This week in Neo4j, the company announced Graph Data Science 2.0 and AuraDS releases, which are designed to make data science more accessible to developers. The new feature includes a Python client for Graph Data Science 2.0, a free training program called #GraphAcademy, and courses on building recommendation engines in Neo4j. Additionally, the company featured an interview with Michael Simons about using Neo4j's OGM with Quarkus, as well as articles on implementing simple recommendation engines and Daniel Starns' journey working on Neo4j GraphQL. The week also saw a tweet from Soliman ElSaber, where he shared his experience playing with the Egyptian football league clubs data in Neo4j.