Kuest AI

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Learn data science 10x faster with AI

pandas, statistics and visualization. Paste your notebook code or output and Kuest helps you understand what your data is telling you.

4.87en iOS13,917,000+estudiantes ya estudian con Kuest

topics
10
Core tools
Python, pandas, matplotlib
Builds on
Statistics and programming
Leads to
Data analysis and machine learning

See how Kuest teaches it

It asks before it tells, so you do the thinking and it sticks.

You: My dataset's average income is $95,000 but the median is $52,000. Which one should I report?
Kuest: Good catch that they differ so much. What would have to be true about the data for the mean to be that much higher than the median?
You: Maybe a few people have really high incomes?
Kuest: That's the usual reason. How could you check that in pandas or with a chart?
You: df["income"].describe() to see the max and quartiles, or a histogram to see if it's skewed right.
Kuest: Exactly. If it's right-skewed, the median better describes a typical person, and you can mention the mean to show the skew.

In skewed data the mean gets pulled toward the tail, so the median usually describes the typical value better.

Students who lock in with Kuest

students
13,917,000+
App Store rating
4.87
countries
100+
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The method

How to study Data science with Kuest

Data science is part coding, part statistics and part judgment. Learn it by asking a question of a real dataset, predicting what you'll see before you plot it, and explaining the result in plain words. Review the statistics regularly, since that's where most misreadings come from.

  1. Paste your code and outputTutor chat

    Share the pandas code, the error or the table it printed. Kuest asks what you expected and helps you read what the data shows.

  2. See the distributionGraphs

    Kuest graphs distributions, scatter plots and regression lines so you can see skew, outliers and trends.

  3. Snap a chart or slideSnap a photo

    Take a photo of a chart from class or a paper and ask what it shows and what it doesn't.

  4. Check your statisticsQuizzes

    Quizzes on p-values, confidence intervals and chart choice build the judgment that code alone doesn't give you.

  5. Listen on the goPodcasts

    Turn your lecture notes into a podcast that reviews concepts like sampling bias and regression.

  6. Remember the pandas APIFlashcards

    Spaced flashcards for loc versus iloc, groupby, merge and common statistics terms keep them within reach.

What you'll cover

Tap a topic to learn it now.

  1. 01The data science workflowGo from a question to data, cleaning, analysis and a clear conclusion.
  2. 02pandas basicsLoad CSVs, select columns and filter rows with DataFrames and boolean masks.
  3. 03Cleaning dataHandle missing values, duplicates, wrong types and messy strings.
  4. 04Grouping and mergingSummarize with groupby and agg, and combine tables with merge.
  5. 05Descriptive statisticsDescribe data with mean, median, spread and percentiles, and spot outliers.
  6. 06VisualizationChoose the right chart and build it with matplotlib or seaborn.
  7. 07Probability and distributionsReason with the normal distribution, sampling and the central limit theorem.
  8. 08Hypothesis testingRun and interpret t-tests and confidence intervals without overclaiming.
  9. 09RegressionFit and read a linear regression, including coefficients and residuals.
  10. 10Communicating resultsExplain findings, limits and uncertainty to people who didn't do the analysis.

Try asking

Tap a question and Kuest starts teaching it, step by step.

Helps you prepare for

  • Intro to data science courses
  • AP Statistics
  • Data analyst interviews
  • Data science bootcamps

A month of Kuest costs less than one hour with a tutor

Same patience, any hour, every subject. Or stay on the free plan for good.

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  • One subject per session
  • Stops when the hour ends

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$10a month, billed yearly

  • Every subject and exam on this site
  • Any hour, as long as you need
  • Quizzes, flashcards, podcasts and mock exams

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