This week in Neo4j brings a mix of new data science and applied graph algorithms online trainings, including courses on using Neo4j with Python data science tools and applying graph algorithms to enhance applications. A blog series by Max De Marzi explores finding fraud with Neo4j, covering modeling credit card transactions as a graph and optimizing the model for scale and performance. Additionally, Keith Damiani presented on connecting the dots between graph databases and Laravel, and Jesús Barrasa released a new version of NSMNTX, a Neo4j plugin for working with RDF data. Graph algorithms were also covered in a talk by Amy Hodler and her colleague, introducing the Graph Algorithms Playground, a tool for using graph algorithms without writing code. Other topics include exploring League of Legends data in Neo4j, powering data discovery systems at Airbnb and Lyft, Cypher index hints, and migrating dimensional models into property graphs. The developer relations team also invites feedback on the new GraphQL integrations or GRANDstack via a short survey.