Hasconductedbasic datacleaningtasksCan explainthe differencebetweenmean andmedianKnowswhat ahistogramis used forCancalculate asimplecorrelationcoefficientPursuing adegree indata scienceor analyticsCan identifytrends in atime seriesdatasetKnowswhat adict is inPythonHascreated abasic lineplotHasexperiencewithpredictivemodelingCanidentifyoutliers ina datasetHascontributed toopen-sourcedata scienceprojectsFreeHasexperiencewith cloudcomputingplatformsKnows howto calculatea percentagechangeKnowswhat abox plotrepresents Has donedatavisualisationKnows howto create abar chart inExcelHasattended adata sciencebootcampCandescribe theprocess ofhypothesistestingHas built adashboardusingTableau orPower BICan explainmachinelearningconceptsCan explainthe conceptof overfittingin machinelearningHas used pivottables for datasummarizationHas usedExcel fordataanalysisHasattended adata sciencemeetup orconferenceCan explainthe conceptof datanormalizationHasexperiencewithclusteringalgorithmsHas donedataanalysisHascodedin RUnderstandsthe conceptof data typesHascoded inPythonCan interpreta basicregressionanalysisKnows howto create apie chart inExcelKnows howto importdata into aspreadsheetor databaseCaninterpretA/B testresultsHasdeployedmachinelearningmodelsHasconductedbasic datacleaningtasksCan explainthe differencebetweenmean andmedianKnowswhat ahistogramis used forCancalculate asimplecorrelationcoefficientPursuing adegree indata scienceor analyticsCan identifytrends in atime seriesdatasetKnowswhat adict is inPythonHascreated abasic lineplotHasexperiencewithpredictivemodelingCanidentifyoutliers ina datasetHascontributed toopen-sourcedata scienceprojectsFreeHasexperiencewith cloudcomputingplatformsKnows howto calculatea percentagechangeKnowswhat abox plotrepresents Has donedatavisualisationKnows howto create abar chart inExcelHasattended adata sciencebootcampCandescribe theprocess ofhypothesistestingHas built adashboardusingTableau orPower BICan explainmachinelearningconceptsCan explainthe conceptof overfittingin machinelearningHas used pivottables for datasummarizationHas usedExcel fordataanalysisHasattended adata sciencemeetup orconferenceCan explainthe conceptof datanormalizationHasexperiencewithclusteringalgorithmsHas donedataanalysisHascodedin RUnderstandsthe conceptof data typesHascoded inPythonCan interpreta basicregressionanalysisKnows howto create apie chart inExcelKnows howto importdata into aspreadsheetor databaseCaninterpretA/B testresultsHasdeployedmachinelearningmodels

Data Analytics 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 conducted basic data cleaning tasks
  2. Can explain the difference between mean and median
  3. Knows what a histogram is used for
  4. Can calculate a simple correlation coefficient
  5. Pursuing a degree in data science or analytics
  6. Can identify trends in a time series dataset
  7. Knows what a dict is in Python
  8. Has created a basic line plot
  9. Has experience with predictive modeling
  10. Can identify outliers in a dataset
  11. Has contributed to open-source data science projects
  12. Free
  13. Has experience with cloud computing platforms
  14. Knows how to calculate a percentage change
  15. Knows what a box plot represents
  16. Has done data visualisation
  17. Knows how to create a bar chart in Excel
  18. Has attended a data science bootcamp
  19. Can describe the process of hypothesis testing
  20. Has built a dashboard using Tableau or Power BI
  21. Can explain machine learning concepts
  22. Can explain the concept of overfitting in machine learning
  23. Has used pivot tables for data summarization
  24. Has used Excel for data analysis
  25. Has attended a data science meetup or conference
  26. Can explain the concept of data normalization
  27. Has experience with clustering algorithms
  28. Has done data analysis
  29. Has coded in R
  30. Understands the concept of data types
  31. Has coded in Python
  32. Can interpret a basic regression analysis
  33. Knows how to create a pie chart in Excel
  34. Knows how to import data into a spreadsheet or database
  35. Can interpret A/B test results
  36. Has deployed machine learning models