The increasing production and availability of massive and heterogeneous data bringforward challenging opportunities. Among them, the development of computing systemscapable of learning, reasoning, and inferring facts based on prior knowledge. In this sce-nario, knowledge bases are valuable assets for the knowledge representation and automa-ted reasoning of diverse application domains. Especially, inference tasks on knowledgegraphs (knowledge bases’ graphical representations) are increasingly important in aca-demia and industry. In this short course, we introduce machine learning methods andtechniques employed in knowledge graph inference tasks as well as discuss the technicaland scientific challenges and opportunities associated with those tasks.