Tutorials Paths Practice AI Tools Reference

LevelEasy Start

Topics

Level Easy Change

0/33 in this chapter

01What is an LLM?
02Tokens — how AI reads text
03Training vs inference
04Transformers in plain English
05Serving Large Language Models
06Context window suitcase
07Memory & conversation state
08Temperature — safe vs creative
09Embeddings — meaning as numbers
10Vectors & similarity search
11Overfitting playground
12Multimodal AI
13Diffusion models in plain English
14RAG — look it up, then answer
15Inside RAG — the pipeline
16Chunking for RAG quality
17Vector databases explained
18Hybrid search for RAG
19Fine-tuning vs RAG
20Tools — when AI takes action
21Structured outputs & JSON mode
22Agents — think, act, repeat
23Multi-Agent Systems
24MCP — a standard plug for AI tools
25Alignment and RLHF
26Human in the loop
27Evals and benchmarks
28Reasoning models
29AI Monitoring
30Prompt injection & AI security
31Choosing a model
32Local LLMs & Ollama
33Production AI Architecture

Tutorials · Paths · Practice

Chapter C · Review

How it works review

10 mixed questions covering this chapter. No pressure — revisit lessons anytime.

How it works review

1 / 10

LLMs mainly predict…

← Back to chapter

AnyoneLearnAI · Tutorials · Paths · Practice · AI Tools · Reference

Home LearnPractice Paths

Topics

Level Easy Change

0/33 in this chapter

01What is an LLM?
02Tokens — how AI reads text
03Training vs inference
04Transformers in plain English
05Serving Large Language Models
06Context window suitcase
07Memory & conversation state
08Temperature — safe vs creative
09Embeddings — meaning as numbers
10Vectors & similarity search
11Overfitting playground
12Multimodal AI
13Diffusion models in plain English
14RAG — look it up, then answer
15Inside RAG — the pipeline
16Chunking for RAG quality
17Vector databases explained
18Hybrid search for RAG
19Fine-tuning vs RAG
20Tools — when AI takes action
21Structured outputs & JSON mode
22Agents — think, act, repeat
23Multi-Agent Systems
24MCP — a standard plug for AI tools
25Alignment and RLHF
26Human in the loop
27Evals and benchmarks
28Reasoning models
29AI Monitoring
30Prompt injection & AI security
31Choosing a model
32Local LLMs & Ollama
33Production AI Architecture

Tutorials · Paths · Practice