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Channel

Free Courses with Certificate - Python Programming, Data Science, Java Coding, SQL, Web Development, AI, ML, ChatGPT Expert

@free4unow_backup

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

74,744subscribers

-203 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 31,623–100,000.

Register entry

Telegram ID-1001277667926
TypeChannel
Username@free4unow_backup
DescriptionWe provide unlimited Free Courses with Certificate to learn Python, Data Science, Java, Web development, AI, ML, Finance, Hacking, Marketing and many more from top websites. For promotions: @love_data
CreatedBetween 1 March 2018 and 31 July 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live19 September 2026
Measurements held33
Confirmed unchanged1 time, most recently 19 September 2026
On Telegramt.me/free4unow_backup

Topic

Education — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 20 August 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 why it has no browse page of its own yet.

Growth

74,71274,99174,851.56 August 2026 — 74,947 subscribers6 August 2026 — 74,947 subscribers7 August 2026 — 74,952 subscribers8 August 2026 — 74,939 subscribers10 August 2026 — 74,924 subscribers11 August 2026 — 74,933 subscribers12 August 2026 — 74,934 subscribers13 August 2026 — 74,989 subscribers14 August 2026 — 74,991 subscribers16 August 2026 — 74,961 subscribers17 August 2026 — 74,949 subscribers18 August 2026 — 74,957 subscribers19 August 2026 — 74,950 subscribers20 August 2026 — 74,945 subscribers22 August 2026 — 74,943 subscribers24 August 2026 — 74,914 subscribers25 August 2026 — 74,891 subscribers26 August 2026 — 74,877 subscribers27 August 2026 — 74,862 subscribers28 August 2026 — 74,844 subscribers29 August 2026 — 74,830 subscribers30 August 2026 — 74,832 subscribers31 August 2026 — 74,831 subscribers1 September 2026 — 74,826 subscribers2 September 2026 — 74,821 subscribers3 September 2026 — 74,813 subscribers5 September 2026 — 74,788 subscribers9 September 2026 — 74,732 subscribers11 September 2026 — 74,712 subscribers13 September 2026 — 74,736 subscribers15 September 2026 — 74,789 subscribers17 September 2026 — 74,766 subscribers19 September 2026 — 74,744 subscribers74,7446 August 202619 September 2026
33 measurements spanning 44 days, net -203. 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 74,670–75,033 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 33
Measured (UTC)SubscribersChange
19 Sept 2026, 09:5874,744-22
17 Sept 2026, 00:3774,766-23
15 Sept 2026, 02:0174,789+53
13 Sept 2026, 13:1974,736+24
11 Sept 2026, 16:0174,712-20
9 Sept 2026, 05:0074,732-56
5 Sept 2026, 21:3774,788-25
3 Sept 2026, 19:5674,813-8
2 Sept 2026, 10:1774,821-5
1 Sept 2026, 13:3374,826-5
31 Aug 2026, 11:1874,831-1
30 Aug 2026, 09:0374,832+2
29 Aug 2026, 10:5674,830-14
28 Aug 2026, 07:3674,844-18
27 Aug 2026, 06:1474,862-15
26 Aug 2026, 07:5474,877-14
25 Aug 2026, 04:2174,891-23
24 Aug 2026, 00:1874,914-29
22 Aug 2026, 05:4374,943-2
20 Aug 2026, 19:2274,945first reading

Engagement

23 posts held, back to 17 April 2025 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 100 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
3.42%
avg views ÷ 74,744 subscribers
Avg views / post
2,550
3 posts measured
Reaction rate
0.783%
reactions ÷ views · ER floor
Posts in window
3
of 23 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
WindowRolling 30 days · latest post in window 23 September 2026
Posts held23 (17 April 2025 – 23 September 2026)
Views total7,660
Reactions total60
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken24 Sept 2026, 12:53 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
Videos
1
Links
294

Lifetime counters from Telegram’s own channel header, read 24 September 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
30s
Average length
30s

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

1,318 reactions across 23 posts, in 11 distinct kinds. The most used accounts for 80.2% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤1,05780.2%
👍15111.5%
🔥322.43%
👏211.59%
😁181.37%
🥰90.683%
🤣80.607%
🤩80.607%
🫡70.531%
🥱50.379%
🤝20.152%

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 23 of the 23 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 1,318 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 23 most recent posts we hold, published 17 April 2025 to 23 September 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

23 Sept 2026, 18:02 UTC≈1,050 views18 reactionsread 24 September 2026

🔥 FREE Resources to Learn Generative AI 🤖 🔹 Generative AI – Google 👉 https://www.cloudskillsboost.google/paths/118 🔹 Generative AI for Everyone – DeepLearning.AI 👉 https://www.deeplearning.ai/courses/generative-ai-for-everyone/ 🔹 LLM Course – Hugging Face 👉 https://huggingface.co/learn/llm-course 🔹 Microsoft Generative AI 👉 https://learn.microsoft.com/en-us/training/generative-ai/ 🔹 Generative AI Learning Path –…

❤17🔥1

22 Sept 2026, 15:44 UTC≈2,000 views9 reactionsread 24 September 2026
Video

GigaChat 3.5 Reasoning is a new open-source LLM designed to reason before generating responses. The model breaks problems into stages, builds execution plans, checks intermediate results, and self-corrects when needed. Built on GigaChat 3.5 Ultra, it was trained on math and coding tasks using multiple step-by-step reasoning paths. An automated verification step reinforces the paths that lead to correct answers, enab…

❤7👍2

15 Sept 2026, 11:00 UTC≈4,610 views33 reactionsread 24 September 2026

🔥 FREE Resources to Learn AI 🤖 🔹 Agentic AI – DeepLearning.AI 👉 https://www.deeplearning.ai/courses/agentic-ai 🔹 Google Machine Learning – ML & GenAI 👉 https://developers.google.com/machine-learning 🔹 Hugging Face Learn – LLMs, NLP & AI Agents 👉 https://huggingface.co/learn 🔹 Kaggle Learn – ML, GenAI & Data Science 👉 https://www.kaggle.com/learn 🔹 fast.ai – Practical Deep Learning 👉 https://course.fast.ai/ 🔹 MI…

❤23🔥4👍2👏2🥰2

20 May 2026, 15:19 UTC≈23,000 views111 reactionsread 24 September 2026

FREE Resources to Learn Machine Learning 🔥 * Python – python.org/doc * Math & Stats – khanacademy.org/math * ML Crash Course – developers.google.com/machine‑learning/crash‑course * Scikit‑learn – https://scikit-learn.org/ * Pandas – pandas.pydata.org/docs * Matplotlib – matplotlib.org * Seaborn – seaborn.pydata.org * Kaggle Learn (ML) – https://www.kaggle.com/learn/intro-to-machine-learning * Google ML Guides – deve…

❤100👍9😁2

15 Dec 2025, 08:05 UTC≈45,900 views271 reactionsread 24 September 2026

✅ Top Tech Career Paths to Explore in 2026 💻🚀 1. Software Developer Builds websites, apps, and systems. Needs skills in JavaScript, Python, Java, or C#. Frontend, backend, or full-stack. 2. Cloud Engineer Works with AWS, Azure, or GCP to manage scalable cloud infrastructure, services, and deployments. 3. DevOps Engineer Bridges development and operations. Manages CI/CD, automation, monitoring, and infrast…

❤243👍14🔥9🥱3🥰2

28 Nov 2025, 13:15 UTC≈41,100 views102 reactionsread 24 September 2026

Machine Learning Roadmap | |-- Fundamentals | |-- Mathematics | | |-- Linear Algebra | | |-- Calculus | | |-- Probability | | |-- Statistics | | | |-- Programming | | |-- Python | | | |-- NumPy | | | |-- Pandas | | | |-- Matplotlib | | |-- R | |-- Data Handling | |-- Data Collection | | |-- APIs | | |-- Web Scraping | | |-- SQL Databases | | | |-- Data…

❤90👏5👍4🔥1🤩1😁1

23 Nov 2025, 05:40 UTC≈26,000 views69 reactionsread 24 September 2026

Important Topics You Should Know to Learn Web Development: 👉 Beginner Topics HTML • Structure of a web page (doctype, html, head, body) • Headings, paragraphs, lists, links, images • Forms and input elements • Semantic tags (header, footer, article, section) CSS • Selectors, classes, IDs • Box model (margin, border, padding, content) • Flexbox and Grid layout • Colors, fonts, backgrounds • Pseudo-classes and pseud…

❤62👏2🥰2🫡2👍1

22 Nov 2025, 12:01 UTC≈18,700 views48 reactionsread 24 September 2026

SQL Detailed Roadmap | | | |-- Fundamentals | |-- Introduction to Databases | | |-- What SQL does | | |-- Relational model | | |-- Tables, rows, columns | |-- Keys and Constraints | | |-- Primary keys | | |-- Foreign keys | | |-- Unique and check constraints | |-- Normalization | | |-- 1NF, 2NF, 3NF | | |-- ER diagrams | | |-- Core SQL | |-- SQL Basics | | |-- SELECT, WHERE, ORDER BY | | |-- GROUP BY and HAVING | | …

❤42🤩3👏2🥰1

20 Nov 2025, 10:18 UTC≈14,400 views33 reactionsread 24 September 2026

Artificial Intelligence Roadmap | |-- Core Foundations | |-- Mathematics | | |-- Linear Algebra | | |-- Calculus | | |-- Probability | | |-- Statistics | | | |-- Programming | | |-- Python | | | |-- NumPy | | | |-- Pandas | | | |-- Matplotlib | | |-- R | | |-- SQL | |-- Classical AI | |-- Search Algorithms | | |-- BFS | | |-- DFS | | |-- A* | | | |…

❤30👍1👏1🫡1

19 Nov 2025, 16:04 UTC≈12,800 views35 reactionsread 24 September 2026

Data Science Roadmap | |-- Core Foundations | |-- Mathematics | | |-- Linear Algebra | | |-- Calculus Basics | | |-- Probability | | |-- Statistics | | | |-- Programming | | |-- Python | | | |-- NumPy | | | |-- Pandas | | | |-- Matplotlib | | | |-- Seaborn | | |-- R | | |-- SQL | |-- Data Handling | |-- Data Collection | | |-- APIs | | |-- Web Scrapi…

❤28👍4🤩2👏1

16 Nov 2025, 07:04 UTC≈15,900 views43 reactionsread 24 September 2026

Web Development Roadmap | |-- Core Basics | |-- How the Web Works | | |-- Client Server | | |-- HTTP | | |-- DNS | | | |-- Internet Basics | | |-- Browsers | | |-- Developer Tools | | |-- Debugging | |-- Frontend | |-- HTML | | |-- Tags | | |-- Forms | | |-- Semantics | | | |-- CSS | | |-- Selectors | | |-- Flexbox | | |-- Grid | | |-- Responsive Design …

❤32🫡4🥰2👍1👏1🤝1🤩1😁1

12 Oct 2025, 09:32 UTC≈22,400 views56 reactionsread 24 September 2026

Data Analytics Roadmap | |-- Fundamentals | |-- Mathematics | | |-- Descriptive Statistics | | |-- Inferential Statistics | | |-- Probability Theory | | | |-- Programming | | |-- Python (Focus on Libraries like Pandas, NumPy) | | |-- R (For Statistical Analysis) | | |-- SQL (For Data Extraction) | |-- Data Collection and Storage | |-- Data Sources | | |-- APIs | | |-- Web Scrap…

❤44👍5🔥3👏2😁2

Showing the 12 most recent of 23 posts we hold for @free4unow_backup. 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.

Mentions

Named by 18 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.

Named by

Channels on the register whose posts name this channel's handle.

Free Online Courses with Certificate | Udacity Free Courses | Eduonix | IP Cybersecurity | Coursera | Premium Certified Courses
@udacityfreecourse · 46,786
22 posts
Google Jobs - FAANG Companies • Facebook • Microsoft • Amazon • Netflix • Apple
@FAANGJob · 26,871
14 posts
Python Projects & Free Books
@pythonfreebootcamp · 40,776
14 posts
Coding & AI Resources
@leadcoding · 35,447
10 posts
Best AI Tools | ChatGPT | Perplexity | Deepseek | Artificial Intelligence
@AI_Best_Tools · 58,470
8 posts
Data Analytics & AI | SQL Interviews | Power BI Resources
@Data_Visual · 27,531
7 posts
Udemy Free Courses | Coding | ChatGPT | AI Crypto | Microsoft Certificate | Artificial Intelligence
@udemy_free_courses_with_certi · 70,746
7 posts
Machine Learning & Artificial Intelligence | Data Science Free Courses
@datasciencefree · 68,356
4 posts
Freelancing Tips: Earn Money Online
@freelancing_upwork · 22,347
4 posts
Python Courses & Resources
@Python53 · 50,715
4 posts
Machine Learning with Python
@CodeProgrammer · 68,301
3 posts
MS Excel for Data Analysis
@excel_analyst · 72,703
3 posts
Programming Resources | Python | Javascript | Artificial Intelligence Updates | Computer Science Courses | AI Books
@programming_guide · 56,038
3 posts
Data Science Projects
@pythonspecialist · 56,284
3 posts
Data Engineers
@sql_engineer · 11,050
3 posts
SQL Programming Resources
@sqlanalyst · 76,675
3 posts
Data Science & Machine Learning
@datasciencefun · 77,458
2 posts
Data Analyst Interview Resources
@dataanalystinterview · 52,595
1 post

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.

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 19 September 2026 — this entry's latest reading, not the date you are reading this.

“Free Courses with Certificate - Python Programming, Data Science, Java Coding, SQL, Web Development, AI, ML, ChatGPT Expert” (@free4unow_backup), 74,744 subscribers as measured 19 September 2026. Telegram Register, tgregister.com/channel/free4unow_backup.

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.