AI Micro-Internship · ~180 min · low-code

Audit a YouTube channel: what actually drives its views?

Creators guess; analysts check. Build a dataset of one channel’s last 30 videos — views, length, title style, upload gap — and find what actually correlates with performance on that channel.

Steps

01Pick a mid-size channel you watch (not a megastar — patterns are clearer). Collect its last 30 videos into a CSV: title, views, duration, upload date, and features you code yourself (question title? number in title? thumbnail has face?).
02Normalise for age: views-per-day since upload beats raw views.
03Analyse: which features correlate with views-per-day? Where are the outliers, and what’s special about them?
04Write the memo you’d send the creator: 3 evidence-backed recommendations.

Tools: YouTube, Google Sheets, ChatGPT or Gemini for analysis help

Your submission

Submit the channel, the 30-video CSV with your coded features, the analysis, and a chart. The feature-coding is your real work — AI can’t watch the videos for you.

The channel and why you picked it *The 30-video dataset as CSV, including your hand-coded features *What correlates with views-per-day, the outliers explained, and 3 recommendations for the creator *A chart of your strongest pattern *

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