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Sessions Library

Browse the completed sessions we have already offered. 
Watch each one, anytime, or download the slides to dive into the data.

Developer Communities:
How & where to engage with developers

In this collaborative Session, SlashData is talking about developer communities, sharing the latest available insights from our global survey. We are looking at where developers go to seek information, what types of information they’re looking for, and the support and interaction they expect from the community and vendors. Stack Overflow presents how to use developer community activity to define opportunity and how Collectives addresses developers’ needs.

Which developers are working on Generative AI projects?

In this session we will look at what developers have to say about working on Generative AI projects. Generative AI seems to have taken the world by storm, introducing new productivity tools and even passing medical and bar exams. While the tech industry seems to still working out what this will mean for the future, we will take a look at the people at the heart of the revolution, developers.

The inside view on running a Developer Program

In this session, you will access direct insights on how professionals run their developer program. We will look into the data from our latest Developer Program Leaders survey, where we asked industry professionals to tell us what they do all day, how they measure success and more. The results shown come from our latest Q2 2021 survey and the responses of 96+ developer marketing, relations, advocacy or evangelism professionals

Machine Learning Developers & their Data

In this session, we look into Machine Learning, Artificial Intelligence and Data Scientists and the data they work with. The results shown come from our latest Q1 2021 survey wave and the responses of 19,000+ developers.
What you will learn

  • Types of data that ML/AI/Data Scientists work with

  • How many ML/AI/Data Scientists work on each type

  • Which types are frequently used together

  • The professional / hobbyist/student mix in the ML/AI/Data Scientists data ecosystem

  • Industry application areas for different data types

  • The size of unstructured training data ML/AI/Data Scientists use