Paths · Student
Learn AI for students
A student path from AI literacy to research helpers, prompting, and first coding labs — structured for school and college.
Core spine
- 01AI you already use8m
- 02What is AI?8m
- 03History of AI10m
- 04AI vs human smarts9m
- 05What AI can and can't do9m
- 06Machine learning in plain English9m
- 07Generative AI vs older AI9m
- 08Speech Recognition9m
- 09Why AI makes mistakes10m
- 10Bias and fairness9m
- 11AI Copyright10m
- 12Privacy and smart sharing9m
- 13Your AI learning map8m
- 14Talk to AI for the first time8m
- 15Good prompts have a job9m
- 16Add context9m
- 17Iterate: bad to better9m
- 18Chain-of-Thought Prompting10m
- 19Study helper9m
- 20AI for Research10m
- 21AI for Teachers10m
- 22Home and life helper9m
- 23Work helper9m
- 24AI for Excel10m
- 25AI for Presentations10m
- 26Pictures and creative tools9m
- 27Spot wrong answers9m
- 28Your weekly AI habit8m
- 29What is an LLM?7m
- 30Tokens — how AI reads text6m
- 31Temperature — safe vs creative6m
- 32Embeddings — meaning as numbers7m
- 33Vectors & similarity search7m
- 34RAG — look it up, then answer8m
- 35Inside RAG — the pipeline8m
- 36Tools — when AI takes action7m
- 37Agents — think, act, repeat8m
- 38MCP — a standard plug for AI tools8m
- 39Python only what you need8m
- 40Python dictionaries9m
- 41Python virtual environments9m
- 42Data: tables and simple plots9m
- 43File handling9m
- 44Prediction: your first ML idea9m
- 45Clustering10m
- 46Decision trees10m
- 47Train a tiny model10m
- 48Loss functions10m
- 49Neural nets by building10m
- 50Deep learning10m
- 51Git basics10m
- 52GitHub basics10m
- 53Talk to an LLM from code10m
- 54Build a mini RAG11m
- 55Capstone: ship a tiny AI app12m