Perplexity: Foundations
Apply Perplexity through capabilities, limitations, responsible use.
Beginner / Structured learning draft / Version 0.9
Structured learning draftAI Research: Perplexity & Gemini
Build a responsible AI workflow for a real work task. You will finish with a documented prompt, verification and revision workflow.
This open learning manuscript is undergoing course-specific editorial review. It does not provide certification. Progress and notes are stored only in this browser.
AI toolsTool stack
PerplexityGoogle Gemini
12guided lessons
4focused modules
1reviewable project
PDFoffline workbook
The problem
What this course helps you do
AI Research: Perplexity & Gemini is a structured, practical course covering Perplexity, Gemini, AI search. It emphasizes explainable methods, checked work and a final outcome that can be reviewed.
Who it is for
People who want dependable, responsible AI-assisted workflows.
Prerequisites
- Basic computer and web skills
Portfolio-ready project
Produce a reviewable AI Research: Perplexity & Gemini project using Perplexity, Gemini, AI search.
Deliverable: A working AI Research: Perplexity & Gemini artefact plus an evidence-based self-review.
Practice fileResponsible AI workflowA source, instruction, review and privacy-check worksheet.Planning template · MarkdownProject briefDefine the user, outcome, boundaries, evidence and acceptance criteria before building.Printable workbook · PDFComplete course workbookA4-ready lesson prompts, project worksheets, evidence logs and references.
Downloads open without an account. Practice data is fictional; review each file before using it in another system.
Definition of done
- The output matches the stated outcome.
- Inputs and decisions are reproducible.
- Boundary and failure evidence is included.
- Limitations and responsibility considerations are explicit.
Course plan
From first concept to finished work
Gemini: Working methods
Apply Gemini through clear instructions, context design, verification.
AI search: Applied workflows
Apply AI search through research, creation, automation.
Perplexity: Quality and review
Apply Perplexity through evaluation, privacy, repeatable practice.
Source-led learning
Authoritative references
Course claims are grounded in primary documentation and recognized public guidance. Recheck version-sensitive information before professional use.