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DataCampGeneral MLBeginnerRegistration unverifiedRegistration unverified

Cleaning Data and the Skies

Beginners who want a low-friction first competition on a learning platform with DataLab notebooks.

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Suggested next step

Decide whether this contest fits your current stage before you sink time into the leaderboard.

Beginner score

88/100

Higher means a safer real starting point for your current stage.

Learning value

86/100

Measures whether the competition teaches habits you can transfer elsewhere.

Estimated effort

6-14 hours

Use this to check whether the task fits your current time budget.

Metric

[object Object],[object Object],[object…

If you cannot explain this metric clearly yet, you probably still need a bit of prep.

Who this competition fits

Beginners who want a low-friction first competition on a learning platform with DataLab notebooks.

Official blurb (unedited)
Your are a data analyst at an environmental company. Your task is to evaluate ozone pollution across various regions. You’ve obtained data from the U.S. Environmental Protection Agency (EPA), containing daily ozone measurements at monitoring stations across California. However, like many real-world datasets, it’s far from clean: there are missing values, inconsistent formats, potential duplicates, and outliers. Before you can provide meaningful insights, you must clean and validate the data. Only then can you analyze it to uncover trends, identify high-risk regions, and assess where policy interventions are most urgently needed. Create a report that covers the following: Scoring notes: [object Object],[object Object],[object Object],[object Object]

Prep before joining

If the items below still feel unfamiliar, you usually get a better result by preparing first instead of rushing in.

Python or R basics

DataCamp / DataLab workflow

pandas or tidyverse

Where the real difficulty shows up

The real friction is usually not library usage. It is validation, time allocation, and task framing.

Even learning competitions can stall if you have never turned analysis into a clean submission notebook.

Read this first

This guide is the best pre-read if you want a cleaner start instead of trial-and-error.

How to learn feature engineering, validation, and competition workflow without heavy hardware.

No GPU? Pick Competitions That Still Teach You Good Habits

Your decision

Use these fields to make a quick decision before you dive deeper.

Status
Registration unverified
Registration
Registration unverified
Eligibility
Needs official confirmation
Reward
$500 GIFT CARD
Compute
CPU only
Official metric
[object Object],[object Object],[object Object],[object Object]
Verification
Source page verified

Registration is unverified; confirm availability on the official page before investing.

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Official source

Rules, files, submission details, and the live deadline still come from the official page.

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Data and review state

Separate what is confirmed from what still needs review. Official rules and deadlines win — report anything that looks wrong.

Source page verifiedMetric confirmedReviewed
Source published
Jun 27, 2025
Source created
Jun 27, 2025
Published on this site
Jul 18, 2026