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@neural_university_webinar: statistics and cleanliness index

AI Университет

Курсы по AI №1 🔥 📌 Самая большая база AI контента в мире - 340 тем 📌 Стажировки студентов в ТОП компаниях - KIA, Wildberries, РЖД и др. 📌 100% гарантия трудоустройства 🌐 https://neural-university.ru Заявление в РКН №7051847522

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Grade A metrics look normal cleanliness index
data from 2026-10-18
Subscribers
37,262
Median views
1,071
ERR
2.9%
Posts sampled
40
Niche Education
Post language Russian
Channel age 4 years

Data from 2026-10-18 — 19 days old.

Assessment summary

Channel of an online AI school: announcements of webinars and intensives on Codex and RAG, breakdowns of neural networks, student reviews, and graduate employment cases. There is no third-party advertising or reposts in the sample — the feed consists entirely of the school's own materials.

By the share of subscribers who see a post, the channel is behind some similar catalog channels, and reactions almost never appear — about 1% of views, while comments are closed. Plus, at 5.7 posts per day, an announcement quickly moves down the feed, so reach is limited to actually visible views, not the number of subscribers.

About the channel

Channel of the online school AI University: a feed about learning neural networks — webinars and intensives, technology breakdowns, student reviews, and graduate employment stories. They have been running in Russian for the fourth year, with varied formats: text announcements, videos, photo cards.

In the catalog, @pro_ai_novosti, @neuralforbusiness, and @aivacancychannel are nearby. By subscriber count, this channel is larger than @neuralforbusiness and @aivacancychannel, but smaller than @pro_ai_novosti. A post here is seen by a larger share of subscribers than at @neuralforbusiness and @pro_ai_novosti, but a smaller share than at @aivacancychannel.

What it publishes:

  • Webinars and intensives: announcements of classes on Codex, Skills, and RAG with registration links and start reminders.
  • Reviews and graduate cases: stories about internships and employment — with company, position, and salary.
  • AI breakdowns and news: cards about roles in AI (developer, architect, integrator) and explanations of systems like Netflix recommendations.

Posts are published mainly during the day, less often in the evening, more often on weekdays than on weekends. The feed is the school's short announcements and promo texts, without third-party forwards or others' advertising.

By subscribers, it ranks #14 of 26 channels in the Education niche of the catalog.

What to pay attention to

Low reach: ERR ≈ 2.9%

View-based engagement is below the norm for a channel of this size. It may be explained by the niche and a passive audience, but it's worth checking.

What grade A means

Metrics look normal: no signals lowering the index were found, or they are weak.

Channel content

📣 Heavy advertising load

The feed mainly promotes the school's own courses and webinars: pricing tiers with prices, enrollment deadlines for a discounted tier, and a promise of guaranteed employment.

Compared with similar channels

Compared with 11 Education catalog channels whose metrics look normal. They are a similar size: 12,606 to 102,027 subscribers.

ERR (reach) lower than 11 of 11
@neural_university_webinar 2.9%
similar channels median 11.6%
Reactions per 100 views higher than 8 of 10
@neural_university_webinar 1.11
similar channels median 0.27

This is not a niche norm: only catalog channels are included. A high ERR is not always a plus: if the other metrics do not support it, the index goes down.

Dynamics and anomalies

Scroll horizontally to see the full charts.

Views by post

The latest 40 posts with views, from Oct 11 to Oct 18. The dashed line is the median (1,071).

08131.6KOct 11: 1,140 viewsOct 11: 1,217 viewsOct 11: 1,304 viewsOct 11: 1,051 viewsOct 11: 1,138 viewsOct 11: 1,213 viewsOct 12: 1,147 viewsOct 12: 1,182 viewsOct 12: 1,032 viewsOct 12: 1,216 viewsOct 12: 1,111 viewsOct 12: 1,171 viewsOct 12: 1,210 viewsOct 12: 1,229 viewsOct 13: 1,209 viewsOct 13: 1,491 viewsOct 13: 1,541 viewsOct 13: 1,595 viewsOct 13: 1,627 viewsOct 14: 1,092 viewsOct 14: 1,030 viewsOct 14: 1,159 viewsOct 15: 1,103 viewsOct 15: 999 viewsOct 15: 1,000 viewsOct 15: 957 viewsOct 15: 948 viewsOct 15: 861 viewsOct 15: 879 viewsOct 15: 921 viewsOct 16: 831 viewsOct 16: 860 viewsOct 16: 864 viewsOct 16: 873 viewsOct 17: 768 viewsOct 18: 510 viewsOct 18: 531 viewsOct 18: 543 viewsOct 18: 554 viewsOct 18: 551 views Oct 11Oct 18
  • post views
  • 5 posts newer than one day and still gaining views
  • median 1,071

Maximum: 1,627 views. Data as of Oct 18.

What scoring found in the view pattern

Low reach: ERR ≈ 2.9%

View-based engagement is below the norm for a channel of this size. It may be explained by the niche and a passive audience, but it's worth checking.

Cleanliness-index history

The channel's data has been collected once — the chart will appear after the next update.

Advertising outlook

Advertising placement: not recommended.

Only a small share of subscribers sees the posts.

About 534–553 people will see your post in the first 48 hours.

Reach of advertising posts

No advertising posts among the latest 40.

Buy advertising

Telegram ads are sold on these marketplaces — they have channel catalogs, prices, and checkout.

We don't sell ads. This channel may not be listed there.

Where to buy advertising

Affiliate links: we get a commission. It never affects the channel's score.

Questions about @neural_university_webinar

What does grade A and a purity index of 85 out of 100 mean?

The purity index is 85 out of 100, grade A, level “metrics within norm”. No notable deviations were found in the check; among the issues, only low reach was noted.

What share of subscribers see the channel's posts?

The median post gets about 1071 views with 37 thousand subscribers — that's roughly 2.9% of the base. A post is seen by a small share of subscribers.

Can advertising be placed here?

Our assessment of the feasibility of ad placement is doubtful. Reason: a post is seen by a small share of subscribers, so the reach of a single placement is limited.

How the assessment was produced

Data source
Public Telegram data: posts, views, reactions, and channel metadata.
Date or snapshot
2026-10-18
Sample
The latest 40 public posts available at check time.
Calculation method
TG Inspector calculates metrics from the saved snapshot and combines independent signals into a deterministic 0–100 cleanliness index.
Factual result
The @neural_university_webinar assessment dated 2026-10-18 uses 40 recent public posts. At that snapshot the channel had 37,262 subscribers, median post views were 1,071, ERR was 2.9%, and the cleanliness index was 85/100.
Limitations
This is a probabilistic assessment based on public data: it describes metrics, not the owner's actions, and is not a real-time measurement.

Full methodology and interpretation rules

This automated assessment is probabilistic: it describes the channel's public metrics, not its owner's actions. The index and grade are calculated from public data and are not changed on request. Channel owners can request removal of the page — t.me/obsessed_with_ai.