Knows howto calculatea percentagechangeKnows howto create apie chart inExcelKnowswhat ahistogramis used forHasexperiencewith cloudcomputingplatformsKnowswhat adict is inPythonHas donedataanalysisCan explainmachinelearningconceptsKnows howto create abar chart inExcelHasattended adata sciencebootcampHasattended adata sciencemeetup orconferenceKnows howto importdata into aspreadsheetor databaseHas built adashboardusingTableau orPower BIHasexperiencewithclusteringalgorithmsHascodedin RCanidentifyoutliers ina datasetHasconductedbasic datacleaningtasksCan identifytrends in atime seriesdatasetHas usedExcel fordataanalysisCan interpreta basicregressionanalysisUnderstandsthe conceptof data typesHas used pivottables for datasummarizationHasdeployedmachinelearningmodelsPursuing adegree indata scienceor analyticsFreeCandescribe theprocess ofhypothesistestingHasexperiencewithpredictivemodelingKnowswhat abox plotrepresents Can explainthe conceptof overfittingin machinelearningCancalculate asimplecorrelationcoefficientCan explainthe conceptof datanormalizationCaninterpretA/B testresultsCan explainthe differencebetweenmean andmedianHascoded inPythonHas donedatavisualisationHascreated abasic lineplotHascontributed toopen-sourcedata scienceprojectsKnows howto calculatea percentagechangeKnows howto create apie chart inExcelKnowswhat ahistogramis used forHasexperiencewith cloudcomputingplatformsKnowswhat adict is inPythonHas donedataanalysisCan explainmachinelearningconceptsKnows howto create abar chart inExcelHasattended adata sciencebootcampHasattended adata sciencemeetup orconferenceKnows howto importdata into aspreadsheetor databaseHas built adashboardusingTableau orPower BIHasexperiencewithclusteringalgorithmsHascodedin RCanidentifyoutliers ina datasetHasconductedbasic datacleaningtasksCan identifytrends in atime seriesdatasetHas usedExcel fordataanalysisCan interpreta basicregressionanalysisUnderstandsthe conceptof data typesHas used pivottables for datasummarizationHasdeployedmachinelearningmodelsPursuing adegree indata scienceor analyticsFreeCandescribe theprocess ofhypothesistestingHasexperiencewithpredictivemodelingKnowswhat abox plotrepresents Can explainthe conceptof overfittingin machinelearningCancalculate asimplecorrelationcoefficientCan explainthe conceptof datanormalizationCaninterpretA/B testresultsCan explainthe differencebetweenmean andmedianHascoded inPythonHas donedatavisualisationHascreated abasic lineplotHascontributed toopen-sourcedata scienceprojects

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