It's Sunday evening. You have three lectures' worth of slides, maybe 150 of them, and an exam in two weeks. You know flashcards work, and you also know that typing 150 slides into a flashcard app, card by card, will take the whole evening before you've studied anything.
You can skip most of that typing. Your slides already hold nearly everything a good deck needs, so the job is getting the content out of the slides and into question-and-answer form without doing it by hand.
This guide covers three ways to do that, from fully automatic to more hands-on. After that come a few rules for writing cards you'll keep using past the first week.
Why slides are almost flashcards already
Lecture slides are compressed notes. Your lecturer has already picked what matters, cut what doesn't, and broken the topic into small chunks. A slide titled "Causes of the French Revolution" with four bullets underneath is basically four flashcards.
Slides don't test you, though. Reading one feels like learning because everything looks familiar, but recognising a fact on a slide won't help much when you're facing a blank exam page and have to recall it. Flashcards make you pull the answer out of your own head, and that effort is what makes it stick. Spreading the reviews over several days, instead of cramming them into one night, makes the effect stronger.
So the goal is to turn each slide's main ideas into questions. Copying the slides word for word into cards misses the point.
Step 0: Get your slides into a usable file
Start with a PDF whichever method you pick. Every tool handles it well.
PowerPoint: File → Save As (or Export) → PDF
Google Slides: File → Download → PDF document
Keynote: File → Export To → PDF
If your university portal already gives you a PDF, you can skip ahead.
If your lecturer shares slides with 4 or 6 per page, try to get the one-slide-per-page version. Text extraction comes out cleaner and the diagrams stay readable.
Method 1: Use an AI study tool
This is the option for when you want to be studying in five minutes. Topic Learner and similar tools are built for this: you upload the PDF, the AI reads the content, and it generates flashcards and quizzes from it.
Upload your slide PDF.
Let it generate a set of cards.
Skim the cards and edit them. Delete the ones on things you already know cold, fix anything phrased awkwardly, and add a card or two on points your lecturer stressed out loud but never wrote down.
Start reviewing.
Please don't skip step 3. AI is good at pulling facts out of a document, but it has no idea your professor spent twenty minutes on slide 34 and said "this will be on the exam." You do, and two minutes of editing gets that into the deck.
This works best for text-heavy lectures: definitions, processes, anything where the slides are mostly bullets.
Method 2: A general AI chatbot plus an import
If you already have a flashcard app you like, such as Anki or Quizlet, you can use any AI assistant to generate the cards and then import them.
Upload your PDF to the chatbot, or paste the text in chunks for long decks.
Use a prompt like this:
Turn these lecture slides into flashcards.
Rules:
- One idea per card. Never put a list of more than 3 items on one card.
- Write questions that make me recall, not recognise (prefer "Why", "How", "What happens when").
- Skip title slides, agenda slides, and "questions?" slides.
- Keep answers under 25 words.
- Output as CSV with two columns: front,back. No header row. Wrap each field in double quotes.
Save the output as a
.csvfile.Import it. In Anki, use File → Import and map the columns to Front and Back. Quizlet lets you paste term and definition pairs into its import box.
This suits people who are already invested in one app and its review history. One thing to watch: with long lectures the chatbot may cut off or summarise too aggressively. For 80 or more slides, feed them in batches of 20 to 30.
Method 3: Image occlusion for diagram-heavy slides
Some slides are hardly text at all. An anatomy diagram, a circuit, a map or a labelled cell loses most of its value when you turn it into text questions.
For these, use image occlusion. You take the diagram, hide one label at a time, and quiz yourself on what's underneath. Anki has this built in: screenshot the slide, drop it in, draw boxes over the labels, and Anki makes one card per hidden label.
It's the right tool for anatomy, biology, geography and engineering diagrams, or anywhere the position of something matters as much as its name.
Most courses mix text slides and diagrams, so combining methods is normal. Let an AI tool handle the text and use image occlusion for the three or four diagrams that count.
What makes a good card
Whichever method you use, you'll get a first draft. These rules make it usable.
Put one idea on each card. "List the 7 functions of the liver" is a bad card, because you'll half-remember it every time and never know which part you're missing. Split it up, or ask about one function at a time.
Ask why and how as well as what. "What is osmosis?" is fine. "Why does a cell placed in salt water shrink?" is better, because it checks that you understand the idea and don't just know the definition.
Cut the filler. Title slides, agenda slides, "any questions?" slides and slides that repeat the previous one don't need cards. You're better off finishing a small deck than giving up halfway through a huge one.
Keep your lecturer's wording for key terms. If the same person who wrote the slides writes the exam, their phrasing is a hint, so keep technical terms exactly as they appear.
Add the context the slides leave out. If you remember an example or explanation from class, put it on the back of the card.
A realistic workflow for exam season
| When | What to do | Time |
|---|---|---|
| Right after the lecture | Export slides, generate cards | ~5 min |
| Same day | Edit the deck: delete, fix, add what was said out loud | ~10 min |
| Next day | First review session | ~10 min |
| Every few days after | Short reviews, focusing on cards you got wrong | ~10 min |
| Week before the exam | Mixed review across all lectures + practice quizzes | Daily |
Doing this after each lecture is much easier than saving it all for the end. Ten minutes a week per lecture beats a panicked weekend with 400 slides.
Common mistakes
Generating cards and never editing them. You end up with duplicates, trivia and clumsy questions, and reviewing starts to feel like a chore.
Making a card for every bullet. Not every bullet is exam material.
Only reviewing the cards you know. It feels good and teaches you very little. The cards you get wrong are the ones that help.
Waiting until the week before. Spaced review needs time between sessions, so start early and keep sessions short.
FAQ
Can I do this with handwritten notes or scanned slides?
Yes, as long as the text is readable. Scanned PDFs may need text recognition (OCR) first. Many AI tools do this automatically, but check the output for misread words, especially formulas and technical terms.
How many cards should one lecture produce?
There's no fixed number. As a rough guide, a one-hour lecture usually gives somewhere around 20 to 40 useful cards. If you're getting over 100, you're probably making cards from filler; if you're getting 5, you're probably cramming too much onto each card.
Is it cheating to let AI make my flashcards?
No. You learn when you review the cards, so automating the typing leaves you more time for that part. Editing the deck is still worth doing, since deciding what matters is part of learning too.
Flashcards or quizzes: which is better?
Use both. Flashcards work well for short daily recall. Quizzes are closer to the real exam format and show you gaps across a whole topic. Topic Learner generates both from the same document, so you don't have to choose.
The short version
Export your slides as a PDF.
Turn them into cards with a tool. An AI study app is fastest, a chatbot plus import keeps you in Anki or Quizlet, and image occlusion handles diagrams.
Spend ten minutes editing so the deck matches what your lecturer emphasised.
Review a little at a time, starting right after the lecture.
If you want to try the first method, upload your next lecture's slides to Topic Learner.