Use Perplexity Projects for organized research, approved files and connectors, shared instructions, Computer tasks, collaboration, and maintained team knowledge.
Perplexity Projects, 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 Projects around a purpose, owner, source boundary, collaboration rule, and review cadence.; Separate Project context, file or connector access, sharing rights, and downstream action permission.; Keep sources, instructions, threads, and Computer tasks current, attributable, and reviewable.. 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 official Projects, connectors, and enterprise resources; 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.
Purpose, owners, sessions, files, Computer tasks, source boundaries, and review cadence
Audience, output rules, approved assumptions, source requirements, and maintenance ownership
Approved sources, minimum useful access, sharing rights, freshness, and downstream authorization
Contributor roles, evidence status, handoff notes, source trails, and session hygiene
Source ownership, review dates, restricted data, unresolved questions, and final accountability
After completing the modules, pass a realistic scenario test to qualify for an AcademAI completion certificate.
Take scenario test