This paper is mainly methodological. It is concerned with the different ways me may analyse personal life course data. Personal life courses are defined by a succession of events regarding living arrangement, familial life, education, professional career, health, etc. We may focus on one of these events — leaving home, marriage, first job, divorce, becoming disabled — and examine how the hazard of experiencing it evolves with time and may be affected by other factors or events. Alternatively, we may be interested, in a more holistic way, in analysing and comparing whole sequences. The paper surveys the main available methods and classifies them into a typology that distinguishes between the nature of data — time stamped events or sequences — they need and the kind of questions — descriptive or causal — they address. Both classical statistical methods and promising but less known data-mining-based approaches are discussed. The aim of the paper is to put these approaches into perspective by focusing on their specificity and the complementary views they bring on life courses. Three illustrations using data from the Swiss Household Panel will show the kind of results we may expect from some of the less known methods: The first concerns sex differences in working status mobility, the second is a survival tree analysis of the risk to divorce, while the third focuses in sex differencesin the sequencing of a selection of young adults life events.