Available now! Telegram Research 2025 โ the year's key insights 
Coding Projects
Open in Telegram
Channel specialized for advanced concepts and projects to master: * Python programming * Web development * Java programming * Artificial Intelligence * Machine Learning Managed by: @love_data
Show more๐ Analytical overview of Telegram channel Coding Projects
Channel Coding Projects (@programming_experts) in the English language segment is an active participant. Currently, the community unites 65 997 subscribers, ranking 1 980 in the Technologies & Applications category and 5 218 in the India region.
๐ Audience metrics and dynamics
Since its creation on ะฝะตะฒัะดะพะผะพ, the project has demonstrated rapid growth, gathering an audience of 65 997 subscribers.
According to the latest data from 11 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 716 over the last 30 days and by 20 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 4.00%. Within the first 24 hours after publication, content typically collects 1.25% reactions from the total number of subscribers.
- Post reach: On average, each post receives 2 637 views. Within the first day, a publication typically gains 823 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 9.
- Thematic interests: Content is focused on key topics such as |--, algorithm, array, framework, javascript.
๐ Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
โChannel specialized for advanced concepts and projects to master:
* Python programming
* Web development
* Java programming
* Artificial Intelligence
* Machine Learning
Managed by: @love_dataโ
Thanks to the high frequency of updates (latest data received on 12 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.
65 997
Subscribers
+2024 hours
+1347 days
+71630 days
Posts Archive
65 997
๐ฃ๐ฟ๐ฒ๐บ๐ถ๐๐บ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ผ๐๐ฟ๐๐ฒ๐ | Microsoft & AWS included๐
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Oldest Programming Languages Still in Use Today ๐ฐ๏ธ
๐ Fortran (1957) โ Still used in scientific computing
๐ค Lisp (1958) โ Powering AI since the start
๐ผ COBOL (1959) โ Running banks & ATMs
๐ฅ C (1972) โ The godfather of modern languages
๐ฃ Prolog (1972) โ Logic programming OG
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65 997
Roadmap to become a Programmer:
๐ Learn Programming Fundamentals (Logic, Syntax, Flow)
โ๐ Choose a Language (Python / Java / C++)
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โ๐ Learn Problem Solving (LeetCode / HackerRank)
โ๐ Learn OOPs & Design Patterns
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โ๐ Work on Real-World Projects
โ๐ Contribute to Open Source
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Apply for Job / Internship
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65 997
The key to starting your coding career:
โIt's not your degree
โIt's not your job experience
It's how you apply these principles:
1. Learn by building real projects
2. Create a portfolio that shows your skills
3. Share your work and connect with others
No one starts a coding expert, but everyone can become one.
If you're looking for a career in coding, start by:
โถ Watching tutorials
โถ Reading developer blogs
โถ Doing internships or freelance gigs
โถ Building projects (even small ones!)
โถ Learning from senior developers
You'll be amazed at how fast youโll grow and how quickly youโll feel confident writing code.
So, start today and let your coding journey begin!
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65 997
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10 GitHub Repositories for Python Projects
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โฃ Bonus content and exercises from Real Python tutorials.
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โฃ Project-based learning with AI/ML tutorials included.
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๐น Awesome Jupyter: Notebooks, Libraries & More
โฃ Boost your Jupyter Notebook skills and workflow.
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๐น Python Mini-Projects for Quick Wins
โฃ Fun mini-games and small apps for fast practice.
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๐น 100 Practical Python Projects Challenge
โฃ Track your progress across 100 real Python projects.
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๐น Data Science Projects for Python Enthusiasts
โฃ Beginner-friendly data science project ideas.
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๐น Showcase of Awesome Python Projects
โฃ Collection of cool Python projects with guides.
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๐น Python Script Projects from Beginner to Advanced
โฃ Step-by-step script projects for all levels.
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If you want to Excel at using the most used database language in the world, learn these powerful SQL features:
โข Wildcards (%, _) โ Flexible pattern matching
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โข Pivot & Unpivot โ Transform row data into columns
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When to Use Which Programming Language?
C โ OS Development, Embedded Systems, Game Engines
C++ โ Game Dev, High-Performance Apps, Finance
Java โ Enterprise Apps, Android, Backend
C# โ Unity Games, Windows Apps
Python โ AI/ML, Data, Automation, Web Dev
JavaScript โ Frontend, Full-Stack, Web Games
Golang โ Cloud Services, APIs, Networking
Swift โ iOS/macOS Apps
Kotlin โ Android, Backend
PHP โ Web Dev (WordPress, Laravel)
Ruby โ Web Dev (Rails), Prototypes
Rust โ System Apps, Blockchain, HPC
Lua โ Game Scripting (Roblox, WoW)
R โ Stats, Data Science, Bioinformatics
SQL โ Data Analysis, DB Management
TypeScript โ Scalable Web Apps
Node.js โ Backend, Real-Time Apps
React โ Modern Web UIs
Vue โ Lightweight SPAs
Django โ AI/ML Backend, Web Dev
Laravel โ Full-Stack PHP
Blazor โ Web with .NET
Spring Boot โ Microservices, Java Enterprise
Ruby on Rails โ MVPs, Startups
HTML/CSS โ UI/UX, Web Design
Git โ Version Control
Linux โ Server, Security, DevOps
DevOps โ Infra Automation, CI/CD
CI/CD โ Testing + Deployment
Docker โ Containerization
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Microservices โ Scalable Backends
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๐๐ฒ๐ฎ๐ฟ๐ป ๐๐ผ๐ฑ๐ถ๐ป๐ด & ๐๐ฒ๐ ๐ฃ๐น๐ฎ๐ฐ๐ฒ๐ฑ ๐๐ป ๐ง๐ผ๐ฝ ๐ ๐ก๐๐
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15 Coding Project Ideas ๐
Beginner Level:
1. ๐๏ธ File Organizer Script
2. ๐งพ Expense Tracker (CLI or GUI)
3. ๐ Password Generator
4. ๐
Simple Calendar App
5. ๐น๏ธ Number Guessing Game
Intermediate Level:
6. ๐ฐ News Aggregator using API
7. ๐ง Email Sender App
8. ๐ณ๏ธ Polling/Voting System
9. ๐งโ๐ Student Management System
10. ๐ท๏ธ URL Shortener
Advanced Level:
11. ๐ฃ๏ธ Real-Time Chat App (with backend)
12. ๐ฆ Inventory Management System
13. ๐ฆ Budgeting App with Charts
14. ๐ฅ Appointment Booking System
15. ๐ง AI-powered Text Summarizer
Credits: https://whatsapp.com/channel/0029VazkxJ62UPB7OQhBE502
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65 997
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Here's a concise cheat sheet to help you get started with Python for Data Analytics. This guide covers essential libraries and functions that you'll frequently use.
1. Python Basics
- Variables:
x = 10
y = "Hello"
- Data Types:
- Integers: x = 10
- Floats: y = 3.14
- Strings: name = "Alice"
- Lists: my_list = [1, 2, 3]
- Dictionaries: my_dict = {"key": "value"}
- Tuples: my_tuple = (1, 2, 3)
- Control Structures:
- if, elif, else statements
- Loops:
for i in range(5):
print(i)
while x < 5:
print(x)
x += 1
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
arr = np.array([1, 2, 3, 4])
arr.sum()
arr.mean()
arr.reshape((2, 2))
arr[0:2] # First two elements
df = pd.DataFrame({
'col1': [1, 2, 3],
'col2': ['A', 'B', 'C']
})
df = pd.read_csv('file.csv')
df.head() # First 5 rows
df.describe() # Summary statistics
df.info() # DataFrame info
df['col1']
df[['col1', 'col2']]
df[df['col1'] > 2]
df.dropna() # Drop missing values
df.fillna(0) # Replace missing values
df.groupby('col2').mean()
plt.plot(df['col1'], df['col2'])
plt.xlabel('X-axis')
plt.ylabel('Y-axis')
plt.title('Title')
plt.show()
sns.histplot(df['col1'])
sns.boxplot(x='col1', y='col2', data=df)
pd.merge(df1, df2, on='key')
df.pivot_table(index='col1', columns='col2', values='col3')
df['col1'].apply(lambda x: x*2)
df['col1'].mean()
df['col1'].median()
df['col1'].std()
df.corr()
