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
4.48 (361 reviews)
2 696
students
6.5 hours
content
Apr 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
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udemy ID
08/11/2024
course created date
17/12/2024
course indexed date
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