Practical AI tutorials, official courses, prompt engineering, RAG, agents, evaluation, model foundations, and domestic model API learning paths.
A practical first tutorial: understand GenAI limits, turn one vague task into a prompt template, and write an acceptance checklist.
Define role, input, constraints, examples, output format, and verification rules for a daily work task.
Choose one document set, design chunking and retrieval, test answers with citations, and define fallback rules.
Compare Qwen, DeepSeek, Kimi, and Zhipu by context length, tool support, price, and latency.
DeepLearning.AI course for non-technical AI literacy.
Microsoft open curriculum for AI fundamentals.
Google's practical introduction to machine learning concepts.
Practical examples for building with LLM APIs.
Courses for transformers, agents, diffusion, and open models.