Available now! Telegram Research 2025 โ the year's key insights 
Coding Free Books | Python | AI
Open in Telegram
Best Channel for Programmers and Hackers All in one channel to learn ๐ 1. Python 2. Ethical Hacking 3. Java 4. App development 5. Machine learning 6. Data structures 7. Algorithms Promotions: @coderfun
Show more๐ Analytical overview of Telegram channel Coding Free Books | Python | AI
Channel Coding Free Books | Python | AI (@codingwithsagar) in the English language segment is an active participant. Currently, the community unites 30 894 subscribers, ranking 6 259 in the Education category and 13 672 in the India region.
๐ Audience metrics and dynamics
Since its creation on ะฝะตะฒัะดะพะผะพ, the project has demonstrated rapid growth, gathering an audience of 30 894 subscribers.
According to the latest data from 19 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 156 over the last 30 days and by -11 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 3.63%. Within the first 24 hours after publication, content typically collects N/A% reactions from the total number of subscribers.
- Post reach: On average, each post receives 1 120 views. Within the first day, a publication typically gains 0 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 4.
- Thematic interests: Content is focused on key topics such as learning, link:-, css, algorithm, sql.
๐ Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
โBest Channel for Programmers and Hackers
All in one channel to learn
๐
1. Python
2. Ethical Hacking
3. Java
4. App development
5. Machine learning
6. Data structures
7. Algorithms
Promotions: @coderfunโ
Thanks to the high frequency of updates (latest data received on 20 June, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Education category.
30 894
Subscribers
-1124 hours
+337 days
+15630 days
Posts Archive
Repost from AI Prompts | ChatGPT | Google Gemini | Claude
๐๐ฟ๐ฒ๐ฒ ๐ฃ๐๐๐ต๐ผ๐ป ๐๐ผ๐๐ฟ๐๐ฒ: ๐ง๐ต๐ฒ ๐๐ฒ๐๐ ๐ฆ๐๐ฎ๐ฟ๐๐ถ๐ป๐ด ๐ฃ๐ผ๐ถ๐ป๐ ๐ณ๐ผ๐ฟ ๐ง๐ฒ๐ฐ๐ต & ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐ถ๐ฐ๐ ๐๐ฒ๐ด๐ถ๐ป๐ป๐ฒ๐ฟ๐๐
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Repost from Python for Data Analysts
๐ญ๐ฌ๐ฌ๐ฌ+ ๐๐ฟ๐ฒ๐ฒ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฒ๐ฑ ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐ฏ๐ ๐๐ป๐ณ๐ผ๐๐๐ โ ๐๐ฒ๐ฎ๐ฟ๐ป, ๐๐ฟ๐ผ๐, ๐ฆ๐๐ฐ๐ฐ๐ฒ๐ฒ๐ฑ!๐
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Repost from AI Prompts | ChatGPT | Google Gemini | Claude
๐ฐ ๐๐ถ๐ด๐ต-๐๐บ๐ฝ๐ฎ๐ฐ๐ ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐ถ๐ฐ๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป๐ ๐๐ผ ๐๐ฎ๐๐ป๐ฐ๐ต ๐ฌ๐ผ๐๐ฟ ๐๐ฎ๐ฟ๐ฒ๐ฒ๐ฟ ๐ถ๐ป ๐ฎ๐ฌ๐ฎ๐ฑ๐
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If you want to Excel in Data Science and become an expert, master these essential concepts:
Core Data Science Skills:
โข Python for Data Science โ Pandas, NumPy, Matplotlib, Seaborn
โข SQL for Data Extraction โ SELECT, JOIN, GROUP BY, CTEs, Window Functions
โข Data Cleaning & Preprocessing โ Handling missing data, outliers, duplicates
โข Exploratory Data Analysis (EDA) โ Visualizing data trends
Machine Learning (ML):
โข Supervised Learning โ Linear Regression, Decision Trees, Random Forest
โข Unsupervised Learning โ Clustering, PCA, Anomaly Detection
โข Model Evaluation โ Cross-validation, Confusion Matrix, ROC-AUC
โข Hyperparameter Tuning โ Grid Search, Random Search
Deep Learning (DL):
โข Neural Networks โ TensorFlow, PyTorch, Keras
โข CNNs & RNNs โ Image & sequential data processing
โข Transformers & LLMs โ GPT, BERT, Stable Diffusion
Big Data & Cloud Computing:
โข Hadoop & Spark โ Handling large datasets
โข AWS, GCP, Azure โ Cloud-based data science solutions
โข MLOps โ Deploy models using Flask, FastAPI, Docker
Statistics & Mathematics for Data Science:
โข Probability & Hypothesis Testing โ P-values, T-tests, Chi-square
โข Linear Algebra & Calculus โ Matrices, Vectors, Derivatives
โข Time Series Analysis โ ARIMA, Prophet, LSTMs
Real-World Applications:
โข Recommendation Systems โ Personalized AI suggestions
โข NLP (Natural Language Processing) โ Sentiment Analysis, Chatbots
โข AI-Powered Business Insights โ Data-driven decision-making
Like this post if you need a complete tutorial on essential data science topics! ๐โค๏ธ
Join our WhatsApp channel: https://whatsapp.com/channel/0029Va8v3eo1NCrQfGMseL2D
Repost from AI Prompts | ChatGPT | Google Gemini | Claude
๐ณ ๐๐ฟ๐ฒ๐ฒ ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐๐ผ ๐จ๐ฝ๐ด๐ฟ๐ฎ๐ฑ๐ฒ ๐ฌ๐ผ๐๐ฟ ๐ฅ๐ฒ๐๐๐บ๐ฒ ๐ถ๐ป ๐ฎ๐ฌ๐ฎ๐ฑ ๐ฎ๐ป๐ฑ ๐ฆ๐๐ฎ๐ป๐ฑ ๐ข๐๐๐
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Moving Login Button Project (Troll Form ๐)
If the user enters an incorrect password, the "Login" button moves away!
<html>
<head>
<style>
.container {
text-align: center;
margin-top: 50px;
}
.btn {
position: relative;
padding: 10px 20px;
font-size: 16px;
cursor: pointer;
}
</style>
<script>
function moveButton() {
let password = document.getElementById("password").value;
let button = document.getElementById("btn");
if (password !== "legend") {
let x = Math.random() * (window.innerWidth - 100);
let y = Math.random() * (window.innerHeight - 100);
button.style.position = "absolute";
button.style.left = x + "px";
button.style.top = y + "px";
}
}
</script>
</head>
<body>
<div class="container">
<h2>Enter Password</h2>
<input type="password" id="password" placeholder="Type something..." oninput="moveButton()">
<br><br>
<button id="btn" class="btn" onclick="alert('You got lucky!')">Login</button>
</div>
</body>
</html>
How It Works?
If the user types anything other than "legend", the login button starts running away from the cursor.
If the correct password is entered, the button stays in place.
Web Development Best Resources
ENJOY LEARNING ๐๐
#webdev
Repost from Python for Data Analysts
๐๐ฒ๐ฎ๐ฟ๐ป ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ ๐ณ๐ผ๐ฟ ๐๐ฅ๐๐ ๐๐ถ๐๐ต ๐๐ฎ๐ฟ๐๐ฎ๐ฟ๐ฑ ๐จ๐ป๐ถ๐๐ฒ๐ฟ๐๐ถ๐๐๐
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Repost from AI Prompts | ChatGPT | Google Gemini | Claude
๐ฒ ๐๐ฅ๐๐ ๐ข๐ป๐น๐ถ๐ป๐ฒ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป๐ ๐ง๐ผ ๐๐ต๐ฎ๐ป๐ด๐ฒ ๐ฌ๐ผ๐๐ฟ ๐๐ฎ๐ฟ๐ฒ๐ฒ๐ฟ ๐๐ป ๐ฎ๐ฌ๐ฎ๐ฑ ๐
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Repost from Web Development
๐ญ๐ฌ๐ฌ% ๐๐ฅ๐๐ ๐ฆ๐๐ฒ๐ฝ ๐๐ ๐ฆ๐๐ฒ๐ฝ ๐ฒ-๐ ๐ผ๐ป๐๐ต ๐๐๐น๐น ๐ฆ๐๐ฎ๐ฐ๐ธ ๐๐ฒ๐๐ฒ๐น๐ผ๐ฝ๐ฒ๐ฟ ๐ฅ๐ผ๐ฎ๐ฑ๐บ๐ฎ๐ฝ๐
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Pro Serverless Data Handling with Microsoft Azure
Benjamin Kettner, 2022
Repost from AI Prompts | ChatGPT | Google Gemini | Claude
๐ฑ ๐๐ฅ๐๐ ๐ ๐๐ง ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐๐ผ ๐๐ฒ๐ฎ๐ฟ๐ป ๐ง๐ฒ๐ฐ๐ต, ๐๐ & ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ๐
Dreaming of an MIT education without the tuition fees? ๐ฏ
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Your gateway to a smarter careerโ
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Steps to learn Data Structures and Algorithms (DSA) with Python
1. Learn Python: If you're not already familiar with Python, start by learning the basics of the language. There are many online resources and tutorials available for free.
2. Understand the Basics: Before diving into DSA, make sure you have a good grasp of Python's syntax, data types, and basic programming concepts. Use free resources from @dsabooks to help you in learning journey.
3. Pick Good Learning Resources: Choose a good book, online course, or tutorial series on DSA with Python. Most of the free stuff is already posted on the channel @crackingthecodinginterview
4. Data Structures: Begin with fundamental data structures like lists, arrays, stacks, queues, linked lists, trees, graphs, and hash tables. Understand their properties, operations, and when to use them.
5. Algorithms: Study common algorithms such as searching (binary search, linear search), sorting (quick sort, merge sort), and dynamic programming. Learn about their time and space complexity.
6. Practice: The key to mastering DSA is practice. Solve a wide variety of problems to apply your knowledge. Websites like LeetCode and HackerRank provide a vast collection of problems.
7. Analyze Complexity: Learn how to analyze the time and space complexity of algorithms. Big O notation is a crucial concept in DSA.
8. Implement Algorithms: Implement algorithms and data structures from scratch in Python. This hands-on experience will deepen your understanding.
9. Project Work: Apply DSA to real projects. This could be building a simple game, a small web app, or any software that requires efficient data handling. Check channel @programming_experts if you need project ideas.
10. Seek Help and Collaborate: Don't hesitate to ask for help when you're stuck. Engage in coding communities, forums, or collaborate with others to gain new insights.
11. Review and Revise: Periodically review what you've learned. Reinforce your understanding by revisiting data structures and algorithms you've studied.
12. Competitive Programming: Participate in competitive programming contests. They are a great way to test your skills and improve your problem-solving abilities.
13. Stay Updated: DSA is an ever-evolving field. Stay updated with the latest trends and algorithms.
14. Contribute to Open Source: Consider contributing to open source projects. It's a great way to apply your knowledge and work on real-world code.
15. Teach Others: Teaching what you've learned to others can deepen your understanding. You can create tutorials or mentor someone.
Join @free4unow_backup for more free courses
ENJOY LEARNING ๐๐
Repost from AI Prompts | ChatGPT | Google Gemini | Claude
๐ ๐ฎ๐๐๐ฒ๐ฟ ๐ฃ๐ฟ๐ผ๐บ๐ฝ๐ ๐๐ป๐ด๐ถ๐ป๐ฒ๐ฒ๐ฟ๐ถ๐ป๐ด ๐ณ๐ผ๐ฟ ๐๐ฟ๐ฒ๐ฒ ๐ถ๐ป ๐ฎ๐ฌ๐ฎ๐ฑ!๐
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Repost from AI Prompts | ChatGPT | Google Gemini | Claude
๐ฆ๐ค๐ ๐ญ๐ฌ๐ฌ% ๐๐ฅ๐๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐
Looking to master SQL for Data Analytics or prep for your dream tech job? ๐ผ
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Importance of AI in Data Analytics
AI is transforming the way data is analyzed and insights are generated. Here's how AI adds value in data analytics:
1. Automated Data Cleaning
AI helps in detecting anomalies, missing values, and outliers automatically, improving data quality and saving analysts hours of manual work.
2. Faster & Smarter Decision Making
AI models can process massive datasets in seconds and suggest actionable insights, enabling real-time decision-making.
3. Predictive Analytics
AI enables forecasting future trends and behaviors using machine learning models (e.g., sales predictions, churn forecasting).
4. Natural Language Processing (NLP)
AI can analyze unstructured data like reviews, feedback, or comments using sentiment analysis, keyword extraction, and topic modeling.
5. Pattern Recognition
AI uncovers hidden patterns, correlations, and clusters in data that traditional analysis may miss.
6. Personalization & Recommendation
AI algorithms power recommendation systems (like on Netflix, Amazon) that personalize user experiences based on behavioral data.
7. Data Visualization Enhancement
AI auto-generates dashboards, chooses best chart types, and highlights key anomalies or insights without manual intervention.
8. Fraud Detection & Risk Analysis
AI models detect fraud and mitigate risks in real-time using anomaly detection and classification techniques.
9. Chatbots & Virtual Analysts
AI-powered tools like ChatGPT allow users to interact with data using natural language, removing the need for technical skills.
10. Operational Efficiency
AI automates repetitive tasks like report generation, data transformation, and alertsโfreeing analysts to focus on strategy.
Share with credits: https://t.me/sqlspecialist
Hope it helps :)
#dataanalytics
Repost from AI Prompts | ChatGPT | Google Gemini | Claude
๐ญ๐ฌ๐ฌ% ๐๐ฅ๐๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ผ๐๐ฟ๐๐ฒ๐๐
๐ฆ๐ค๐:- https://pdlink.in/3TcvfsA
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Repost from AI Prompts | ChatGPT | Google Gemini | Claude
๐ฒ ๐๐ฅ๐๐ ๐๐ถ๐๐ฐ๐ผ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐๐๐ถ๐น๐ฑ ๐ฎ ๐ง๐ฒ๐ฐ๐ต ๐๐ฎ๐ฟ๐ฒ๐ฒ๐ฟ !๐
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Repost from Web Development
๐๐ฒ๐ฐ๐ผ๐บ๐ฒ ๐ฎ ๐ช๐ฒ๐ฏ ๐๐ฒ๐๐ฒ๐น๐ผ๐ฝ๐ฒ๐ฟ ๐ณ๐ผ๐ฟ ๐๐ฅ๐๐ โ ๐ก๐ผ ๐๐ฒ๐ด๐ฟ๐ฒ๐ฒ ๐ก๐ฒ๐ฒ๐ฑ๐ฒ๐ฑ!๐
You donโt need a degree or pay lakhs to start a career in web development! ๐ธโ
These 100% free courses by Udacity are beginner-friendly and cover everything from frontend to backend๐จโ๐ป๐
๐๐ข๐ง๐ค๐:-
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๐ Save this post & tag a friend whoโs ready to switch to tech!
