Channel
@free4unow_backup
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
74,949subscribers
+2 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
| Telegram ID | -1001277667926 |
|---|---|
| Type | Channel |
| Username | @free4unow_backup |
| Description | We 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 |
| Created | Between 1 April 2018 and 31 July 2021— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 17 August 2026 |
| Measurements held | 11 |
| Confirmed unchanged | 1 time, most recently 17 August 2026 |
| On Telegram | t.me/free4unow_backup |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 17 Aug 2026, 15:35 | 74,949 | -12 |
| 16 Aug 2026, 08:02 | 74,961 | -30 |
| 14 Aug 2026, 21:45 | 74,991 | +2 |
| 13 Aug 2026, 13:17 | 74,989 | +55 |
| 12 Aug 2026, 10:26 | 74,934 | +1 |
| 11 Aug 2026, 07:21 | 74,933 | +9 |
| 10 Aug 2026, 05:34 | 74,924 | -15 |
| 8 Aug 2026, 05:05 | 74,939 | -13 |
| 7 Aug 2026, 01:55 | 74,952 | +5 |
| 6 Aug 2026, 14:45 | 74,947 | no change |
| 6 Aug 2026, 14:38 | 74,947 | first reading |
20 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 26 pagesof Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 20 May 2026. An engagement rate over an empty window would be a number about nothing.
Lifetime counters from Telegram’s own channel header, read 17 August 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.
1,201 reactions across 20 posts, in 11 distinct kinds. The most used accounts for 79.9% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 959 | 79.9% | |
| 👍 | 144 | 12.0% | |
| 🔥 | 27 | 2.25% | |
| 👏 | 19 | 1.58% | |
| 😁 | 17 | 1.42% | |
| 🤣 | 8 | 0.666% | |
| 🤩 | 7 | 0.583% | |
| 🥰 | 7 | 0.583% | |
| 🫡 | 7 | 0.583% | |
| 🥱 | 4 | 0.333% | |
| 🤝 | 2 | 0.167% |
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 20 of the 20 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 1,201reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 17 April 2025 to 20 May 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.
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…
❤78👍8😁1
✅ 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…
❤234👍14🔥9🥰2🥱2
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…
❤89👏5👍4🔥1😁1
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…
❤54👏2🥰2🫡2
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 | | …
❤39🤩3👏2🥰1
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* | | | |…
❤27👍1👏1🫡1
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…
❤27👍4🤩2👏1
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 …
❤31🫡4🥰2👍1👏1🤝1🤩1😁1
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…
❤43👍4🔥3👏2😁2
30-day Roadmap plan for SQL covers beginner, intermediate, and advanced topics 👇 Week 1: Beginner Level Day 1-3: Introduction and Setup 1. Day 1: Introduction to SQL, its importance, and various database systems. 2. Day 2: Installing a SQL database (e.g., MySQL, PostgreSQL). 3. Day 3: Setting up a sample database and practicing basic commands. Day 4-7: Basic SQL Queries 4. Day 4: SELECT statement, retrieving data …
❤34👍2👏2🤩1
Web Development Mastery: From Basics to Advanced 🚀 Start with the fundamentals: - HTML - CSS - JavaScript - Responsive Design - Basic DOM Manipulation - Git and Version Control You can grasp these essentials in just a week. Once you're comfortable, dive into intermediate topics: - AJAX - APIs - Frameworks like React, Angular, or Vue - Front-end Build Tools (Webpack, Babel) - Back-end basics with Node.js, Express, …
❤18👍2🔥2
Essential Python Libraries to build your career in Data Science 📊👇 1. NumPy: - Efficient numerical operations and array manipulation. 2. Pandas: - Data manipulation and analysis with powerful data structures (DataFrame, Series). 3. Matplotlib: - 2D plotting library for creating visualizations. 4. Seaborn: - Statistical data visualization built on top of Matplotlib. 5. Scikit-learn: - Machine learn…
❤19👍3👏1🔥1
Showing the 12 most recent of 20 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.
Citation-graph rank — 39,255 of 1,481,306entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
Named by 15 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.
Names
Channels on the register whose handles appear in this channel's posts.
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.
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 17 August 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), 74,949 subscribers as measured 17 August 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.