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

🌟 Course Title: Generative AI Architectures with LLM, Prompt, RAG, Vector DB 🚀

Course Headline:

Design and Integrate AI-Powered S/LLMs into Enterprise Apps using Prompt Engineering, RAG, Fine-Tuning, and Vector DBs

📚 Course Description:

Join our comprehensive online course to master the art of designing Generative AI Architectures with a focus on integrating AI-Powered S/Large Language Models (S/LLMs) into your EShop Support Enterprise Applications. Throughout this journey, you'll become proficient in Prompt Engineering, harness the power of Retrieval Augmented Generation (RAG), and learn advanced fine-tuning techniques.

Here's what you'll explore in this course: 🔍

Core Components for Generative AI Architectures 🤖

1. Small and Large Language Models (S/LLMs): Explore how they revolutionize natural language understanding and generation.
2. Prompt Engineering: Master the craft of designing effective prompts to unlock LLMs' full potential.
3. Retrieval Augmented Generation (RAG): Learn end-to-end workflows for RAG, enhancing your applications with semantically rich information retrieval.
4. Fine-Tuning: Understand different fine-tuning methodologies to tailor LLMs for specific use-cases like EShop Customer Support.
5. Vector Database and Semantic Search with RAG: Dive into the world of vector databases, understand semantic search mechanisms, and implement them in your applications.

Hands-On Experience 🖻️

We'll guide you through a practical approach to designing an EShop Customer Support application that incorporates advanced AI capabilities such as Summarization, Q&A, Classification, Sentiment Analysis, and Embedding Semantic Search. You'll gain hands-on experience by:

• Working with cloud services like Azure OpenAI and Azure AI Search to design and deploy AI solutions.
• Utilizing vector databases for efficient semantic search and understanding the nuances of vector creation, indexing, and search algorithms.
• Fine-tuning LLMs using various methods such as Full Fine-Tuning, Parameter-Efficient Fine-Tuning (PEFT), LoRA, and Transfer learning.
• Implementing Prompt Engineering and RAG to create intelligent customer support systems that deliver contextually relevant responses utilizing semantic search capabilities.

Key Topics 🗺️

1. Choosing the Right Optimization: Learn when and how to leverage Prompt Engineering, RAG, or Fine-Tuning for optimal results.
2. Vector Database and Semantic Search with RAG: Explore vector embedding models, similarity search algorithms, and a range of real-world vector databases.
3. Design EShopSupport Architecture with LLMs and Vector DBs: Learn to integrate AI components into a microservices architecture for robust enterprise solutions.

Why Take This Course? 🤔

This course is designed to give you more than just theoretical knowledge. It's an immersive learning experience aimed at equipping you with the practical skills necessary to design advanced AI solutions for real-world applications, specifically in Enterprise settings. By the end of this course, you will have a fully functional EShop Customer Support application that showcases your newfound expertise in Generative AI.

Don't miss out on the opportunity to become an architect of cutting-edge AI solutions! 🚀

Enroll now and start your journey towards mastering Generative AI Architectures with LLM, Prompt, RAG, Vector DBs today! 🎓✨