Hastrained amodel ona GPUHasmanuallycleaned aCSV in ExcelHasneverused gitTuned hyper-parametersfor hours withnoimprovementPrefers shippingsomethingsimple overbuildingsomethingcleverTried toexplain whycorrelation≠ causationSpeaks>4 naturallanguagesPrefersTableau toPowerBIHad a modelworkperfectly…only intrainingHad toexplain p-values to anon-technicalaudienceKnowsBayestheorem offthe top oftheir headWrote an entirefunction, only todiscover there’sa library thatdoes it betterBelievesfeatureengineering ismore importantthan modelselectionUsesJupyterStudied/studiesdatascienceBuilt adashboardthat no oneever usedHas hard-codedsomething“just for thedemo”Uses ChatGPT(or Gemini/Claude) 3+times per weekPrefersGemini toChatGPTHasbrokenproductionHasworkedremotelyfull-timeHas Googledtheir ownerrormessageword-for-wordUsesRSpends moretime wranglingdata thanbuildingmodelsHas beento a datascienceconferenceHas beenasked “isthis AI?”Has vibecodedsomethingHas usedreinforcementlearningThinksXGBoostis still kingPreferspytorch totensorflowPrefersMacOSPresented amodel/dash-board, only tobe asked for anExcel exportUsesMATLABHas aChatGPTProsubscriptionSomeoneasked you to“just add AI”to a projectUsesVisualStudioCodeFound outthat yourdataset hasduplicate rowsafter analysisStillusespython 2Has copiedcode fromStackOverflowHas beenthe onlydata personon a teamThinks mostAI-generatedimages lookslightly offUsesPythonUses >4programminglanguagesHastransitionedinto datafrom anotherfieldThought aproject wouldtake aweek…it tookthree monthsTried toexplainoverfitting toyourmanager/clientHastrained amodel ona GPUHasmanuallycleaned aCSV in ExcelHasneverused gitTuned hyper-parametersfor hours withnoimprovementPrefers shippingsomethingsimple overbuildingsomethingcleverTried toexplain whycorrelation≠ causationSpeaks>4 naturallanguagesPrefersTableau toPowerBIHad a modelworkperfectly…only intrainingHad toexplain p-values to anon-technicalaudienceKnowsBayestheorem offthe top oftheir headWrote an entirefunction, only todiscover there’sa library thatdoes it betterBelievesfeatureengineering ismore importantthan modelselectionUsesJupyterStudied/studiesdatascienceBuilt adashboardthat no oneever usedHas hard-codedsomething“just for thedemo”Uses ChatGPT(or Gemini/Claude) 3+times per weekPrefersGemini toChatGPTHasbrokenproductionHasworkedremotelyfull-timeHas Googledtheir ownerrormessageword-for-wordUsesRSpends moretime wranglingdata thanbuildingmodelsHas beento a datascienceconferenceHas beenasked “isthis AI?”Has vibecodedsomethingHas usedreinforcementlearningThinksXGBoostis still kingPreferspytorch totensorflowPrefersMacOSPresented amodel/dash-board, only tobe asked for anExcel exportUsesMATLABHas aChatGPTProsubscriptionSomeoneasked you to“just add AI”to a projectUsesVisualStudioCodeFound outthat yourdataset hasduplicate rowsafter analysisStillusespython 2Has copiedcode fromStackOverflowHas beenthe onlydata personon a teamThinks mostAI-generatedimages lookslightly offUsesPythonUses >4programminglanguagesHastransitionedinto datafrom anotherfieldThought aproject wouldtake aweek…it tookthree monthsTried toexplainoverfitting toyourmanager/client

Data Science Bingo! - Call List

(Print) Use this randomly generated list as your call list when playing the game. There is no need to say the BINGO column name. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.


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  1. Has trained a model on a GPU
  2. Has manually cleaned a CSV in Excel
  3. Has never used git
  4. Tuned hyper-parameters for hours with no improvement
  5. Prefers shipping something simple over building something clever
  6. Tried to explain why correlation ≠ causation
  7. Speaks >4 natural languages
  8. Prefers Tableau to PowerBI
  9. Had a model work perfectly…only in training
  10. Had to explain p-values to a non-technical audience
  11. Knows Bayes theorem off the top of their head
  12. Wrote an entire function, only to discover there’s a library that does it better
  13. Believes feature engineering is more important than model selection
  14. Uses Jupyter
  15. Studied/ studies data science
  16. Built a dashboard that no one ever used
  17. Has hard-coded something “just for the demo”
  18. Uses ChatGPT (or Gemini/ Claude) 3+ times per week
  19. Prefers Gemini to ChatGPT
  20. Has broken production
  21. Has worked remotely full-time
  22. Has Googled their own error message word-for-word
  23. Uses R
  24. Spends more time wrangling data than building models
  25. Has been to a data science conference
  26. Has been asked “is this AI?”
  27. Has vibe coded something
  28. Has used reinforcement learning
  29. Thinks XGBoost is still king
  30. Prefers pytorch to tensorflow
  31. Prefers MacOS
  32. Presented a model/dash-board, only to be asked for an Excel export
  33. Uses MATLAB
  34. Has a ChatGPT Pro subscription
  35. Someone asked you to “just add AI” to a project
  36. Uses Visual Studio Code
  37. Found out that your dataset has duplicate rows after analysis
  38. Still uses python 2
  39. Has copied code from Stack Overflow
  40. Has been the only data person on a team
  41. Thinks most AI-generated images look slightly off
  42. Uses Python
  43. Uses >4 programming languages
  44. Has transitioned into data from another field
  45. Thought a project would take a week…it took three months
  46. Tried to explain overfitting to your manager/client