Here’s a brief overview of what we did in GraphAcademy last quarter:
New GraphAcademy Course: Cypher Aggregations
We are pleased to announce our new Cypher Aggregations course.
The course takes approximately four hours to complete.
In this course, you’ll learn how to:
Profile and explain how aggregation works at runtime
- Using collect()
- Using count()
- Using pattern comprehension
Work with lists
- Functions that return a single value
- Functions that return lists
- Element type transformations
- List selection predicates
- List comprehension
Use aggregating functions
- percentages and percentiles
Updated Challenge: Importing CSV Data
We have recently updated the Importing CSV files with the Neo4j Data Importer Challenge in the Importing CSV Data course to use the Import tab in Neo4j Workspace. Neo4j Workspace is a single tool that combines the most commonly used tools into one place, allowing you to Explore, Query, and Import in the same tab.
When you click the Open the Challenge in Neo4j Workspace button in the challenge, you will now be taken to Neo4j Workspace. The steps to complete the challenge are pinned on the right-hand side of the screen, guiding you through every stage of the challenge.
We’d love to hear your thoughts on the change and whether you find this approach helpful.
Updated Course: Building Neo4j Applications With Go
While updating the Building Neo4j Applications With Go course to the latest version of the Neo4j Go Driver, we have revamped the course to take on the shorter format. The shorter format still teaches you everything you need to know, but it should also be less of a commitment.
Like the TypeScript course, the new code challenges now run in Gitpod. This means you don’t have to clone the repository to complete the course. Everything can be done online directly from your internet browser.
Improved Course Recommendations
You may have noticed the Similar Courses section added to the GraphAcademy course overview page providing course suggestions. We have added a new section to the course completion email that offers personalized recommendations based on your enrollment history. All powered by Neo4j, of course!
The suggestions are generated by a hybrid recommendation engine that combines content-based recommendations with collaborative filtering. The content-based recommendations use relationships to find common courses, for example, ones in the same category, while the collaborative filtering step uses the enrollment history of similar users to improve the recommendations.
We also throw a curveball by suggesting the lowest-ranked course if you want to try something completely different. We refer to this as serendipity!
We hope that you find these suggestions helpful.
Let Us Know About Your Learning Experience!
We’d love to hear about your experiences learning Neo4j through our website, documentation, and GraphAcademy. We’re also happy to send you some swag as a thank-you.
We relish every opportunity to improve the learning experience for our users, and the best way to do that is with your feedback.
If you are interested in providing feedback, please complete this form, and we will get back to you to arrange a convenient time to talk.
Adam Cowley, Elaine Rosenberg, and the Neo4j Developer Relations Team