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 12 September 2026 and assigned it the closest of 31 fixed categories, at 99% 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
24 measurements spanning 92 days, net +640. 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 6,990–8,132 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 24
Measured (UTC)
Subscribers
Change
7 Nov 2026, 13:26
7,965
-13
4 Nov 2026, 05:08
7,978
-16
1 Nov 2026, 05:19
7,994
-6
29 Oct 2026, 01:09
8,000
+58
26 Oct 2026, 00:41
7,942
+36
22 Oct 2026, 21:21
7,906
+108
19 Oct 2026, 17:48
7,798
+21
16 Oct 2026, 17:50
7,777
+38
14 Oct 2026, 00:07
7,739
+109
9 Oct 2026, 02:39
7,630
+97
2 Oct 2026, 16:38
7,533
+411
16 Sept 2026, 12:00
7,122
-23
12 Sept 2026, 14:41
7,145
-19
8 Sept 2026, 19:59
7,164
-40
3 Sept 2026, 06:37
7,204
-10
30 Aug 2026, 20:57
7,214
-18
28 Aug 2026, 02:54
7,232
-2
24 Aug 2026, 21:35
7,234
-13
21 Aug 2026, 02:53
7,247
-22
17 Aug 2026, 18:56
7,269
first reading
Engagement
19 posts held, back to 20 May 2023 — the reader has reached the start of this channel’s public history, so this is the full archive Telegram still exposes. Read across 30 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
25.8%
avg views ÷ 7,965 subscribers
Avg views / post
2,060
5 posts measured
Reaction rate
0.321%
reactions ÷ views · ER floor
Posts in window
5
of 19 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.
What these figures were computed from
Window
Rolling 30 days · latest post in window 2 November 2026
Posts held
19 (20 May 2023 – 2 November 2026)
Views total
10,280
Reactions total
33
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
10 Nov 2026, 13:10 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
16
Videos
1
Links
14
Lifetime counters from Telegram’s own channel header, read 10 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
Video runtime
51s
Average length
51s
Measured directly from 1 video 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
132 reactions across 17 posts, in 8 distinct kinds. The most used accounts for 71.2% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
94
71.2%
👎
10
7.58%
😁
8
6.06%
🥰
8
6.06%
🍌
6
4.55%
👍
3
2.27%
👏
2
1.52%
🔥
1
0.758%
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 17 of the 19 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 132 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 19 most recent posts we hold, published 20 May 2023 to 2 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: 2 of 5 posts held from the last 30 days (40.0%) 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).
ℹ️ از تصویرسازی تا فیلمسازی؛ مسیر حرفهای خلق محتوا با هوش مصنوعی 👾
🧠سرفصلهای دوره جامع هوش مصنوعی Online AI ✔️
👤مدرس: جواد نبوی⭐️
🔖سر فصل های دوره ⬇️
🚀 دوره جامع هوش مصنوعی | Online AI
✨ 1. معرفی ابزارها و تکنیکهای مختلف هوش مصنوعی 🛠️
آشنایی با ابزارها و روشهای کاربردی هوش مصنوعی
✍🏻 2. اصول پرامپتنویسی 🧠
یادگیری نحوه نوشتن دستورات حرفهای برای گرفتن بهترین خروجی از هوش مصنوعی❗️
🖼️ 3. ساخت تصاویر و تیزره…
ویدئوسازی با هوش مصنوعی و NFP
مدرس : الوانا
🔖 سرفصلهای دوره⬇️
۱۱ موضوع آموزشی
1️⃣ انتخاب موضوع برای پیج یا کانال
2️⃣ طراحی هوک و ساختار ویدئو
3️⃣ راهاندازی NFP در Claude
4️⃣ ساخت ریلز با NFP
5️⃣ انتخاب سبک بصری برای ویدئو
6️⃣ تدوین و افزودن موسیقی و افکت صوتی
7️⃣ ویدئوسازی با Seedance
8️⃣ تولید ویدئو با Omni
9️⃣ اجرای پروژه انیمیشن
🔟 اجرای پروژه ویدئوی سینمایی
1️⃣1️⃣ سناریونویسی با هوش مصنوعی
🔖مهارتهایی که یاد م…
🎥 دو دوره کاربردی برای ورود جدی به دنیای یوتیوب🎥
🎬پک دوره های احسان رضایی ✌️
1️⃣ یوتیوبر هوشمند؛ هوش مصنوعی برای تولید محتوای یوتیوب
2️⃣یوتیوببیزنس؛ آموزش راهاندازی کسبوکار یوتیوب
🔖توضیحات دوره یوتویوب هوشمند⬇️
تولید ویدیو چند کار جدا داره: ایده، متن، تصویر و آمادهسازی برای انتشار. این آموزش ابزارهای هوش مصنوعی رو تو همین مسیر معرفی میکنه؛ از ایدهپردازی و اسکریپت تا تبدیل متن به تصویر، صدا و ویدیو، ساخت شورت…
🎯 یک مهارت جدید یاد بگیر؛ از ساخت چتبات تا اتوماسیون کسبوکار!
🤖 دوره متخصص اتوماسیون با هوش مصنوعی و n8n 👇
👑مدرس : سونلرن
🧩
🕰 بیش از 15 ساعت و 8 پروژه عملی ⭐️
📌 پیشنیاز: فقط لپتاپ و اینترنت؛ دانش برنامهنویسی لازم نیست.
🔖این دوره چیا یاد میده ⬇️
این دوره یاد میده با n8n و هوش مصنوعی، اتوماسیونها و ایجنتهای واقعی بسازی؛ از چتبات و تولید محتوا تا پردازش ایمیل، اتصال APIها، RAG و استقرار روی سرور. تمرکز ا…
💣دیگه فقط کاربر AI نباش؛ سازنده سیستمهای هوشمند باش🤷♂️
🤖اتوپایلوت؛ اتوماسیون و ایجنت هوش مصنوعی ✈
👑مدرس🔤 مهدی فولادوند ➡️
🔖سرفصلهای دوره ⬇️
⚡️ پرامپتنویسی و ساخت اصولی AI Agent 🔥
⚡️ اتصال مدلهای زبانی مختلف و کاهش هزینه API🐺
⚡️ اتصال ایجنتها به دیتابیس و مدیریت اطلاعات😂
⚡️ ساخت چتبات واتساپ، تلگرام و بله
⚡️ وباسکرپینگ و استخراج اطلاعات از سایتها
⚡️ ساخت ایجنت صوتی و سیستم رزرو جلسه
⚡️ اتوماسیون …
👑 دورهای برای کسانی که میخواهند معمولی زندگی نکنند🔴
⭐️ دوره استاندارد ثروت
👩🏫 مدرس شقایق کافکا
👑اینجا یاد میگیری چطور استانداردهای خودت رو بالا ببری، تصمیمهای بهتری بگیری و پایههای لازم برای ساخت یک کسبوکار و زندگی موفق رو بسازی. 🔥
🔖داخل دوره چیا یاد میگیرین ⬇️
🧠 هویت و استانداردهای شخصی
⚙️ انضباط، تصمیمگیری و مسئولیتپذیری
🎩 پرستیژ و تصویر شخصی
🚀 جاهطلبی و وسعت خواستهها
❤️ ساخت کسبو…
از تصویر تا ویدیو؛ مسیر حرفهای ساخت محتوای AI 🤷♂️
🤖 دوره استیبل دیفیوژن و ComfyUI 🧠
👨🏫 مدرس 🔤علیرضا یزدانی
🔖 سرفصلهای دوره ⬇️
👈 مقدمه و معرفی دوره
فصل 1: معرفی امکانات و موارد پایه👋
فصل 2: توضیحات کامل img2img💝
فصل 3: افزونه های پرکاربرد😘
فصل 4: ComfyUi👍
فصل 5: آپدیت🐺
فصل 6: مدل های FLUX😂
فصل 7: SD.Forge👻
فصل 8: بررسی کامل مدل ها🫰
فصل 9: ChatGPT💀
فصل 10: ساخت ویدیو با مدل LTX🐺
فصل 11: Flux Kontext🌹
فصل 12: …
🐞دوره انیمیکس
📖 مدرس حسین ملک زاده
🔖 سرفصلهای دوره جامع انیمیکس⬇️
1️⃣ پرامپتنویسی حرفهای ✍️
یادگیری نحوه گرفتن بهترین خروجی از هوش مصنوعی
2️⃣ شناخت ابزارهای هوش مصنوعی 🤖
کار با ChatGPT، Gemini، Claude، Grok، Flow، Seedance و ابزارهای AI
3️⃣ ساخت عکس با هوش مصنوعی 🎨
ساخت تصویر، استایل اختصاصی، کاراکتر، Character Sheet و Storyboard
4️⃣ ساخت ویدیو با هوش مصنوعی 🎬
از ایده و سناریو تا تولید، صداگذاری، دیالوگ و ادی…
💎 پایان ادیت های آماتور ! شروع ادیت های حرفه ای ‼️
🧔 دوره جامع الایت موشن | Advanced Alight Motion
👑 مدرس🔤 آرمان هاشمی 🔴
از آموزش کامل ابزارهای الایت موشن تا اجرای ادیتهای حرفهای و ترند؛ همهچیز در یک دوره کاربردی و پروژهمحور 🔘
🔖سر فصل های دوره ⬇️
🥹 دوره جامع و پروژهمحور Alight Motion
🔹 صفر تا صد Alight Motion و ابزارها
آشنایی کامل با محیط برنامه، ابزارها، تنظیمات و تکنیکهای کاربردی برای شروع ادیت حرفهای.
…
🖱 با هوش مصنوعی کار نکن؛ کاری کن هوش مصنوعی برایت کار کند. 🧠
🤖 دوره سفر با هوش مصنوعی
👑مدرس عرفان فرنود
قیمت در سایت 8.900
🔖این دوره بدرد چه کسانی میخوره ⬇️
✅ اگه صاحب کسبوکاری و میخوای کارهات رو هوشمندتر کنی و زمان بیشتری ذخیره کنی.
✅ اگه تولیدکننده محتوا، ادمین، مارکتر یا فعال فضای دیجیتال هستی و میخوای با AI چند برابر حرفهایتر کار کنی.
✅ اگه دنبال یادگیری یک مهارت جدید و درآمدزا برای آینده هستی.
✅ …
❤️ ساخت امپراطوری محتوا در تلگرام، بله و روبیکا💙
🔫دوره استراتژی رشد کانال: از خلق مزیت رقابتی تا سناریونویسی محتوا و ... 🧑💻
👑از استاد مهدی میرزایی ➡️
🌐توضیحات دوره در سایتℹ️
🔖 سرفصلهای دوره ⬇️
1️⃣. تعیین سفر مشتری 🎯
🔹 طراحی مسیر رشد رسانه
🔹 نمونه رشد رسانه تخصصی با Social IMC
🔹 تعیین موضوع رسانه و شناخت انواع رسانهها
🔹 طراحی سفر مشتری با مثال واقعی
2️⃣. ایجاد مزیت رقابتی برای رسانه 💎
🔹 شناخت مشکلات رایج ک…
❤9
Showing the 12 most recent of 19 posts we hold for @inesta_dore_vip. 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 edited after publishing
@inesta_dore_vip edited 3 posts after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
First edit seen
18 August 2026
Most recent edit
6 November 2026
Posts recorded as deleted after publishing
We recorded 1 post on @inesta_dore_vip 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
3 November 2026
Most recent seen missing
3 November 2026
Median time before seen missing
4 months
Seen missing in the last 30 days
1
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
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 1 registered channel — 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.
Named by
Channels on the register whose posts name this channel's handle.
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.
Handles this channel named that no longer answer
Dead references
1
handles named in this channel’s posts, vacant today
Evidenced gone
0
we ourselves saw one of these resolve, at some point
Never seen alive
1
vacant every time we have ever looked
@inesta_dore_vip named 1 handle that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@admin named in 4 posts, 4 November 2026 – 7 November 2026
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 7 November 2026 — this
entry's latest reading, not the date you are reading this.
“اینستا دوره VIP” (@inesta_dore_vip), 7,965 subscribers as measured 7 November 2026. Telegram Register, tgregister.com/channel/inesta_dore_vip.
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.