Generative AI Architectures with LLM, Prompt, RAG, Vector DB

Design and Integrate AI-Powered S/LLMs into Enterprise Apps using Prompt Engineering, RAG, Fine-Tuning and Vector DBs
4.47 (277 reviews)
Udemy
platform
English
language
Software Engineering
category
instructor
Generative AI Architectures with LLM, Prompt, RAG, Vector DB
2,196
students
6.5 hours
content
Jan 2025
last update
$69.99
regular price

What you will learn

Generative AI Model Architectures (Types of Generative AI Models)

Transformer Architecture: Attention is All you Need

Large Language Models (LLMs) Architectures

Text Generation, Summarization, Q&A, Classification, Sentiment Analysis, Embedding Semantic Search

Generate Text with ChatGPT: Understand Capabilities and Limitations of LLMs (Hands-on)

Function Calling and Structured Outputs in Large Language Models (LLMs)

LLM Providers: OpenAI, Meta AI, Anthropic, Hugging Face, Microsoft, Google and Mistral AI

LLM Models: OpenAI ChatGPT, Meta Llama, Anthropic Claude, Google Gemini, Mistral Mixral, xAI Grok

SLM Models: OpenAI ChatGPT 4o mini, Meta Llama 3.2 mini, Google Gemma, Microsoft Phi 3.5

How to Choose LLM Models: Quality, Speed, Price, Latency and Context Window

Interacting Different LLMs with Chat UI: ChatGPT, LLama, Mixtral, Phi3

Installing and Running Llama and Gemma Models Using Ollama

Modernizing Enterprise Apps with AI-Powered LLM Capabilities

Designing the 'EShop Support App' with AI-Powered LLM Capabilities

Advanced Prompting Techniques: Zero-shot, One-shot, Few-shot, COT

Design Advanced Prompts for Ticket Detail Page in EShop Support App w/ Q&A Chat and RAG

The RAG Architecture: Ingestion with Embeddings and Vector Search

E2E Workflow of a Retrieval-Augmented Generation (RAG) - The RAG Workflow

End-to-End RAG Example for EShop Customer Support using OpenAI Playground

Fine-Tuning Methods: Full, Parameter-Efficient Fine-Tuning (PEFT), LoRA, Transfer

End-to-End Fine-Tuning a LLM for EShop Customer Support using OpenAI Playground

Choosing the Right Optimization – Prompt Engineering, RAG, and Fine-Tuning

Vector Database and Semantic Search with RAG

Explore Vector Embedding Models: OpenAI - text-embedding-3-small, Ollama - all-minilm

Explore Vector Databases: Pinecone, Chroma, Weaviate, Qdrant, Milvus, PgVector, Redis

Using LLMs and VectorDBs as Cloud-Native Backing Services in Microservices Architecture

Design EShop Support with LLMs, Vector Databases and Semantic Search

Design EShop Support with Azure Cloud AI Services: Azure OpenAI, Azure AI Search

Screenshots

Generative AI Architectures with LLM, Prompt, RAG, Vector DB - Screenshot_01Generative AI Architectures with LLM, Prompt, RAG, Vector DB - Screenshot_02Generative AI Architectures with LLM, Prompt, RAG, Vector DB - Screenshot_03Generative AI Architectures with LLM, Prompt, RAG, Vector DB - Screenshot_04
6277173
udemy ID
11/8/2024
course created date
12/17/2024
course indexed date
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