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

Generative AI Architectures with LLM, Prompt, RAG, Vector DB from Udemy. Design and Integrate AI-Powered S/LLMs into Enterprise Apps using Prompt Engineering, RAG, Fine-Tuning and Vector DBs

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Courses Contents

* Overview of Generative AI Architectures with LLM, Prompt, RAG, Vector DB Course on Udemy

* What to Expect from the Generative AI Architectures with LLM, Prompt, RAG, Vector DB Course

* What You Will Learn in Generative AI Architectures with LLM, Prompt, RAG, Vector DB

* Why Choose This Generative AI Architectures with LLM, Prompt, RAG, Vector DB Course on Udemy

* Recommended Courses with Generative AI Focus

* Our Review of Generative AI Architectures with LLM, Prompt, RAG, Vector DB Course

* Rating the Generative AI Architectures with LLM, Prompt, RAG, Vector DB Course

* Additional Information from Search Insights

Overview of Generative AI Architectures with LLM, Prompt, RAG, Vector DB Course on Udemy

Unlock the potential of AI-driven enterprise solutions with the Generative AI Architectures with LLM, Prompt, RAG, Vector DB course on Udemy. This comprehensive program teaches you to design and integrate AI-powered Small and Large Language Models (S/LLMs) into enterprise applications, using Prompt Engineering, Retrieval-Augmented Generation (RAG), Fine-Tuning, and Vector Databases. Led by instructor Mehmet Ozkaya, this 6.5-hour course includes 11 downloadable resources, offering lifetime access, mobile/TV compatibility, and a certificate of completion. Perfect for developers and architects aiming to build advanced AI solutions, this course is a game-changer. Enroll today with udemy coupon codes SEPT25 (valid until September 30, 2025—check the offer box below for the discount link!).[](https://www.udemy.com/course/generative-ai-architectures-with-llm-prompt-rag-vector-db/)

What to Expect from the Generative AI Architectures with LLM, Prompt, RAG, Vector DB Course

This 6.5-hour course delivers a hands-on learning experience, guiding you through designing an EShop Customer Support application with AI-powered features. Mehmet Ozkaya combines step-by-step instruction with real-world projects, covering Prompt Engineering, RAG, and Vector DBs. Aimed at AI developers and software engineers, it uses the LLM Augmentation Flow to teach practical integration of LLMs like ChatGPT, Llama, and Gemini. Udemy’s platform ensures flexible access across mobile, desktop, and TV, making learning seamless.[](https://mehmetozkaya.medium.com/generative-ai-architectures-with-llm-prompt-rag-fine-tuning-and-vector-db-636783149420)

What You Will Learn in Generative AI Architectures with LLM, Prompt, RAG, Vector DB

By completing this course, you’ll master:

* Designing AI-Powered Architectures for enterprise applications.

* Crafting advanced prompts using Zero-Shot Prompting and Chain-of-Thought techniques.

* Implementing RAG Systems for precise, context-aware responses.

* Leveraging Vector Databases for semantic search and embeddings.

* Fine-tuning LLMs for Sentiment Analysis and classification tasks.

* Building a complete EShop Support app with Q&A Chat capabilities.

Why Choose This Generative AI Architectures with LLM, Prompt, RAG, Vector DB Course on Udemy

This course stands out due to Mehmet Ozkaya’s industry expertise and its focus on practical, cutting-edge AI tools. Updated for 2025, it covers real-world applications like Text Generation and Semantic Search, making it ideal for developers aiming to lead in AI innovation. With 6.5 hours of content and 11 downloadable resources, it offers exceptional value. Use udemy promo codes SEPT25 to get at a discount (see offer box)

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* AI & LLM Engineering Mastery: GenAI, RAG Complete Guide: Master RAG, AI agents, and vector databases with real-world projects.

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* RAG, AI Agents, and Generative AI with Python and OpenAI 2025: Develop advanced RAG systems and AI agents with Python.

Our Review of Generative AI Architectures with LLM, Prompt, RAG, Vector DB Course

From a website admin perspective, this course is exceptionally well-organized, with Mehmet Ozkaya delivering clear, actionableかと

System: actionable insights. The hands-on EShop Support project effectively integrates LLM capabilities like summarization and Q&A, making it highly practical. However, beginners may need some Python familiarity, and advanced learners might want deeper fine-tuning details. It’s a top choice for developers focused on Generative AI Architectures. With udemy courses coupon SEPT25, it’s a steal

9.4Expert Score

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

6.5 hours on-demand video

9.4

11 downloadable resources

9.4

Access on mobile and TV

9.4

Certificate of completion

9.4

* Pros:

* Practical, hands-on AI integration projects.

* Covers cutting-edge tools like RAG and Vector DBs.

* Ideal for intermediate to advanced developers.

* Cons:

* Assumes basic Python and AI knowledge.

* Limited depth on advanced fine-tuning scenarios.

Rating the Generative AI Architectures with LLM, Prompt, RAG, Vector DB Course

Overall Rating: 8.7/10

* Content: 8.5/10 – Comprehensive coverage of Generative AI Architectures and LLM integration.

* Delivery: 8.5/10 – Clear but requires some technical background.

* Value: 9/10 – Affordable with udemy discounts coupon SEPT25.

Enroll now to master AI-powered architectures with this top-tier course!

Additional Information from Search Insights

This course aligns with trending search keywords like Prompt Engineering, RAG Systems, Vector Databases, and LLM Integration, reflecting the growing demand for AI-driven enterprise solutions in 2025. These terms highlight the course’s relevance for developers aiming to build intelligent, scalable applications, making it a strategic career investment.[](https://mehmetozkaya.medium.com/generative-ai-architectures-with-llm-prompt-rag-fine-tuning-and-vector-db-636783149420)

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The modules are sequenced to unpack Generative AI (GenAI) step by step, blending theory with scenarios you can reuse at work while keeping the Udemy course reviews tone in mind.

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