¡Ya disponible! Investigación de Telegram 2025 — los principales insights del año 
Programming Resources | Python | Javascript | Artificial Intelligence Updates | Computer Science Courses | AI Books
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Everything about programming for beginners * Python programming * Java programming * App development * Machine Learning * Data Science Managed by: @love_data
Mostrar más📈 Análisis del canal de Telegram Programming Resources | Python | Javascript | Artificial Intelligence Updates | Computer Science Courses | AI Books
El canal Programming Resources | Python | Javascript | Artificial Intelligence Updates | Computer Science Courses | AI Books (@programming_guide) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 56 097 suscriptores, ocupando la posición 2 379 en la categoría Tecnologías y Aplicaciones y el puesto 6 302 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 56 097 suscriptores.
Según los últimos datos del 23 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 63, y en las últimas 24 horas de -15, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 2.11%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 0.49% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 1 182 visualizaciones. En el primer día suele acumular 273 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 7.
- Intereses temáticos: El contenido se centra en temas clave como algorithm, structure, stack, javascript, programming.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Everything about programming for beginners
* Python programming
* Java programming
* App development
* Machine Learning
* Data Science
Managed by: @love_data”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 24 junio, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.
56 097
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Publicaciones del Canal
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| 4 | Quick Python Cheat Sheet for Beginners 🐍✍️
Python is widely used for data analysis, automation, and AI—perfect for beginners starting their coding journey.
Aggregation Functions 📊
• sum(list) → Adds all values
👉 sum([1,2,3]) = 6
• len(list) → Counts total elements
👉 len([1,2,3]) = 3
• max(list) → Highest value
👉 max([4,7,2]) = 7
• min(list) → Lowest value
👉 min([4,7,2]) = 2
• sum(list)/len(list) → Average
👉 sum([10,20])/2 = 15
Lookup / Searching 🔍
• in → Check existence
👉 5 in [1,2,5] = True
• list.index(value) → Position of value
👉 [10,20,30].index(20) = 1
• Dictionary lookup
👉 data = {"name": "John", "age": 25} data["name"] # John
Logical Operations 🧠
• if condition: → Decision making
👉 if x > 10: print("High") else: print("Low")
• and → All conditions true
• or → Any condition true
• not → Reverse condition
Text (String) Functions 🔤
• len(text) → Length
👉 len("hello") = 5
• text.lower() → Lowercase
• text.upper() → Uppercase
• text.strip() → Remove spaces
👉 " hi ".strip() = "hi"
• text.replace(old, new)
👉 "hi".replace("h","H") = "Hi"
• String concatenation
👉 "Hello " + "World"
Date Time Functions 📅
• from datetime import datetime
• datetime.now() → Current date time
• Extract values:
now = datetime.now() now.year now.month now.day
Math Functions ➗
• import math
• math.sqrt(x) → Square root
• math.ceil(x) → Round up
• math.floor(x) → Round down
• abs(x) → Absolute value
Conditional Aggregation (Like Excel SUMIF) ⚡
• Using list comprehension
nums = [10, 20, 30, 40] sum(x for x in nums if x > 20) # 70
• Count condition
len([x for x in nums if x > 20]) # 2
Pro Tip for Data Analysts 💡
👉 For real-world work, use libraries: pandas & numpy
Example:
import pandas as pd df["salary"].mean()
Python Resources: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L
Double Tap ♥️ For More | 557 |
| 5 |  𝗣𝗮𝘆 𝗔𝗳𝘁𝗲𝗿 𝗣𝗹𝗮𝗰𝗲𝗺𝗲𝗻𝘁 - 𝗙𝘂𝗹𝗹𝘀𝘁𝗮𝗰𝗸𝗗𝗲𝘃 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗪𝗶𝘁𝗵 𝗚𝗲𝗻𝗔𝗜 😍
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Hurry! Limited seats are available.🏃♂️ | 464 |
| 6 | 🔗 9. SQL Joins
Joins combine data from multiple tables. This is one of the most important SQL concepts.
Types of Joins:
✔ INNER JOIN
✔ LEFT JOIN
✔ RIGHT JOIN
✔ FULL JOIN
Example
SELECT Customers.Name, Orders.Order_ID
FROM Customers
INNER JOIN Orders
ON Customers.Customer_ID = Orders.Customer_ID;
⚡ 10. Query Optimization
As databases grow, performance becomes important.
Imagine: 100 Records = Fast, 10 Million Records = Slow
Optimization helps retrieve data efficiently.
Common Optimization Techniques:
✔ Indexing
✔ Proper Joins
✔ Filtering Early
✔ Avoiding Unnecessary Queries
🛠 Databases Every Developer Should Know
🐬 MySQL
Best for: Beginners, Web Applications, Small to Medium Projects
Official Site: MySQL
🐘 PostgreSQL
Best for: Enterprise Applications, Analytics, Complex Systems
Official Site: PostgreSQL
🍃 MongoDB
Best for: Flexible Data Storage, Modern Applications, NoSQL Projects
Official Site: MongoDB
🚀 Beginner Database Projects
Build these projects to strengthen your skills:
✔ Student Management System
✔ Library Management System
✔ Inventory Tracker
✔ Expense Tracker
✔ Employee Database System
✔ E-commerce Database
⚠️ Common Beginner Mistakes
❌ Skipping SQL fundamentals
❌ Learning NoSQL before SQL
❌ Ignoring database design
❌ Not practicing joins
❌ Memorizing queries without understanding
🗺️ Database Learning Roadmap
Week 1 ✔ Tables, Rows & Columns, CRUD Operations
Week 2 ✔ Filtering, Sorting, Aggregations
Week 3 ✔ Joins, Relationships, Primary & Foreign Keys
Week 4 ✔ Indexes, Optimization, Database Design
💡 Why Databases Matter
Almost every software application relies on databases.
Whether you're becoming:
✔ Web Developer
✔ Data Analyst
✔ Data Scientist
✔ Backend Engineer
✔ AI Engineer
Database skills are essential.
👉 Double Tap ❤️ For More | 498 |
| 7 | 🚀 Learn Databases 🗄️💾
Every application stores data.
Think about:
✔ Instagram storing user profiles
✔ Amazon storing product information
✔ Netflix storing movies and subscriptions
✔ Banking applications storing transactions
Where is all this data stored?
👉 In Databases
If programming is the brain of an application, then databases are its memory 🧠💾
🧠 1. What is a Database?
A Database is an organized collection of data that can be stored, managed, and retrieved efficiently.
Without databases:
❌ Data would be lost after closing the application
❌ Searching information would be difficult
❌ Large applications would be impossible to build
🌍 Real-World Examples
Banking System Stores:
✔ Customer Information
✔ Account Details
✔ Transaction History
✔ Loan Information
E-Commerce Website Stores:
✔ Products
✔ Orders
✔ Customers
✔ Payments
Social Media Platform Stores:
✔ Users
✔ Posts
✔ Comments
✔ Messages
📊 2. Types of Databases
There are two major categories:
🗄️ Relational Databases SQL
Data is stored in tables.
Example:
ID Name Age
1 John 25
2 Sarah 30
Popular SQL Databases:
✔ MySQL
✔ PostgreSQL
✔ Microsoft SQL Server
📄 NoSQL Databases
Data is stored in flexible formats.
Example:
{
"name": "John",
"age": 25
}
Popular NoSQL Databases:
✔ MongoDB
✔ Redis
🧠 3. Why Learn SQL?
SQL Structured Query Language is used to communicate with databases.
It is one of the most important skills for:
✔ Developers
✔ Data Analysts
✔ Data Scientists
✔ Backend Engineers
✔ Database Administrators
Many companies ask SQL questions in interviews.
📋 4. CRUD Operations
CRUD stands for:
Operation Meaning
Create Insert Data
Read Retrieve Data
Update Modify Data
Delete Remove Data
These are the most fundamental database operations.
➕ CREATE Insert Data
Example:
INSERT INTO Students VALUES (1, 'John', 22);
Adds a new record.
🔍 READ Retrieve Data
Example:
SELECT _ FROM Students;
Displays all records.
✏️ UPDATE Modify Data
Example:
UPDATE Students SET Age = 23 WHERE ID = 1;
Updates existing information.
❌ DELETE Remove Data
Example:
DELETE FROM Students WHERE ID = 1;
Removes a record.
📊 5. Database Tables
Databases organize information using tables.
Example: Employees Table
Employee_ID Name Department
101 Rahul IT
102 Priya HR
103 Amit Finance
Each row is a record. Each column represents an attribute.
🔗 6. Primary Keys
A Primary Key uniquely identifies each row.
Example:
ID Name
1 Rahul
2 Priya
ID acts as the Primary Key.
Rules:
✔ Unique
✔ Cannot be NULL
🔄 7. Relationships Between Tables
Large databases contain multiple tables. These tables are connected using relationships.
Example
Customers Table
Customer_ID Name
1 Rahul
Orders Table
Order_ID Customer_ID
101 1
Customer_ID connects both tables.
🔍 8. SQL Queries Every Beginner Must Learn
Select Data
SELECT _ FROM Employees;
Filter Data
SELECT _ FROM Employees WHERE Department = 'IT';
Sort Data
SELECT _ FROM Employees ORDER BY Salary DESC;
Count Records
SELECT COUNT(_) FROM Employees;
Group Data
SELECT Department, COUNT(_) FROM Employees GROUP BY Department; | 346 |
| 8 |  𝗔𝗰𝗰𝗲𝗻𝘁𝘂𝗿𝗲 𝗙𝗥𝗘𝗘 𝗩𝗶𝗿𝘁𝘂𝗮𝗹 𝗜𝗻𝘁𝗲𝗿𝗻𝘀𝗵𝗶𝗽 𝗳𝗼𝗿 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝘄𝗶𝘁𝗵 𝗙𝗿𝗲𝗲 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗲 📊
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🔥 Start your Data Analytics journey today and gain valuable virtual internship experience from a top global company. | 399 |
| 9 | COMMON TERMINOLOGIES IN PYTHON - PART 1
Have you ever gotten into a discussion with a programmer before? Did you find some of the Terminologies mentioned strange or you didn't fully understand them?
In this series, we would be looking at the common Terminologies in python.
It is important to know these Terminologies to be able to professionally/properly explain your codes to people and/or to be able to understand what people say in an instant when these codes are mentioned. Below are a few:
IDLE (Integrated Development and Learning Environment) - this is an environment that allows you to easily write Python code. IDLE can be used to execute a single statements and create, modify, and execute Python scripts.
Python Shell - This is the interactive environment that allows you to type in python code and execute them immediately
System Python - This is the version of python that comes with your operating system
Prompt - usually represented by the symbol ">>>" and it simply means that python is waiting for you to give it some instructions
REPL (Read-Evaluate-Print-Loop) - this refers to the sequence of events in your interactive window in form of a loop (python reads the code inputted>the code is evaluated>output is printed)
Argument - this is a value that is passed to a function when called eg print("Hello World")... "Hello World" is the argument that is being passed.
Function - this is a code that takes some input, known as arguments, processes that input and produces an output called a return value. E.g print("Hello World")... print is the function
Return Value - this is the value that a function returns to the calling script or function when it completes its task (in other words, Output). E.g.
>>> print("Hello World")
Hello World
Where Hello World is your return value.
Note: A return value can be any of these variable types: handle, integer, object, or string
Script - This is a file where you store your python code in a text file and execute all of the code with a single command
Script files - this is a file containing a group of python scripts | 442 |
| 10 |  🚀 𝗧𝗼𝗽 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝗬𝗼𝘂 𝗖𝗮𝗻 𝗟𝗲𝗮𝗿𝗻 𝗳𝗼𝗿 𝗙𝗥𝗘𝗘! 💼🔥
These free courses can help you build in-demand tech skills for 2026 👇
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| 11 | ✅ Web development Interview Questions with Answers: Part-1
QUESTION 1
What happens step by step when you enter a URL in a browser and press Enter?
Answer
You trigger a long chain of events.
• Browser parses the URL and identifies protocol, domain, path
• Browser checks cache, DNS cache, OS cache, router cache
• If not found, DNS lookup happens to get the IP address
• Browser opens a TCP connection with the server
• HTTPS triggers TLS handshake for encryption
• Browser sends an HTTP request to the server
• Server processes request and sends HTTP response
• Browser downloads HTML, CSS, JS, images
• HTML parsed into DOM
• CSS parsed into CSSOM
• DOM + CSSOM create render tree
• Layout calculates positions
• Paint draws pixels on screen
• JavaScript executes and updates UI
Interview tip
Mention DNS, TCP, TLS, render tree. This separates juniors from seniors.
QUESTION 2
What are the roles of HTML, CSS, and JavaScript in a web application?
Answer
Each layer has a single responsibility.
HTML
• Structure of the page
• Content and meaning
• Headings, forms, inputs, buttons
CSS
• Presentation and layout
• Colors, fonts, spacing
• Responsive behavior
JavaScript
• Behavior and logic
• Events, API calls, validation
• Dynamic updates
Real example
HTML builds a login form
CSS styles it
JavaScript validates input and sends API request
QUESTION 3
What are the main differences between HTML and HTML5?
Answer
HTML5 added native capabilities.
Key differences
• Semantic tags like header, footer, article
• Audio and video support without plugins
• Canvas and SVG for graphics
• Local storage and session storage
QUESTION 4
What is the difference between block-level and inline elements in HTML?
Answer
Block elements
• Start on a new line
• Take full width
• Respect height and width
• Examples: div, p, h1
Inline elements
• Stay in same line
• Take only content width
• Height and width ignored
• Examples: span, a, strong
Inline-block
• Stays inline
• Respects height and width
QUESTION 5
What is semantic HTML and why is it important for SEO and accessibility?
Answer
Semantic HTML uses meaningful tags.
Examples
• header, nav, main, article, section, footer
Benefits
• Search engines understand content better
• Screen readers read pages correctly
• Code becomes readable and maintainable
SEO example
article tag signals main content to search engines.
Accessibility example
Screen readers jump between landmarks.
QUESTION 6
What are meta tags and how do they impact search engines?
Answer
Meta tags provide page metadata.
Common meta tags
• charset defines encoding
• viewport controls responsiveness
• description influences search snippets
• robots control indexing
SEO impact
• Description affects click-through rate
• Robots tag controls indexing behavior
Note: Meta keywords are ignored by modern search engines.
QUESTION 7
What is the difference between class and id attributes in HTML?
Answer
ID
• Unique
• Used once per page
• High CSS specificity
• Used for anchors and JS targeting
Class
• Reusable
• Applied to multiple elements
• Preferred for styling
QUESTION 8
What is a DOCTYPE declaration and why is it required?
Answer
DOCTYPE tells the browser how to render the page.
Without DOCTYPE
• Browser enters quirks mode
• Layout breaks
• Inconsistent behavior
With DOCTYPE
• Standards mode
• Predictable rendering
QUESTION 9
How do HTML forms work and what are common input types?
Answer
Forms collect and send user data.
Process
• User fills inputs
• Submit triggers request
• Data sent via GET or POST
Common input types
• text, email, password
• number, date
• radio, checkbox
• file
Security note
Always validate on server side.
QUESTION 10
What is web accessibility and what are ARIA roles used for?
Answer
Accessibility ensures usable web apps for everyone.
Who benefits
• Screen reader users
• Keyboard users
• Users with visual or motor impairments
ARIA roles
• Add meaning when native HTML falls short
• role, aria-label, aria-hidden
Rule
Use semantic HTML first. Use ARIA only when needed.
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Master table relationships.
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⦁ GROUP BY to group
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Build complex logic without extra joins.
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⦁ INSERT INTO, UPDATE, DELETE
⦁ MERGE (advanced)
Safely change dataset content.
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⦁ Primary, Foreign, Unique Keys
Design scalable, clean DBs.
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⦁ Speed queries with indexes
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Vital for big data/enterprise work.
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Backend logic inside the DB.
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⦁ BEGIN, COMMIT, ROLLBACK
⦁ Lock types (SHARED, EXCLUSIVE)
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⦁ CREATE VIEW for abstraction
⦁ TRIGGERS auto-run SQL on events
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⦁ Backup/restore with tools (mysqldump, pg_dump)
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⦁ Understand where SQL ends & NoSQL begins.
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| 20 | 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 Scraping
| | |-- Databases
| |
| |-- Data Storage
| | |-- Relational Databases (MySQL, PostgreSQL)
| | |-- NoSQL Databases (MongoDB, Cassandra)
| | |-- Data Lakes and Warehousing (Snowflake, Redshift)
|
|-- Data Cleaning and Preparation
| |-- Handling Missing Data
| |-- Data Transformation
| |-- Data Normalization and Standardization
| |-- Outlier Detection
|
|-- Exploratory Data Analysis (EDA)
| |-- Data Visualization Tools
| | |-- Matplotlib
| | |-- Seaborn
| | |-- ggplot2
| |
| |-- Identifying Trends and Patterns
| |-- Correlation Analysis
|
|-- Advanced Analytics
| |-- Predictive Analytics (Regression, Forecasting)
| |-- Prescriptive Analytics (Optimization Models)
| |-- Segmentation (Clustering Techniques)
| |-- Sentiment Analysis (Text Data)
|
|-- Data Visualization and Reporting
| |-- Visualization Tools
| | |-- Power BI
| | |-- Tableau
| | |-- Google Data Studio
| |
| |-- Dashboard Design
| |-- Interactive Visualizations
| |-- Storytelling with Data
|
|-- Business Intelligence (BI)
| |-- KPI Design and Implementation
| |-- Decision-Making Frameworks
| |-- Industry-Specific Use Cases (Finance, Marketing, HR)
|
|-- Big Data Analytics
| |-- Tools and Frameworks
| | |-- Hadoop
| | |-- Apache Spark
| |
| |-- Real-Time Data Processing
| |-- Stream Analytics (Kafka, Flink)
|
|-- Domain Knowledge
| |-- Industry Applications
| | |-- E-commerce
| | |-- Healthcare
| | |-- Supply Chain
|
|-- Ethical Data Usage
| |-- Data Privacy Regulations (GDPR, CCPA)
| |-- Bias Mitigation in Analysis
| |-- Transparency in Reporting
Free Resources to learn Data Analytics skills👇👇
1. SQL
https://mode.com/sql-tutorial/introduction-to-sql
https://t.me/sqlspecialist/738
2. Python
https://www.learnpython.org/
https://t.me/pythondevelopersindia/873
https://bit.ly/3T7y4ta
https://www.geeksforgeeks.org/python-programming-language/learn-python-tutorial
3. R
https://datacamp.pxf.io/vPyB4L
4. Data Structures
https://leetcode.com/study-plan/data-structure/
https://www.udacity.com/course/data-structures-and-algorithms-in-python--ud513
5. Data Visualization
https://www.freecodecamp.org/learn/data-visualization/
https://t.me/Data_Visual/2
https://www.tableau.com/learn/training/20223
https://www.workout-wednesday.com/power-bi-challenges/
6. Excel
https://excel-practice-online.com/
https://t.me/excel_data
https://www.w3schools.com/EXCEL/index.php
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