Training course · Perplexity · Education & Teaching

Perplexity for Educators

AI-powered research with Perplexity: cited answers, source control, Spaces, Deep Research and systematic fact-checking.

Duration
1 day (7 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

This course connects Perplexity with the everyday processes of Education & Teaching. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

Perplexity combines language models with live web search and delivers answers backed by numbered citations. That makes it particularly suited to work where currency and traceability matter: market and competitor monitoring, research into regulation and standards, supplier and partner due diligence, or preparing decision papers. In this practical day you learn to phrase research questions precisely, steer the choice of sources deliberately and use follow-up questions to turn an initial answer into a robust research result.

You work with Spaces, where you group research on a topic, add your own files and set instructions for the team. With Deep Research you produce extensive reports that evaluate many sources and bring them together in a structured way. Quality is a key focus: you learn to assess sources, cross-check claims and recognise typical failure patterns such as outdated or misattributed information. We also address data protection and licensing questions for business use. You leave with a reusable research process tailored to your own function.

Schools, universities, adult education providers and corporate academies are undergoing a fundamental shift with generative AI. Educators use AI assistants to differentiate teaching materials, create tasks at different levels, prepare feedback and write course descriptions. At the same time, AI challenges established assessment formats, coursework and the very notion of independent work. Educational institutions therefore have two jobs: to make their own work lighter in sensible ways and to equip learners to use AI competently and critically. A pedagogically sound approach frees up time for individual support, while careless use risks lower quality, data protection issues and unclear grading criteria.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

Who is this course for?

  • Teachers in general and vocational schools
  • University lecturers
  • Trainers in adult and continuing education
  • L&D and corporate academy managers
  • Heads of school and programme directors

Typical challenges we address

  • Mixed-ability groups that need differentiated materials
  • Heavy workload for marking, feedback and documentation
  • Uncertainty about assessment and independent work in the age of AI
  • Unclear rules on which tools may be used with which data

What you will be able to do

  • You phrase precise research questions and steer the choice of sources deliberately.
  • You assess sources by origin, currency and reliability and trace claims back to the original.
  • You organise research in Spaces and combine web sources with your own documents.
  • You use Deep Research to produce structured reports and decision support.
  • Create differentiated teaching and learning materials with AI while safeguarding subject accuracy.
  • Develop assessment and task formats that deal sensibly with AI use.
  • Draft practical rules for privacy-compliant AI use in your institution.

Course outline

Module 1 Foundations of AI-powered research
  • How it works: language model, live web search and citations
  • How it differs from a classic search engine and a general chat assistant
  • Framing research questions precisely: time frame, region, source type
  • Follow-ups and drilling down instead of one-off queries
Module 2 Steering and assessing sources
  • Narrowing sources: web, academic literature, your own files
  • Targeting primary sources, official websites and specialist publications
  • Assessing source quality: origin, currency, vested interests
  • Tracing quotes and figures back to the original source
Module 3 Spaces and teamwork
  • Setting up Spaces for topics, projects or client requests
  • Uploading your own documents and combining them with web sources
  • Storing instructions for consistent output formats
  • Sharing research and turning it into pages or reports
Module 4 Deep Research and structured reports
  • Tackling broad questions with Deep Research
  • Producing market overviews, competitor comparisons and topic briefs
  • Turning results into tables, side-by-side comparisons and executive summaries
  • Recognising the limits of in-depth research and refining results
Module 5 Fact-checking, data protection and workflow
  • Systematic fact-checking: counter-research and spotting contradictions
  • Typical failure patterns: outdated, misattributed or fabricated details
  • Data protection, enterprise licences and handling confidential queries
  • A reusable research process and source documentation
Module 6 Practice lab: Education & Teaching
  • Differentiating materials
  • Generating tasks and exercises
  • Preparing feedback
  • Course and module planning
  • Building learners' AI literacy
  • Communication and administration
Module 7 Data protection, quality & transfer to daily work
  • Pupil and learner data, grades and special needs information are highly sensitive and may only be processed in approved systems, ideally anonymised; national and regional education and data protection rules apply. Grading and examination decisions remain with educators, and AI use in assessed work must be governed by transparent rules.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

Practical scenarios from your field

Differentiating materials

From a source text, AI creates versions for different ability levels, language proficiency or support needs – with glossaries, guiding questions and extension tasks that the teacher checks and adapts.

Generating tasks and exercises

Practice questions, case studies, quizzes and model answers are created to match learning objectives and competence levels and can be imported into learning platforms. Variants for resits are easy to produce too.

Preparing feedback

Based on a marking rubric, AI drafts constructive, criteria-based feedback on anonymised work, which the educator adds to, weighs and takes responsibility for. Learners receive detailed feedback sooner.

Course and module planning

AI supports outline and lesson planning for teaching units, seminars or trainings, suggests changes of method and drafts module descriptions with clear learning outcomes. Timings and material lists are included.

Building learners' AI literacy

Educators design tasks in which learners use AI deliberately, verify its output and reflect on their process, rather than simply banning or ignoring AI use.

Communication and administration

Letters to parents, participant information, meeting minutes and FAQ answers are drafted faster, prepared in several languages and brought into a consistent tone. Key dates and deadlines are highlighted.

Prerequisites

Experience with online research in a professional context; no prior AI knowledge is required. Experience in teaching, training or education management; no technical background required.

Technical requirements

A laptop with an up-to-date browser and a Perplexity account; we recommend Pro or Enterprise access to use Spaces with files and Deep Research in full.

Data protection & compliance

Pupil and learner data, grades and special needs information are highly sensitive and may only be processed in approved systems, ideally anonymised; national and regional education and data protection rules apply. Grading and examination decisions remain with educators, and AI use in assessed work must be governed by transparent rules.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Fri, 27 November 2026 Online Request
  • Fri, 4 December 2026 Hanover Request
  • Fri, 18 December 2026 Online Request
  • Fri, 8 January 2027 Online Request
  • Wed, 13 January 2027 Munich Request
  • Tue, 26 January 2027 Online Request

Frequently asked questions

How does Perplexity differ from ChatGPT or a search engine?

A search engine returns a list of links, and a general chat assistant often answers from its training data. Perplexity searches the web at the moment you ask, summarises what it finds and backs each statement with citations. That makes it particularly well suited to current, verifiable research – although you still need to assess the sources yourself.

Can I rely on Perplexity's citations?

Citations make verification much easier, but they do not replace it. Occasionally a statement is attributed to a source that does not say quite that, or an outdated page is used. In the course you learn a lean fact-checking routine that lets you quickly verify critical statements against the original source.

Is Perplexity suitable for confidential research within a company?

Enterprise plans offer additional commitments on data use and administration. Even so, you should not put trade secrets or personal data into queries unless your internal policy explicitly allows it. We discuss how to phrase queries so that sensitive details stay protected while the research remains useful.

Can I let AI mark my students' work?

AI can prepare feedback drafts on anonymised texts, but grading remains your responsibility. Names, marks and support information do not belong in unapproved tools. In the course we practise anonymising work, applying rubrics and critically weighing AI suggestions. Responsibility stays clearly with you.

How should I deal with AI-written coursework?

Bans alone fall short, and AI detectors are unreliable. More effective are formats that make process and reflection visible, such as oral components, learning journals or disclosed AI use. The course presents concrete task formats and policies that allow independent work to be assessed fairly.

How much does “Perplexity for Educators” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 1 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart or Kaiserslautern. We can also run the course exclusively for your team.

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