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

524.9.2. Optimizing Code for Performance

21. Introduction: 1.1. Learning Objectives

534.9.3. Handling Rate Limits and API Restrictions

32. Generative AI Workflow

544.10. Extending LangChain with Advanced Techniques

42.1. Introduction to the Vertex AI Studio

554.10.1. Leveraging Data Augmentation for Improved Model Performance

52.2. Generative AI

564.10.2. Enhancing Model Responsiveness with Dynamic Prompting

Show all chapters

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

574.10.3. Adapting Model Interactions Based on User Feedback

73. The Gemini Multimodal

584.11. Deploying LangChain Projects

83.1. Gemini Business Use Cases

594.11.1. Preparing Your LangChain Project for Deployment

93.2. How to Interact with Gemini Multimodal

604.11.2. Deployment Options (Local, Cloud, and Hybrid)

103.2.1. Starting with a Prompt

614.11.3. Monitoring and Maintaining Deployed Applications

113.2.2. Anatomy of a Prompt

624.12. Advanced Use Cases and Applications

123.3. Language Capabilities: Prompt Design Modes

634.12.1. Using LangChain for NLP Tasks

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

644.12.2. AI-Driven Customer Support Solutions

143.3.2. Structured Prompt Design: Hands-on Practice 2

654.12.3. Building AI-Powered Research Tools

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

664.13. LangChain with Vertex AI Studio

163.4. Model Tuning

674.13.1. Introduction to Vertex AI and LangChain Integration

173.4.1. How to Customize & Tune a GenAI Model

684.13.2. Setting Up LangChain Projects in Vertex AI Studio

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

694.13.3. Model Deployment and Workflow Automation in Vertex AI Studio: Deploy, Monitor & Evaluate

193.5. Wrap up

704.13.4. Optimizing LangChain with Google’s Vertex AI Tools

204. LangChain for Generative AI

714.14. Real-World Projects and Case Studies

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

724.14.1. Case Study: Automating Content Creation

224.2. Core Concepts and Architecture

734.14.2. Hands-On Project: Developing a Sophisticated Smart Personal Assistant Using LangChain

234.2.1. Understanding Chains in LangChain

744.14.3. Real-World Challenges and Solutions

244.2.2. Modules: The Building Blocks of LangChain

754.15. Wrap-Up: Taking Your Skills to the Next Level

254.2.3. Key Components: Models, Prompts, and Parsers

764.16. Overview of Upcoming Parts of the Series

264.3. Models and Prompt Design

774.16.1. Hugging Face: Expanding Your Model Toolkit

274.3.1. Choosing the Right Model for Your Needs

784.16.2. Vector Databases: Efficient Data Storage and Retrieval for AI

284.3.2. Prompt Design Fundamentals

794.16.3. Llama Index: Building and Optimizing AI-Driven Knowledge Bases

294.3.3. Advanced Prompting Techniques for Custom Responses

804.16.4. More LLM Generative AI Projects and Deployment Techniques

304.4. Building Chains and Workflows

815. Practice Exercises & Projects

314.4.1. Creating Simple Chains

825.1. Multiple Choice Questions, Set 1

324.4.2. Designing Multi-Step Workflows

835.2. Correct Answers

334.4.3. Handling Errors and Fallbacks in Chains

845.3. Multiple Choice Questions, Set 2

344.5. Integrating APIs with LangChain

855.4. Correct Answers

354.5.1. API Integration Basics

865.5. Practice Project 1: Getting Started with Gemini Multimodal in Vertex AI Studio

364.5.2. Leveraging External APIs for Enhanced Functionality

875.5.1. Project Objective

374.5.3. Using Web Scraping and Other Data Sources

885.5.2. Project Overview

384.6. Memory Management in LangChain

895.5.3. Steps to Complete Project

394.6.1. Introduction to Memory in AI Models

905.5. Practice Project 2: Generating Creative Text Prompts with Gemini Multimodal and Vertex AI Studio

404.6.2. Implementing State Management in LangChain

915.5.1. Project Objective

414.6.3. Best Practices for Memory Optimization

925.5.2. Prerequisites

424.7. User Input and Parsing Responses

935.5.3. Steps to Complete Project

434.7.1. Capturing and Validating User Input

945.6. Practice Project 3: Building an Interactive FAQ Chatbot with LangChain and OpenAI API

444.7.2. Parsing Model Outputs

955.6.1. Project Objective

454.7.3. Using Parsers for Structured Data Handling

965.6.2. Project Overview

464.8. Custom Modules and Extensions

975.6.3. Prerequisites

474.8.1. Writing Custom Modules in LangChain

985.6.4. Steps to Complete the Project

484.8.2. Extending LangChain’s Capabilities with Plugins

995.6.5. Expected Outcome

494.8.3. Using OpenAI Plugins and Integrations

1005.6.6. Next Steps

504.9. Debugging and Optimization

1015.7. How to Get Additional Help & Support

514.9.1. Debugging Common LangChain Errors

102References

Series

Generative AI From Beginner to Paid ProfessionalBook 2

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