Use Perplexity Spaces for shared research, files, connectors, instructions, collaboration, and controlled team knowledge workflows.
Perplexity Spaces, Connectors, and Team Knowledge is an AcademAI intermediate course in the Perplexity Research & Workflows path for learners who want practical AI capability instead of passive tool exposure. It belongs to the Perplexity Research Training topic hub. The course includes 5 modules and an estimated workload of 3-4 hours. Start with the free AI Fluency foundation course before checkout; paid membership unlocks full access to this course and the broader catalog. The course is designed for Teams, managers, researchers, and knowledge workers turning Perplexity into a shared research workspace.. Learners should expect prerequisites such as Perplexity 101 recommended; Basic team knowledge-management experience. Core outcomes include Design Spaces around projects, owners, source boundaries, and review rules.; Use files, pinned threads, shared instructions, and app connectors responsibly.; Separate collaborative research from private or restricted source material.. AcademAI course material is source-informed by public provider documentation where relevant, but the lessons, exercises, scenario mastery tests, and completion certificates are independently written by AcademAI and are not official provider certifications.
Teams, managers, researchers, and knowledge workers turning Perplexity into a shared research workspace.
Source-informed by Perplexity's Spaces and enterprise resource materials; AcademAI adds original governance, collaboration, and review practices.
AcademAI certificates show independent course completion and are not official Perplexity credentials.
This course is part of Perplexity Research Training, AcademAI's crawlable guide to the audience, outcomes, prerequisites, source policy, and recommended course sequence for this topic.
Project structure, owners, threads, files, and source boundaries
Tone, domain rules, reusable assumptions, and maintenance ownership
Approved source sets, app connections, access scope, and review trails
Viewer/contributor norms, pinned assets, handoff notes, and thread hygiene
Freshness reviews, source audits, restricted data, and final accountability
After completing the modules, pass a realistic scenario test to qualify for an AcademAI completion certificate.
Take scenario test