You'll encounter main types:
Supervised Fine-Tuning (SFT): Train on input-output pairs. "Given this prompt, produce this response." Most common starting point.
Preference Alignment: Train the model to prefer certain outputs over others using human feedback. Makes models more helpful and less harmful.
Task-Specific: Optimize for a single task like classification, summarization, or code generation.