Programming Resources | Python | Javascript | Artificial Intelligence Updates | Computer Science Courses | AI Books
Everything about programming for beginners * Python programming * Java programming * App development * Machine Learning * Data Science Managed by: @love_data
Show more📈 Analytical overview of Telegram channel Programming Resources | Python | Javascript | Artificial Intelligence Updates | Computer Science Courses | AI Books
Channel Programming Resources | Python | Javascript | Artificial Intelligence Updates | Computer Science Courses | AI Books (@programming_guide) in the English language segment is an active participant. Currently, the community unites 56 107 subscribers, ranking 2 375 in the Technologies & Applications category and 6 527 in the India region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 56 107 subscribers.
According to the latest data from 09 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 105 over the last 30 days and by 12 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 2.63%. Within the first 24 hours after publication, content typically collects 0.84% reactions from the total number of subscribers.
- Post reach: On average, each post receives 1 473 views. Within the first day, a publication typically gains 470 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 3.
- Thematic interests: Content is focused on key topics such as algorithm, structure, stack, javascript, programming.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“Everything about programming for beginners
* Python programming
* Java programming
* App development
* Machine Learning
* Data Science
Managed by: @love_data”
Thanks to the high frequency of updates (latest data received on 10 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 Technologies & Applications category.
*args, *kwargs, lambda, map/filter/reduce
• File read/write, CSV handling
• Modules & imports
💡 *Practice:* Create custom functions, read data files, handle errors
🔹 Week 4: Object-Oriented Programming (OOP)
• Classes, objects, inheritance, polymorphism
• Encapsulation & abstraction
• Magic methods (__init__, __str__)
💡 *Practice:* Build a simple class like BankAccount or StudentSystem
🔹 Week 5: Exception Handling & Logging
• try-except-else-finally
• Custom exceptions
• Logging errors & debugging best practices
💡 *Practice:* File operations with proper error handling
🔹 Week 6: Advanced Python Concepts
• Decorators, generators, iterators
• Closures & context managers
• Shallow vs deep copy
💡 *Practice:* Create your own decorator, generator examples
🔹 Week 7: Pandas & NumPy for Data Analysis
• DataFrame basics, filtering & grouping
• Handling missing data
• NumPy arrays, slicing, and aggregation
💡 *Practice:* Analyze small CSV datasets
🔹 Week 8: Python for Analytics & Visualization
• Matplotlib, Seaborn basics
• Data summarization & correlation
• Building simple dashboards
💡 *Practice:* Visualize sales or user data
🔹 Week 9: Real Interview Questions (Intermediate–Advanced)
• 50+ Python interview questions with answers
• Common logical & coding tasks
• Real company-style questions (Infosys, TCS, Deloitte, etc.)
💡 *Practice:* Solve daily problem sets
🔹 Week 10: Final Interview Prep (Mock & Revision)
• End-to-end mock interviews
• Python project discussion tips
• Resume & GitHub portfolio guidance
📌 Each week includes:
✅ Key Concepts & Examples
✅ Coding Snippets & Practice Tasks
✅ Real Interview Q&A
✅ Mini Quiz & Discussion
👍 React ❤️ if you’re ready to master Python interviews!
👇 You can access it from here: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L/2099<div>, <p>, <h1>) which start on a new line, and inline tags (like <span>, <a>, <img>) which do not start on a new line.
3. What is the difference between HTML elements and tags?
A tag is the markup itself (e.g., <p>), while an element includes the opening tag, content, and closing tag (<p>Content</p>).
4. What are semantic HTML elements?
Semantic elements clearly describe their meaning in a human- and machine-readable way. Examples include <header>, <footer>, <article>, and <section>.
5. What is the purpose of the doctype declaration in HTML?
The <!DOCTYPE html> declaration defines the document type and version of HTML, helping browsers render the page correctly.
6. What are the different ways to include CSS in an HTML page?
CSS can be added via inline styles (style attribute), internal styles (<style> tag inside <head>), or external style sheets linked via <link> tag.
7. What is the difference between an ID and a Class in HTML?
ID is unique within a page and is used to identify a single element, while class can be assigned to multiple elements for styling or scripting.
8. How do you create a hyperlink in HTML?
Using the <a> tag with an href attribute, e.g., <a href="https://example.com">Link</a>.
9. What are HTML forms used for?
Forms collect user input and submit data to a server for processing, with tags like <form>, <input>, <textarea>, <button>, and more.
10. What is the role of the <meta> tag in HTML?
Meta tags provide metadata about the HTML document such as character set, page description, viewport settings, and SEO info.
Double Tap ♥️ For MoreSELECT name, age FROM customers WHERE age > 30;
2️⃣ JOINs
⦁ Combine related tables (INNER JOIN, LEFT JOIN)
SELECT o.id, c.name FROM orders o JOIN customers c ON o.customer_id = c.id;
3️⃣ GROUP BY
⦁ Aggregate data by groups
SELECT country, COUNT(*) FROM users GROUP BY country;
4️⃣ ORDER BY
⦁ Sort results ascending or descending
SELECT name, score FROM students ORDER BY score DESC;
5️⃣ Aggregation Functions
⦁ COUNT(), SUM(), AVG(), MIN(), MAX()
SELECT AVG(salary) FROM employees;
6️⃣ ROW_NUMBER()
⦁ Rank rows within partitions
SELECT name,
ROW_NUMBER() OVER (PARTITION BY department ORDER BY salary DESC) AS rank
FROM employees;
💡 Final Tip:
Master these basics well, practice hands-on, and build up confidence!
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