Learn AI, Agents, RAG, and Architectures Using Simple Food and Kitchen Analogies Anyone Can Understand
Sub Category
- Other IT & Software
{inAds}
Objectives
- Understand the fundamentals of AI using simple kitchen and food analogies anyone can follow.
- Explain the difference between AI, software, automation, narrow AI, general AI, training, and inference.
- Understand how data, models, compute, and prompts work together to produce AI outputs.
- Learn how Large Language Models work, including tokens, context windows, prompting, and hallucinations.
- Apply prompt engineering techniques such as zero-shot prompting, few-shot prompting, system prompts, structured prompts, and step-by-step reasoning.
- Understand how AI tools, APIs, plugins, and function calling allow AI systems to take action beyond simple text generation.
- Learn Retrieval-Augmented Generation, including embeddings, vector databases, chunking, retrieval, and RAG evaluation.
- Understand AI agents, agent loops, memory, reasoning, tool use, and single-agent workflows.
- Explore multi-agent systems, orchestration, task decomposition, communication protocols, and failure recovery.
- Learn how to design practical AI architectures, evaluate AI systems, apply governance principles, & build a complete AI system from prompt app to deployed agent
Pre Requisites
- No prior AI experience is required.
- No coding background is required to understand the main concepts.
- A basic curiosity about AI, ChatGPT, agents, and automation is helpful.
- Learners should be comfortable using a computer and browsing the internet.
- Beginners are welcome because every concept is explained using simple food, cooking, and kitchen analogies.
- No advanced math, machine learning, or data science knowledge is required.
- Students do not need prior experience with LLMs, RAG, AI agents, MCP, or AI architectures.
- A notebook or digital note-taking tool is recommended for capturing key concepts and examples.
- Optional: Basic familiarity with ChatGPT or other AI tools will help, but it is not mandatory.
- Optional: Learners who want to build hands-on projects may benefit from basic Python knowledge, but the course is designed to explain concepts first.
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
{inAds}
Coupon Code(s)