Course Includes:
- Price: FREE
- Enrolled: 0 students
- Language: English
- Certificate: Yes
- Difficulty: Beginner
Coupon verified 09:04 AM (updated every 10 min)
Course Folder
What You'll Learn
- 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
Requirements
- 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.
Description
This course contains the use of artificial intelligence.
Cooking Up AI: From Basics to Agentic Systems is a beginner-friendly course designed to help anyone understand Artificial Intelligence, Large Language Models, AI Agents, RAG, MCP, and AI architectures using simple food, cooking, and kitchen analogies. Instead of overwhelming learners with complex technical jargon, this course explains modern AI concepts in a way that feels familiar, practical, and easy to remember.
If you have ever wondered how ChatGPT, Generative AI, AI copilots, autonomous agents, or enterprise AI systems actually work, this course gives you a clear foundation. You will learn how AI is like a kitchen, where data becomes ingredients, models become recipes, compute becomes kitchen equipment, and AI systems become full restaurants capable of serving intelligent outcomes.
The course begins with the basics of what AI is, how it differs from regular software and automation, and why concepts like training, inference, narrow AI, and general AI matter. You will then explore how data quality, data preprocessing, bias, and labeling affect the performance of AI systems, just like fresh or spoiled ingredients affect the quality of a meal.
Next, you will learn how machine learning models work, including supervised learning, unsupervised learning, neural networks, pretraining, and fine-tuning. These topics are explained through recipe-based analogies so learners can understand how AI models learn patterns and generate results.
A major part of the course focuses on Large Language Models, including tokens, context windows, hallucinations, and prompt engineering. You will learn how to give better instructions to AI systems using zero-shot prompting, few-shot prompting, system prompts, structured prompts, and reusable prompt patterns.
The course then moves into more advanced but highly practical topics such as tools and APIs, function calling, Retrieval-Augmented Generation, embeddings, vector databases, chunking, and RAG evaluation. You will understand how AI systems can look up information, retrieve relevant knowledge, and produce more accurate responses.
You will also explore the exciting world of AI agents and agentic AI systems. Using the analogy of autonomous chefs and full kitchen teams, you will learn about agent loops, memory, reasoning, tool use, multi-agent systems, orchestration, task decomposition, and failure handling.
The course also introduces Model Context Protocol, AI system architecture, state management, AI evaluation, red teaming, AI safety, governance, guardrails, data privacy, and responsible AI. By the end of the course, you will understand how modern AI systems are designed, evaluated, governed, and deployed in the real world.
Whether you are a student, business professional, entrepreneur, developer, educator, executive, or complete beginner, this course will help you build a strong mental model of AI, Generative AI, RAG, AI Agents, and Agentic Systems without needing advanced math, coding, or machine learning experience.
Who this course is for:
- Beginners who want to understand AI without technical jargon.,Students who are curious about artificial intelligence
- ChatGPT
- LLMs
- RAG
- and AI agents.,Non-technical professionals who want to explain AI concepts clearly in business or workplace conversations.,Business leaders
- managers
- product owners
- and executives who want a practical understanding of modern AI systems.,Developers and technical learners who want a simple mental model before diving deeper into implementation.,Teachers
- trainers
- and content creators who want easy analogies to explain AI to others.,Entrepreneurs and startup founders who want to understand how AI systems
- agents
- tools
- and architectures fit together.,Enterprise professionals exploring AI adoption
- AI governance
- copilots
- automation
- and agentic workflows.,Anyone confused by AI buzzwords and looking for a clear
- beginner-friendly roadmap.,Learners who enjoy simple
- memorable explanations using real-world examples like kitchens
- recipes
- chefs
- ingredients
- and restaurants.
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