Probabilistic Logic Programming is a form of Probabilistic Programming that is receiving an increasing attention for its ability to combine powerful knowledge representation with Turing completeness. The lecture will overview the main systems for learning probabilistic logic programs both in terms of parameters and of structure. For parameter learning, it will illustrate the systems PRISM, LeProbLog, EMBLEM and ProbLog2. For structure learning, it will present the systems ProbFOIL+ and SLIPCOVER.