[MULTI] Llm Engineering Fundamentals : Generative Ai, Agents & Rag

[jinkping5]

Llm Engineering Fundamentals : Generative Ai, Agents & Rag
Published 2/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 47m | Size: 1 GB​

Foundations for professionals working with LLMs and generative AI
What you'll learn
Understand how Generative AI and Large Language Models (LLMs) actually work, beyond tools and hype
Explain why LLMs sound intelligent, where they fail, and why hallucinations and confident mistakes occur.
Understand core LLM concepts such as tokens, embeddings, context windows, transformers, attention, training, fine-tuning, and prompting.
Understand how LLMs are used in real-world systems, including Retrieval-Augmented Generation (RAG) and AI agents.
Identify the limits, risks, and ethical considerations of using LLMs in business and enterprise environments.
Develop a realistic, future-proof understanding of Generative AI, enabling better decisions when working with or around AI systems.
Requirements
No prior AI, machine learning, or programming experience is required
No technical background is needed
No coding, tools, or software installation is required
Description
Generative AI and Large Language Models (LLMs) are everywhere - but most people use them without truly understanding how they work, why they fail, or where their limits are.This course is designed to give you a clear, realistic, and future-proof understanding of Generative AI, without focusing on tools, coding, or temporary frameworks. Instead of teaching what buttons to click, this course explains what is actually happening behind the scenes when an LLM generates text, makes mistakes, or appears intelligent.You will learn how LLMs work at a conceptual level, including next-token prediction, tokens, embeddings, context windows, transformers, attention, training, fine-tuning, and prompting. You will also understand why LLMs hallucinate, how bias appears in outputs, and why confident answers can still be wrong.The course goes beyond theory to explain how LLMs are used in real-world systems, including Retrieval-Augmented Generation (RAG) and AI agents, and why many agent systems fail in production. It also covers ethical concerns, data responsibility, enterprise risks, and what the future of Generative AI will realistically look like.This course is ideal for beginners, professionals, and decision-makers who want clarity over hype and a solid foundation that remains valuable even as tools and technologies change. Keep Learning!! Keep Growing!!
Who this course is for
Beginners who are curious about AI and want clear, foundational understanding
Students and freshers looking to build strong AI fundamentals
Working professionals who use or interact with AI tools and want to understand what's happening behind the scenes
Managers, consultants, and decision-makers who need to make informed choices about AI adoption
Product, business, and non-technical roles working alongside AI teams
Anyone confused by AI buzzwords and looking for clarity over hype

Bitte Anmelden oder Registrieren um Code Inhalt zu sehen!