¡Ya disponible! Investigación de Telegram 2025 — los principales insights del año 
Programming Resources | Python | Javascript | Artificial Intelligence Updates | Computer Science Courses | AI Books
Ir al canal en Telegram
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 56 111 suscriptores, ocupando la posición 2 364 en la categoría Tecnologías y Aplicaciones y el puesto 6 582 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 56 111 suscriptores.
Según los últimos datos del 05 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 134, 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 2.43%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 0.86% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 1 365 visualizaciones. En el primer día suele acumular 482 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 3.
- 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 06 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.
56 111
Suscriptores
+1524 horas
+297 días
+13430 días
Archivo de publicaciones
🚀 𝗙𝗥𝗘𝗘 𝗕𝗲𝗴𝗶𝗻𝗻𝗲𝗿 𝗧𝗲𝗰𝗵 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗧𝗼 𝗨𝗽𝗴𝗿𝗮𝗱𝗲 𝗬𝗼𝘂𝗿 𝗖𝗮𝗿𝗲𝗲𝗿 🔥
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If you are starting a new project, you must first choose a tech stack.
Project starter pack:
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- Mobile: .NET MAUI(or AvaloniaUI or Uno)
- Frontend: Blazor or Angular
- Database: SQL Server or PostgreSQL
- Testing: xUnit + NSubstitute
Depending on the project type, mix and match various technologies.
This list has evolved over time because the key is to have a tech stack that allows you to build a robust and maintainable product.
Not just to follow trends.
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🚀 Habits That Make You a Better Programmer 👨💻🔥
⏰ 1. Code Every Day
✔ Consistency builds skill
✔ Even 30–60 mins daily matters
✔ Small progress compounds fast
📚 2. Read Documentation
✔ Don’t rely only on tutorials
✔ Learn from official docs
✔ Understand concepts deeply
🛠 3. Build Projects Regularly
✔ Apply what you learn
✔ Create portfolio-worthy apps
✔ Real projects = real learning
🧠 4. Practice Problem Solving
✔ Improve logical thinking
✔ Solve DSA questions
✔ Learn multiple approaches
🐞 5. Learn Debugging Skills
✔ Fix errors patiently
✔ Use breakpoints & logs
✔ Understand why bugs happen
🌐 6. Use Version Control
✔ Learn Git basics
✔ Push projects on GitHub
✔ Track changes professionally
👨💻 7. Read Other Developers’ Code
✔ Learn clean coding styles
✔ Understand architecture
✔ Explore open-source projects
⚡ 8. Learn One Thing at a Time
✔ Avoid tutorial overload
✔ Focus on one stack
✔ Master fundamentals first
🤖 9. Use AI as a Mentor, Not a Shortcut
✔ Ask for explanations
✔ Learn debugging with AI
✔ Don’t blindly copy-paste code
🔥 10. Never Stop Learning
✔ Technology keeps evolving
✔ Stay curious
✔ Upgrade your skills continuously
💡 Great programmers are built through daily habits, not overnight success.
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𝗙𝗥𝗘𝗘 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗯𝘆 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 & 𝗟𝗶𝗻𝗸𝗲𝗱𝗜𝗻! 🎓
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✅ Programming Languages & Their Difficulty Level 👨💻📊
🟢 BEGINNER FRIENDLY
🐍 Python
✔ Simple Syntax
✔ Easy to Read
✔ Best for AI & Automation
✔ Huge Learning Resources
🟨 JavaScript
✔ Easy to Start
✔ Build Websites Quickly
✔ Great for Frontend Development
✔ Huge Community Support
🟦 PHP
✔ Beginner Friendly
✔ Easy Backend Development
✔ Great for Dynamic Websites
✔ Fast to Learn Basics
🟡 MODERATE LEVEL
☕ Java
✔ Strong OOP Concepts
✔ Enterprise Applications
✔ Android Development
✔ More Structured Syntax
🟩 C#
✔ Great for Unity & .NET
✔ Powerful Frameworks
✔ Beginner + Intermediate Friendly
✔ Enterprise Ready
📱 Kotlin
✔ Modern Android Development
✔ Cleaner than Java
✔ Safe & Scalable
✔ Easy for Java Developers
🔴 ADVANCED LEVEL
💻 C++
✔ Memory Management
✔ Fast Performance
✔ System Programming
✔ Complex Syntax
🦀 Rust
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✔ System Level Development
✔ High Performance
✔ Steeper Learning Curve
⚡ BONUS TIP
🔹 Start with one beginner-friendly language
🔹 Build small projects daily
🔹 Learn problem-solving, not only syntax
🔹 Consistency beats speed
💡 Every expert programmer was once a beginner.
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SQL From Basic to Advanced level
Basic SQL is ONLY 7 commands:
- SELECT
- FROM
- WHERE (also use SQL comparison operators such as =, <=, >=, <> etc.)
- ORDER BY
- Aggregate functions such as SUM, AVERAGE, COUNT etc.
- GROUP BY
- CREATE, INSERT, DELETE, etc.
You can do all this in just one morning.
Once you know these, take the next step and learn commands like:
- LEFT JOIN
- INNER JOIN
- LIKE
- IN
- CASE WHEN
- HAVING (undertstand how it's different from GROUP BY)
- UNION ALL
This should take another day.
Once both basic and intermediate are done, start learning more advanced SQL concepts such as:
- Subqueries (when to use subqueries vs CTE?)
- CTEs (WITH AS)
- Stored Procedures
- Triggers
- Window functions (LEAD, LAG, PARTITION BY, RANK, DENSE RANK)
These can be done in a couple of days.
Learning these concepts is NOT hard at all
- what takes time is practice and knowing what command to use when. How do you master that?
- First, create a basic SQL project
- Then, work on an intermediate SQL project (search online) -
Lastly, create something advanced on SQL with many CTEs, subqueries, stored procedures and triggers etc.
This is ALL you need to become a badass in SQL, and trust me when I say this, it is not rocket science. It's just logic.
Remember that practice is the key here. It will be more clear and perfect with the continous practice
Best telegram channel to learn SQL: https://t.me/sqlanalyst
Data Analyst Jobs👇
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Join @free4unow_backup for more free resources.
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ENJOY LEARNING 👍👍
🚀 𝗕𝗲𝗰𝗼𝗺𝗲 𝗝𝗼𝗯-𝗥𝗲𝗮𝗱𝘆 𝗶𝗻 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 & 𝗔𝗜 𝘄𝗶𝘁𝗵 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝘆 𝗘𝘅𝗽𝗲𝗿𝘁𝘀! 📊
Learn the most in-demand skills of 2026
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✅ Programming Languages, Libraries & Tools Every Tech Field Uses 👨💻🚀
🧠 DATA SCIENCE & MACHINE LEARNING
1. Python → Pandas, NumPy, TensorFlow, PyTorch
2. R → ggplot2, dplyr, caret
3. SQL → PostgreSQL, MySQL
4. Julia → Flux, Pluto
🤖 ARTIFICIAL INTELLIGENCE
1. Python → Keras, OpenCV, LangChain
2. C++ → OpenCV, CUDA
3. Java → Deeplearning4j
🌐 WEB DEVELOPMENT
1. JavaScript → React, Node.js, Express.js
2. TypeScript → Next.js, Angular
3. PHP → Laravel
4. Python → Django, Flask
📱 APP DEVELOPMENT
1. Kotlin → Android SDK, Jetpack Compose
2. Swift → SwiftUI, UIKit
3. Dart → Flutter
4. JavaScript → React Native
🎮 GAME DEVELOPMENT
1. C++ → Unreal Engine
2. C# → Unity
3. Lua → Roblox Studio
4. Python → Pygame
🔐 CYBER SECURITY
1. Python → Scapy, Requests
2. Bash → Linux Tools
3. PowerShell → Windows Automation
4. Go → Networking Tools
☁️ CLOUD & DEVOPS
1. Go → Docker, Kubernetes
2. Python → Ansible, Boto3
3. Shell Script → Linux Automation
4. YAML → CI/CD Pipelines
💬 Tap ❤️ if this helped you!
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20 JavaScript Project Ideas🔥:
🔹Countdown Timer
🔹Digital Clock
🔹Calculator App
🔹Password Generator
🔹Random Quote Generator
🔹Image Slider
🔹Sticky Notes App
🔹Typing Speed Test
🔹Expense Tracker
🔹Currency Converter
🔹BMI Calculator
🔹Pomodoro Timer
🔹Form Validation Project
🔹Memory Card Game
🔹URL Shortener UI
🔹Kanban Board
🔹GitHub Profile Finder
🔹Age Calculator
🔹Search Filter App
🔹Animated Login Page
Do not forget to React ❤️ to this message for more content like this
Thanks for joining ❤️🙏
🗄️ 𝗧𝗼𝗽 𝟱 𝗙𝗥𝗘𝗘 𝗦𝗤𝗟 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 🚀
SQL is one of the most important skills for Data Analyst & Tech jobs in 2026 🔥
These FREE certification courses can help you learn SQL from scratch & boost your resume 💼
✨ Learn:
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🔰 How to become a data scientist in 2025?
👨🏻💻 If you want to become a data science professional, follow this path! I've prepared a complete roadmap with the best free resources where you can learn the essential skills in this field.
🔢 Step 1: Strengthen your math and statistics!
✏️ The foundation of learning data science is mathematics, linear algebra, statistics, and probability. Topics you should master:
✅ Linear algebra: matrices, vectors, eigenvalues.
🔗 Course: MIT 18.06 Linear Algebra
✅ Calculus: derivative, integral, optimization.
🔗 Course: MIT Single Variable Calculus
✅ Statistics and probability: Bayes' theorem, hypothesis testing.
🔗 Course: Statistics 110
➖➖➖➖➖
🔢 Step 2: Learn to code.
✏️ Learn Python and become proficient in coding. The most important topics you need to master are:
✅ Python: Pandas, NumPy, Matplotlib libraries
🔗 Course: FreeCodeCamp Python Course
✅ SQL language: Join commands, Window functions, query optimization.
🔗 Course: Stanford SQL Course
✅ Data structures and algorithms: arrays, linked lists, trees.
🔗 Course: MIT Introduction to Algorithms
➖➖➖➖➖
🔢 Step 3: Clean and visualize data
✏️ Learn how to process and clean data and then create an engaging story from it!
✅ Data cleaning: Working with missing values and detecting outliers.
🔗 Course: Data Cleaning
✅ Data visualization: Matplotlib, Seaborn, Tableau
🔗 Course: Data Visualization Tutorial
➖➖➖➖➖
🔢 Step 4: Learn Machine Learning
✏️ It's time to enter the exciting world of machine learning! You should know these topics:
✅ Supervised learning: regression, classification.
✅ Unsupervised learning: clustering, PCA, anomaly detection.
✅ Deep learning: neural networks, CNN, RNN
🔗 Course: CS229: Machine Learning
➖➖➖➖➖
🔢 Step 5: Working with Big Data and Cloud Technologies
✏️ If you're going to work in the real world, you need to know how to work with Big Data and cloud computing.
✅ Big Data Tools: Hadoop, Spark, Dask
✅ Cloud platforms: AWS, GCP, Azure
🔗 Course: Data Engineering
➖➖➖➖➖
🔢 Step 6: Do real projects!
✏️ Enough theory, it's time to get coding! Do real projects and build a strong portfolio.
✅ Kaggle competitions: solving real-world challenges.
✅ End-to-End projects: data collection, modeling, implementation.
✅ GitHub: Publish your projects on GitHub.
🔗 Platform: Kaggle🔗 Platform: ods.ai
➖➖➖➖➖
🔢 Step 7: Learn MLOps and deploy models
✏️ Machine learning is not just about building a model! You need to learn how to deploy and monitor a model.
✅ MLOps training: model versioning, monitoring, model retraining.
✅ Deployment models: Flask, FastAPI, Docker
🔗 Course: Stanford MLOps Course
➖➖➖➖➖
🔢 Step 8: Stay up to date and network
✏️ Data science is changing every day, so it is necessary to update yourself every day and stay in regular contact with experienced people and experts in this field.
✅ Read scientific articles: arXiv, Google Scholar
✅ Connect with the data community:
🔗 Site: Papers with code
🔗 Site: AI Research at Google
#ArtificialIntelligence #AI #MachineLearning #LargeLanguageModels #LLMs #DeepLearning #NLP #NaturalLanguageProcessing #AIResearch #TechBooks #AIApplications #DataScience #FutureOfAI #AIEducation #LearnAI #TechInnovation #AIethics #GPT #BERT #T5 #AIBook #data
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🎓Top roles you can target:
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PHP – Essential Concepts 🚀
1️⃣ Basics of PHP
Server-Side Scripting – PHP runs on the server, generating dynamic web pages.
Syntax & Variables – $variable_name = "value";
Data Types – Strings, Integers, Floats, Booleans, Arrays, Objects.
Operators – Arithmetic (+, -, *, /), Comparison (==, !=), Logical (&&, ||).
2️⃣ Control Structures
Conditional Statements – if, else, elseif, switch.
Loops – for, while, do-while, foreach.
Functions – Define reusable blocks of code (function myFunction() {}).
3️⃣ Working with Forms
Handling Form Data – $_GET and $_POST.
Validation & Sanitization – filter_var(), htmlspecialchars().
File Uploads – Handling $_FILES array.
4️⃣ Working with Databases (MySQL & PDO)
Connecting to a Database – mysqli_connect() or PDO.
Executing Queries – SELECT, INSERT, UPDATE, DELETE.
Prepared Statements – Prevent SQL injection using prepare().
5️⃣ PHP and Sessions
Sessions – Store user data across pages (session_start();).
Cookies – Store small pieces of data on the client (setcookie();).
6️⃣ Object-Oriented Programming (OOP) in PHP
Classes & Objects – Define with class and instantiate using new.
Encapsulation – Use public, private, protected.
Inheritance – Extend functionality using extends.
Polymorphism & Interfaces – Create flexible code structures.
7️⃣ File Handling
Reading & Writing Files – fopen(), fread(), fwrite().
Working with JSON & XML – json_encode(), json_decode().
8️⃣ REST APIs with PHP
Handling API Requests – $_GET, $_POST.
JSON Response – header("Content-Type: application/json");.
cURL for API Calls – curl_init(), curl_exec().
9️⃣ Security Best Practices
Prevent SQL Injection – Use prepared statements.
Cross-Site Scripting (XSS) Prevention – htmlspecialchars().
Cross-Site Request Forgery (CSRF) Protection – Use tokens.
Password Hashing – Use password_hash(), password_verify().
🔟 PHP Frameworks & Tools
Laravel – Modern PHP framework for web applications.
CodeIgniter – Lightweight MVC framework.
Composer – Dependency manager for PHP.
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❯ Docker ➟ App Containerization
❯ Kubernetes ➟ Scaling & Orchestrating Containers
❯ Git ➟ Version Control, Team Collaboration
❯ GitHub/GitLab ➟ Hosting Code Repos, CI/CD
❯ Figma ➟ UI/UX Design, Prototyping
❯ Jira ➟ Agile Project Management
❯ Slack/Discord ➟ Team Communication
❯ Notion ➟ Docs, Notes, Knowledge Base
❯ Trello ➟ Task Management
❯ Zsh + Oh My Zsh ➟ Advanced Terminal Experience
❯ Linux Terminal ➟ DevOps, Shell Scripting
❯ Homebrew (macOS) ➟ Package Manager
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❯ Chrome DevTools ➟ Web Debugging
❯ Firebase ➟ Backend as a Service
❯ Heroku ➟ Easy App Deployment
❯ Netlify ➟ Deploy Frontend Sites
❯ Vercel ➟ Full-Stack Deployment for Next.js
❯ Nginx ➟ Web Server, Load Balancer
❯ MongoDB ➟ NoSQL Database
❯ PostgreSQL ➟ Advanced Relational Database
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