.5.3. Using Web Scraping and Other Data Sources

384.6. Memory Management in LangChain

394.6.1. Introduction to Memory in AI Models

404.6.2. Implementing State Management in LangChain

414.6.3. Best Practices for Memory Optimization

424.7. User Input and Parsing Responses

434.7.1. Capturing and Validating User Input

444.7.2. Parsing Model Outputs

454.7.3. Using Parsers for Structured Data Handling

464.8. Custom Modules and Extensions

474.8.1. Writing Custom Modules in LangChain

484.8.2. Extending LangChain’s Capabilities with Plugins

494.8.3. Using OpenAI Plugins and Integrations

504.9. Debugging and Optimization

Series

Generative AI From Beginner to Paid ProfessionalBook 2

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