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Channel

karpov.courses

@KarpovCourses

Verified by Telegram

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts recorded as deleted · Citations · Telegram's recommendations · Cite this entry

27,313subscribers

-230 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1001430200876
TypeChannel
Username@KarpovCourses
DescriptionШкола науки о данных для любого уровня подготовки. Учим актуальным навыкам с акцентом на практику Программы: https://to.karpov.courses/Vy4YuQ Чат для общения: @karpovcourseschat Регистрация в РКН: https://gosuslugi.ru/snet/67b592291bca1d7fe17570a8
Created19 June 2020 — measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded6 August 2026
Last confirmed live11 November 2026
Measurements held61
Confirmed unchanged2 times, most recently 11 November 2026
On Telegramt.me/KarpovCourses

Topic

Education — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 10 September 2026 and assigned it the closest of 31 fixed categories, at 100% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and the other topics.

Growth

27,29927,54327,42127,3136 August 20269 November 2026
61 measurements spanning 95 days, net -230. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 27,262–27,580 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 61
Measured (UTC)SubscribersChange
9 Nov 2026, 17:0827,313-2
8 Nov 2026, 07:5027,315+16
7 Nov 2026, 00:2827,299-8
5 Nov 2026, 20:5627,307-3
4 Nov 2026, 19:5427,310+3
3 Nov 2026, 01:2727,307-4
2 Nov 2026, 02:0927,311-13
1 Nov 2026, 04:3827,324-1
30 Oct 2026, 07:3627,325-3
29 Oct 2026, 09:5927,328-6
28 Oct 2026, 09:2727,334-2
27 Oct 2026, 10:5527,336-2
26 Oct 2026, 12:3727,338-9
25 Oct 2026, 13:2627,347-2
24 Oct 2026, 16:2627,349-4
23 Oct 2026, 17:4027,353-10
22 Oct 2026, 16:3627,363+15
21 Oct 2026, 11:4127,348-14
20 Oct 2026, 09:0627,362+4
19 Oct 2026, 09:1527,358first reading

Engagement

127 posts held, back to 30 July 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 156 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
8.76%
avg views ÷ 27,313 subscribers
Avg views / post
2,390
42 posts measured
Reaction rate
0.359%
reactions ÷ views · ER floor
Posts in window
44
of 127 held

ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.

ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate. It is computed over the 40 of 42 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 12 November 2026
Posts held127 (30 July 2026 – 12 November 2026)
Views total100,521
Reactions total344
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken12 Nov 2026, 17:21 UTC

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

What this channel posts

Photos
≈2,510
Videos
≈21
Links
≈1,530

Lifetime counters from Telegram’s own channel header, read 12 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.

Video runtime
7m 04s
Average length
1m 11s

Measured directly from 6 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.

Reaction mix

1,103 reactions across 116 posts, in 13 distinct kinds. The most used accounts for 34.4% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤37934.4%
custom 544540352637099293722720.6%
🔥16214.7%
😁16014.5%
custom 5445061088628486272887.98%
👍332.99%
custom 5280503514081042965221.99%
🎉110.997%
👏110.997%
😎30.272%
😢30.272%
😱20.181%
🤯20.181%

Custom emoji. 3 of the rows above are Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The counts beside them are Telegram’s.

No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.

Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.

Coverage. Reactions were read on 120 of the 127 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 1,103 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 127 most recent posts we hold, published 30 July 2026 to 12 November 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.

Recent posts

Telegram’s own ‘edited’ marker: 4 of 44 posts held from the last 30 days (9.09%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).

12 Nov 2026, 15:18 UTC691 views2 reactionsread 12 November 2026
Photo

Представьте, что вам в подчинение наняли нескольких помощников. Один собирает информацию, второй по ней готовит презентацию, а третий следит, чтобы процессы запускались вовремя и данные не терялись между сервисами. Вы же можете сосредоточиться на сложных и интересных задачах, а не тратить время на рутину. Такими помощниками могут стать нейросети. Получать от них максимум пользы учим на курсе «Нейросети для работы». …

custom 52805035140810429651custom 54454035263709929371

12 Nov 2026, 09:17 UTC≈1,260 views9 reactionsread 12 November 2026
Photo

Почему «Чёрная пятница» — чёрная? Самая популярная версия — бухгалтерская. Убытки записывали красными чернилами, а прибыль — чёрными. В этот день магазины наконец выходили из «красной зоны» в «чёрную». Мы тоже решили сменить цвет — для корпоративного обучения. Часто компании смотрят на корпоративные цены и переносят развитие команды на следующий квартал. Нам это не нравится. Поэтому на «Чёрную пятницу» открываем к…

custom 54454035263709929375custom 52805035140810429653🔥1

11 Nov 2026, 13:44 UTC≈1,780 views3 reactionsread 12 November 2026
Photo

Кто учит нейросеть самостоятельно распознавать объекты, анализировать тексты и генерировать контент? Этим занимаются инженеры глубокого обучения, и в karpovꓸcourses можно освоить эту профессию. Сейчас — со скидкой 30% по промокоду BFDL30. На курсе «Deep Learning Engineer (Инженер глубокого обучения)» вам помогут разобраться в устройстве нейросетей, научиться создавать и обучать модели, а затем выбрать специализацию…

❤2custom 54454035263709929371

10 Nov 2026, 13:29 UTC≈1,980 views3 reactionsread 12 November 2026

Войти в IT через ML Начните учиться хоть завтра, сэкономьте 25% на обучении и получите возможность устроиться в MAGNIT TECH на позицию инженера машинного обучения. Как вам такой план на ноябрь? Все абсолютно реально: скидка Чёрной пятницы действует по промокоду BF25, курс можно начать проходить сразу после оплаты, а возможность принять участие в программе ускоренного трудоустройства MAGNIT TECH после обучения есть …

❤2custom 54454035263709929371

10 Nov 2026, 13:29 UTC≈1,550 views11 reactionsread 12 November 2026
Forwarded from @pioner_notes_dsVideo

Пробы на SMM в karpov.courses 👍 Сегодня будет необычный пост. Не рекламный, а скорее рекомендация для тех, кто уже в профессии или хотел бы попасть в IT через ML Многие сейчас говорят, что IT-пузырь почти лопнул и всех заменит LLM. Но чтобы управлять искусственным интеллектом, нужен свой естественный. Поэтому стоит иметь экспертизу, чтобы тебя не заменили. Плюс вайбкодеры могут легко скопировать сайт или приложение…

👍7🔥3😱1

10 Nov 2026, 13:29 UTC≈1,710 viewsread 12 November 2026

А у нас — свежий отзыв о курсе «Продвинутое машинное обучение» И не просто емкое «спасибо за знания», а целый обзор, да еще и с визуализацией! Разумеется, мы не могли не поделиться с вами таким подробным отчетом — вдруг это вдохновит и вас начать осваивать новую профессию и/или навыки в karpovꓸcourses.

9 Nov 2026, 15:21 UTC≈2,310 views11 reactionsread 12 November 2026
Photo

У нас это впервые! Чёрные пятницы в karpovꓸcourses бывали и раньше, а вот скидок на курс «ML Design: Основы проектирования систем машинного обучения и ИИ-систем» с Валерием Бабушкиным еще не было. С 9 по 16 ноября воспользуйтесь промокодом BFML20, чтобы получить скидку 20%, и приходите осваивать работу с системами машинного обучения на продвинутом уровне. Курс рассчитан на опытных ML-инженеров, руководителей техни…

❤5🔥4custom 54454035263709929372

8 Nov 2026, 13:56 UTC≈2,400 views6 reactionsread 12 November 2026
Photo

Чего ждать студенту-аналитику, когда курс окончен и пора искать работу? Приходите на вебинар, вместе с экспертами разберем путь новичка в реалиях 2026 года. Джунов без опыта не берут: как начинающему аналитику прокачать навыки до первой работы Поговорим о том, какой опыт засчитывают работодатели и разберем три задачи из «Симулятора аналитика»: ✔️ Хватит ли недели на A/B-тест ✔️ Оценка эффекта маркетинговой акции ✔️…

❤5custom 54454035263709929371

7 Nov 2026, 15:08 UTC≈2,550 views4 reactionsread 12 November 2026
Video

Умеете строить пайплайны, а хочется влиять на архитектуру целиком? Вас поняли! Пора перейти на уровень middle/senior – научиться проектировать и развивать сложные платформы данных. Собрали под эту задачу нужное комбо — «Инженер данных» + «Системный дизайн». Забирайте, пока идет Чёрная пятница и действует скидка 25%. Промокод — BF25. 1️⃣ Инженер данных Чтобы углубить навыки работы с Big Data, хранилищами, витринами,…

❤2🔥1custom 54454035263709929371

7 Nov 2026, 11:01 UTC≈2,430 views25 reactionsread 12 November 2026
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Всем привет! На связи Анатолий Карпов 👋🏻 Сегодня выступаю на Higgsfield Data Day в Алматы — расскажу, как симулировать A/B-тесты: от Монте-Карло до синтетических пользователей. Мой доклад — в 15:30 по МСК (17:30 по Алматы). Трансляция уже идёт, смотреть можно здесь. Ещё выступают Валерий Бабушкин, Игорь Котенков («Сиолошная»), Ануар Аймолдин (DSMLꓸKZ) и команда Higgsfield. Запись останется по той же ссылке ✅

❤20🔥5

6 Nov 2026, 15:28 UTC≈2,720 views5 reactionsread 12 November 2026
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Решать простые задачи с помощью ИИ все равно что заказывать такси, чтобы добраться до соседнего подъезда. Как выбрать задачу для автоматизации, разбираем в карточках. Больше прикладных советов и навыков — на курсе «Нейросети для работы». Сейчас на обучение действует скидка 30% в честь Чёрной пятницы🔥 Получить скидку можно по промокоду BFAI30. После программы вы сможете: ✔️ Разбираться в особенностях нейросетей: Dee…

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5 Nov 2026, 14:37 UTC≈2,760 views12 reactionsread 12 November 2026
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Два дня, 100+ докладов и тысячи возможностей для нетворкинга Все это ждет вас на Матемаркетинге — технической конференции для аналитиков, маркетологов и продакт-менеджеров. Своим опытом работы с ИИ-решениями поделятся эксперты крупных компаний: VK, Avito Tech, Сбера, Т-Банка, Magnit Tech и других. Организатор конференции разыгрывает 5 билетов на Матемаркетинг среди студентов и выпускников karpovꓸcourses. Как приня…

❤8custom 54454035263709929372👍1custom 52805035140810429651

Showing the 12 most recent of 127 posts we hold for @KarpovCourses. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.

Posts recorded as deleted after publishing

We recorded 1 post on @KarpovCourses as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.

A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.

First seen missing
1 November 2026
Most recent seen missing
1 November 2026
Median time before seen missing
2 days
Seen missing in the last 30 days
1

Forward network

Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.

Mentions

Named by 8 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.

A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.

Channels Telegram recommends alongside this one

Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.

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Reveal the Data
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#5
Инжиниринг Данных
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LEFT JOIN
@leftjoin · 41,459
#7
Нескучный Data Science
@not_boring_ds · 12,077
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Data Secrets
@data_secrets · 96,159
#9
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#10
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#11
Тагир Анализирует
@tagir_analyzes · 11,641
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Борзило
@y_borzilo · 5,527
#13
Продакт аналитикс
@productanalyticsfordummies · 9,393
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Аналитика и growth mind-set
@analyticsgrowthmindset · 17,392
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Заскуль питона (Аналитика данных)
@zasql_python · 8,985
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Datalytics
@datalytx · 8,783
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Борис опять
@boris_again · 17,955
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Yandex for ML
@yandexforml · 19,155
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Kantor.AI
@kantor_ai · 12,217
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Machinelearning
@ai_machinelearning_big_data · 275,659
#22
Аналитика данных / Data Study
@data_study · 9,414
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РИСЕРЧОШНАЯ
@researchoshnaya · 2,464
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ANDRON ALEXANYAN
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Avito Data Tech
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Я твой продукт анализировал
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Reliable ML
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@Lady_Analyst · 2,241
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Denis Sexy IT 🤖
@denissexy · 140,845
#40
Data Coffee
@datacoffee · 2,636
#41
Мир аналитика данных
@analysts_world · 4,593
#42
Data Secrets | Карьера
@data_secrets_career · 7,412
#43
This is Data
@thisisdata · 6,163
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Аналитик сюра
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Математика Дата саентиста
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LEFT JOIN Insider
@leftjoin_insider · 1,423
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Симулейтив
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#57
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#60
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@datafest · 8,857
#61
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@data_hr · 11,171
#62
Data Science Jobs
@datascienceml_jobs · 21,640
#63
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#65
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#66
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#70
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#71
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@nastengraph · 28,082
#72
ODS #jobs
@odsjobs · 14,599
#73
эйай ньюз
@ai_newz · 98,339
#74
Крис про аналитику🧠🦾
@kris_the_analyst · 4,449
#75
Job for Analysts & Data Scientists
@foranalysts · 37,857
#76
Dev & ML Connectable Jobs
@dev_connectablejobs · 29,105
#77
Data jobs feed
@datajobschannel · 12,646
#78
New Yorko Times
@new_yorko_times · 10,720
#79
Анализ данных (Data analysis)
@data_analysis_ml · 51,973
#80
Поступашки - ШАД, Стажировки и Магистратура
@postypashki_old · 47,200
#81
Noukash
@noukashblog · 21,576
#82
from:adam
@c3po_notes · 6,861
#83
Это считается
@eto_schitaetsya · 4,282
#84
Техножрица 👩‍💻👩‍🏫👩‍🔧
@tech_priestess · 15,143
#85
Connectable Jobs
@zarubezhom_jobs · 106,423
#86
Записки Ппилифа
@ppilif_chanel · 4,483
#87
Дашбордец
@dashboardets · 8,799
#88
kyrillic
@kyrillic · 61,233
#89
Дудь
@yurydud · 849,220
#90
Вадим Новосёлов | Карьера и удалёнка в IT
@gernar228 · 5,694
#91
Young&&Yandex
@Young_and_Yandex · 113,002
#92
Чартомойка
@chartomojka · 14,786
#93
Канал Алексея Куличевского
@kulichevskiy · 3,419
#94
Не AБы какие тесты
@abba_testing · 1,816
#95
Медуза — LIVE
@meduzalive · 1,116,618
#96

Read from Telegram’s recommendation API, most recently 10 September 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.

Appears in Telegram’s recommendations for other channels

The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.

Reveal the Data
@revealthedata · 27,662
Telegram ranks this channel #13 of 96 here — alongside 95 others — read 10 September 2026
Клуб анонимных аналитиков
@analyst_club · 33,307
Telegram ranks this channel #13 of 96 here — alongside 95 others — read 4 September 2026
LEFT JOIN
@leftjoin · 41,459
Telegram ranks this channel #20 of 95 here — alongside 94 others — read 29 August 2026
Инжиниринг Данных
@rockyourdata · 23,679
Telegram ranks this channel #24 of 93 here — alongside 92 others — read 17 September 2026
Время Валеры
@cryptovalerii · 32,080
Telegram ranks this channel #25 of 94 here — alongside 93 others — read 6 September 2026
Data Science Jobs
@datasciencejobs · 22,587
Telegram ranks this channel #33 of 93 here — alongside 92 others — read 21 September 2026
Job for Analysts & Data Scientists
@foranalysts · 37,857
Telegram ranks this channel #40 of 96 here — alongside 95 others — read 1 September 2026
Поколение Python 🐍
@pygen_ru · 50,348
Telegram ranks this channel #44 of 93 here — alongside 92 others — read 25 August 2026
Яндекс Практикум
@yndx_practicum · 33,857
Telegram ranks this channel #48 of 97 here — alongside 96 others — read 3 September 2026
Data Science. SQL hub
@sqlhub · 36,003
Telegram ranks this channel #56 of 87 here — alongside 86 others — read 2 September 2026
Data Science Jobs
@datascienceml_jobs · 21,640
Telegram ranks this channel #57 of 97 here — alongside 96 others — read 24 September 2026
Stepik – онлайн-курсы
@stepik_courses · 28,865
Telegram ranks this channel #57 of 93 here — alongside 92 others — read 16 September 2026
настенька и графики
@nastengraph · 28,082
Telegram ranks this channel #59 of 94 here — alongside 93 others — read 9 September 2026
Noukash
@noukashblog · 21,576
Telegram ranks this channel #65 of 95 here — alongside 94 others — read 23 September 2026
Yandex for ML
@yandexforml · 19,155
Telegram ranks this channel #67 of 96 here — alongside 95 others — read 4 October 2026
Анализ данных (Data analysis)
@data_analysis_ml · 51,973
Telegram ranks this channel #69 of 93 here — alongside 92 others — read 25 August 2026
Machine learning Interview
@machinelearning_interview · 30,562
Telegram ranks this channel #80 of 98 here — alongside 97 others — read 7 September 2026
Data Science | Machinelearning [ru]
@devsp · 19,651
Telegram ranks this channel #84 of 91 here — alongside 90 others — read 30 September 2026

This channel appears in 18 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.

Cite this entry

A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 9 November 2026 — this entry's latest reading, not the date you are reading this.

“karpov.courses” (@KarpovCourses), 27,313 subscribers as measured 9 November 2026. Telegram Register, tgregister.com/channel/KarpovCourses.

Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.