Available now! Telegram Research 2025 โ the year's key insights 
Programming Resources | Python | Javascript | Artificial Intelligence Updates | Computer Science Courses | AI Books
Open in Telegram
Everything about programming for beginners * Python programming * Java programming * App development * Machine Learning * Data Science Managed by: @love_data
Show more๐ 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 56 118 subscribers, ranking 2 374 in the Technologies & Applications category and 6 527 in the India region.
๐ Audience metrics and dynamics
Since its creation on ะฝะตะฒัะดะพะผะพ, the project has demonstrated rapid growth, gathering an audience of 56 118 subscribers.
According to the latest data from 10 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 89 over the last 30 days and by 1 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 2.65%. Within the first 24 hours after publication, content typically collects 0.87% reactions from the total number of subscribers.
- Post reach: On average, each post receives 1 485 views. Within the first day, a publication typically gains 488 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 algorithm, structure, stack, javascript, programming.
๐ Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
โEverything about programming for beginners
* Python programming
* Java programming
* App development
* Machine Learning
* Data Science
Managed by: @love_dataโ
Thanks to the high frequency of updates (latest data received on 11 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.
56 118
Subscribers
+124 hours
+317 days
+8930 days
Posts Archive
+8
๐ 8 Super useful HTML tips & tricks that every Developer should know about
Repost from Artificial Intelligence
๐ฒ ๐๐ฟ๐ฒ๐ฒ ๐๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐ง๐ผ ๐จ๐ฝ๐๐ธ๐ถ๐น๐น ๐๐ป ๐ฎ๐ฌ๐ฎ๐ฑ๐
Whether youโre a student, aspiring data analyst, software enthusiast, or just curious about AI, nowโs the perfect time to dive in.
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Learning DSA wasnโt just about acing interviews, --- it was about thinking better, building faster, and debugging smarter.
๐ฏ ๐๐ฒ๐ฟ๐ฒ ๐ฎ๐ฟ๐ฒ ๐๐ต๐ฒ ๐ต ๐ฐ๐ผ๐ฟ๐ฒ ๐ฝ๐ฎ๐๐๐ฒ๐ฟ๐ป๐ ๐๐ต๐ฎ๐ ๐๐ฟ๐ฎ๐ป๐๐ณ๐ผ๐ฟ๐บ๐ฒ๐ฑ ๐ต๐ผ๐ ๐ ๐๐ผ๐น๐๐ฒ ๐ฝ๐ฟ๐ผ๐ฏ๐น๐ฒ๐บ๐:
โข Sliding Windows
โข Two Pointers
โข Stack Based Patterns
โข Dynamic Programing
โข BFS/DFS (Trees & Graphs)
โข Merge Intervals
โข Backtracking & Subsets
โข top-k Elements (Heaps)
โข Greedy Techniques
๐ค๏ธ ๐ ๐ ๐ฃ๐ฎ๐๐ต ๐๐ผ ๐ ๐ฎ๐๐๐ฒ๐ฟ๐ถ๐ป๐ด ๐๐ฆ๐:
โข Started with basic problems on arrays & strings
โข Solved 1-2 problems a day, consistently for 3 months
โข Focused more on patterns than individual questions
โข Made my own notes, revisited problems I struggled with
โข Used visual tools to understand recursion & DP
โข Practiced explaining my solutions out loud (like system design reviews)
โข Applied patterns in real-world projects (DevOps automation, log parsing, infra tools)
๐ก ๐๐ผ๐ผ๐ธ๐ถ๐ป๐ด ๐ฏ๐ฎ๐ฐ๐ธ, ๐ผ๐ป๐ฒ ๐๐ต๐ถ๐ป๐ด ๐ถ๐ ๐ฐ๐น๐ฒ๐ฎ๐ฟ:
> It's not how many problems you solve, it's how well you can recognize the pattern hiding in each one.
๐ ๐ถ๐ฐ๐ฟ๐ผ๐๐ผ๐ณ๐ ๐๐ฅ๐๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ผ๐๐ฟ๐๐ฒ๐๐
Whether youโre a student, fresher, or professional looking to upskill โ Microsoft has dropped a series of completely free courses to get you started.
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JavaScript (JS) roadmap:
1. Basic Fundamentals:
- Variables, data types, and operators.
- Control structures like loops and conditionals.
- Functions and scope.
2. DOM Manipulation:
- Access and modify HTML and CSS using JavaScript.
- Event handling.
3. Asynchronous Programming:
- Promises and async/await for handling asynchronous operations.
4. ES6 and Modern JavaScript:
- Arrow functions, template literals, and destructuring.
- Modules for code organization.
- Classes for object-oriented programming.
5. Popular Libraries and Frameworks:
- Learn libraries like jQuery or frameworks like React, Angular, or Vue depending on your project needs.
6. Package Management:
- Tools like npm or yarn for managing dependencies.
7. Build Tools:
- Webpack, Babel, and other tools for bundling and transpiling.
8. API Interaction:
- Fetch or Axios for making API requests.
9. State Management (For Frameworks):
- Redux for React, Vuex for Vue, etc.
10. Testing:
- Learn testing frameworks like Jest.
11. Version Control:
- Git for code versioning and collaboration.
12. Continuous Integration (CI) and Deployment:
- Travis CI, Jenkins, or others for automating testing and deployment.
13. Server-Side JavaScript (Optional):
- Node.js for server-side development.
14. Advanced Topics (Optional):
- WebSockets, WebRTC, Progressive Web Apps (PWAs), and more.
This roadmap covers the foundational knowledge and key steps in a JavaScript developer's journey. You can explore more deeply into areas that align with your specific goals and projects.
How to stay motivated while learning to code:
๐ฏ Set small, achievable goals each week
โ
Celebrate every tiny win โ progress is progress
๐งฑ Build projects you're actually excited about
๐ฅ Join communities or study groups for support
โ๏ธ Keep a coding journal to track your growth
๐ Mix learning with building โ apply what you learn
๐ฎ Turn coding into a game with challenges (like LeetCode, HackerRank)
๐ง Avoid burnout โ take breaks when needed
๐ Remind yourself why you started โ purpose fuels progress
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Repost from Data Analyst Jobs
๐ง๐ผ๐ฝ ๐๐ฅ๐๐ ๐ฉ๐ถ๐ฟ๐๐๐ฎ๐น ๐๐ป๐๐ฒ๐ฟ๐ป๐๐ต๐ถ๐ฝ๐ ๐๐ผ ๐ฆ๐๐ฎ๐ฟ๐ ๐ง๐ผ๐ฑ๐ฎ๐๐
1. Introduction to Data Science
2. PwC Digital Intelligence
3. BCG Generative AI
4. Data Analytics
๐๐ถ๐ป๐ธ:-๐
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Enroll For FREE & Get Certified ๐
Complete Python Roadmap ๐๐
1. Introduction to Python
- Definition
- Purpose
- Python Installation
- Interpreter vs Compiler
2. Basic Python Syntax
- Print Statement
- Variables and Data Types
- Input and Output
- Operators
3. Control Flow
- Conditional Statements (if, elif, else)
- Loops (for, while)
- Break and Continue Statements
4. Data Structures
- Lists
- Tuples
- Sets
- Dictionaries
5. Functions
- Function Definition
- Parameters and Return Values
- Lambda Functions
6. File Handling
- Reading from and Writing to Files
- Handling Exceptions
7. Modules and Packages
- Importing Modules
- Creating Packages
8. Object-Oriented Programming (OOP)
- Classes and Objects
- Inheritance
- Polymorphism
- Encapsulation
- Abstraction
9. Error Handling
- Try, Except Blocks
- Custom Exceptions
10. Advanced Data Structures
- List Comprehensions
- Generators
- Collections Module
11. Decorators and Generators
- Function Decorators
- Generator Functions
12. Working with APIs
- Making HTTP Requests
- JSON Handling
13. Database Interaction with Python
- Connecting to Databases
- CRUD Operations
14. Web Development with Flask/Django
- Flask/Django Setup
- Routing and Templates
15. Asynchronous Programming
- Async/Await
- Asyncio Library
16. Testing in Python
- Unit Testing
- Testing Frameworks (e.g., pytest)
17. Pythonic Code
- PEP 8 Style Guide
- Code Readability
18. Version Control (Git)
- Basic Commands
- Collaborative Development
19. Data Science Libraries
- NumPy
- Pandas
- Matplotlib
20. Machine Learning Basics
- Scikit-Learn
- Model Training and Evaluation
21. Web Scraping
- BeautifulSoup
- Scrapy
22. RESTful API Development
- Flask/Django Rest Framework
23. CI/CD Basics
- Continuous Integration
- Continuous Deployment
24. Deployment
- Deploying Python Applications
- Hosting Platforms (e.g., Heroku)
25. Security Best Practices
- Input Validation
- Handling Sensitive Data
26. Code Documentation
- Docstrings
- Generating Documentation
27. Community and Collaboration
- Open Source Contributions
- Forums and Conferences
Resources to Learn Python:
1. Free Course
- https://www.freecodecamp.org/learn/data-analysis-with-python/
2. Projects
- t.me/pythonfreebootcamp/177
- t.me/pythonspecialist/90
3. Books & Notes
- https://t.me/dsabooks/99
- https://t.me/dsabooks/101
4. Python Interview Preparation
- https://t.me/PythonInterviews
- t.me/DataAnalystInterview/63
Join @free4unow_backup for more Python resources.
Like this post if you want more content like this ๐โค๏ธ
ENJOY LEARNING ๐๐
๐ ๐ฎ๐๐๐ฒ๐ฟ ๐ฆ๐ค๐ ๐ถ๐ป ๐ฏ๐ฌ ๐๐ฎ๐๐ ๐๐ถ๐๐ต ๐ง๐ต๐ฒ๐๐ฒ ๐ญ๐ฌ๐ฌ% ๐๐ฟ๐ฒ๐ฒ ๐ฅ๐ฒ๐๐ผ๐๐ฟ๐ฐ๐ฒ๐๐
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Use cases of top programming languages
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ENJOY LEARNING ๐๐
Java Basics every beginner should learn to build a strong foundation:
1. Hello World & Setup
Install JDK and an IDE (like IntelliJ or Eclipse)
Write your first program: public class HelloWorld
2. Data Types & Variables
Primitive types: int, double, char, boolean
Non-primitive types: String, Arrays, Objects
Type casting (implicit & explicit)
3. Operators
Arithmetic: + - * / %
Comparison: == != > < >= <=
Logical: && || !
4. Control Flow
If, else if, else
Switch-case
Loops: for, while, do-while
break and continue
5. Functions (Methods)
Syntax: public static returnType methodName(params)
Method overloading
Return types & parameter passing
6. Object-Oriented Programming (OOP)
Classes & Objects
this keyword
Constructors (default & parameterized)
7. OOP Concepts
Encapsulation (private variables + getters/setters)
Inheritance (extends keyword)
Polymorphism (method overriding)
Abstraction (abstract classes & interfaces)
8. Arrays & ArrayList
Declaring and iterating arrays
ArrayList methods: add, remove, get, size
Multidimensional arrays
9. Exception Handling
Try-catch-finally blocks
throw and throws
Custom exceptions
10. Basic Input/Output
Scanner class for user input
System.out.println() for output
Free Java Resources: https://whatsapp.com/channel/0029VamdH5mHAdNMHMSBwg1s
ENJOY LEARNING ๐๐
Learn Python in 45 Days ๐
Python Interview Questions ๐
HTML cheatsheet๐ฅ๐...
Repost from Data Analytics
๐ ๐ฎ๐๐๐ฒ๐ฟ ๐ง๐ต๐ฒ๐๐ฒ ๐ฏ ๐๐๐๐ฒ๐ป๐๐ถ๐ฎ๐น ๐ฆ๐ธ๐ถ๐น๐น๐ ๐๐ผ ๐๐ฎ๐ป๐ฑ ๐ฎ ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐ ๐๐ผ๐ฏ ๐ถ๐ป ๐ฎ๐ฌ๐ฎ๐ฑ๐
If youโre serious about becoming a Data Analyst in 2025, you need more than just basic theory๐จโ๐ป
You must master skills that recruiters actually look for โ skills that make you job-ready, confident, and in-demand๐ฅ
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All you need is dedication, practice, and the right resources โ and Iโve got you covered!โ
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