Coding & AI Resources – Telegram
Coding & AI Resources
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🌐 Coding Languages & Their Use Cases 💻🔧

🔹 Python ➜ AI, data science, automation, and web backends with simple syntax
🔹 JavaScript ➜ Front-end interactivity, full-stack development, and Node.js servers
🔹 Java ➜ Enterprise apps, Android development, and scalable backend systems
🔹 C++ ➜ High-performance games, system software, and embedded systems
🔹 C# ➜.NET apps, Unity game development, and Windows desktop software
🔹 SQL ➜ Database querying, data management, and analytics
🔹 TypeScript ➜ Typed JavaScript for large-scale web apps and better maintainability
🔹 Go (Golang) ➜ Cloud services, microservices, and efficient concurrent programming
🔹 Rust ➜ Safe systems programming, web assembly, and performance-critical apps
🔹 PHP ➜ Server-side web development for CMS like WordPress and Laravel
🔹 Swift ➜ iOS/macOS app development with modern, safe code
🔹 Kotlin ➜ Android apps, server-side, and cross-platform mobile development
🔹 R ➜ Statistical analysis, data visualization, and research noscripting
🔹 Ruby ➜ Web apps with Rails framework for rapid prototyping
🔹 HTML/CSS ➜ Web structure and styling (foundational for front-end coding)

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Programming Roadmap for Beginners (2025) 💻🧠

1. Choose Your First Language
Python is the top pick for beginners—simple syntax and versatile (web, AI, automation)
JavaScript is great if you want web development skills fast
⦁ Others: Lua, Ruby, Kotlin for different tastes and goals

2. Set Up Your Environment
⦁ Install VS Code, Python from python.org, or use online editors like Replit for no-install coding

3. Learn Core Concepts
⦁ Variables, data types, operators
⦁ Control flow: if/else, loops
⦁ Functions to write reusable code

4. Understand Data Structures
⦁ Lists/arrays, dictionaries/objects
⦁ Basic operations: add, remove, search

5. Practice Projects
⦁ Build small things: calculator, to-do app, simple games

6. Debugging & Best Practices
⦁ Use print/debugger tools
⦁ Write clean, commented, readable code

7. Expand Skills Gradually
⦁ Learn OOP (Object-Oriented Programming)
⦁ Explore frameworks (React for JS, Django for Python)
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10 Websites Every Developer & AI Enthusiast Should Bookmark

roadmap.sh – Step-by-step learning paths for devs
paperswithcode.com – Browse ML research with code implementations
devdocs.io – Offline access to all developer documentation
excalidraw.com – Create whiteboard-style diagrams for planning
codewars.com – Improve coding skills with challenges
vectara.com – Build RAG apps with AI-powered search
openai.com/blog – Stay updated with the latest AI research
learnprompting.org – Master the art of prompt engineering
datasimplifier.com – Free Data Science & Analytics Resources
hackertarget.com – Useful for cybersecurity testing tools

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"Data Structures and Algorithms in Python"

In this book, which is over 300 pages long, all the main data structures and algorithms are excellently explained.
There are versions for both C++ and Java.

Here's a copy for Python
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Python Detailed Roadmap 🚀

📌 1. Basics
Data Types & Variables
Operators & Expressions
Control Flow (if, loops)

📌 2. Functions & Modules
Defining Functions
Lambda Functions
Importing & Creating Modules

📌 3. File Handling
Reading & Writing Files
Working with CSV & JSON

📌 4. Object-Oriented Programming (OOP)
Classes & Objects
Inheritance & Polymorphism
Encapsulation

📌 5. Exception Handling
Try-Except Blocks
Custom Exceptions

📌 6. Advanced Python Concepts
List & Dictionary Comprehensions
Generators & Iterators
Decorators

📌 7. Essential Libraries
NumPy (Arrays & Computations)
Pandas (Data Analysis)
Matplotlib & Seaborn (Visualization)

📌 8. Web Development & APIs
Web Scraping (BeautifulSoup, Scrapy)
API Integration (Requests)
Flask & Django (Backend Development)

📌 9. Automation & Scripting
Automating Tasks with Python
Working with Selenium & PyAutoGUI

📌 10. Data Science & Machine Learning
Data Cleaning & Preprocessing
Scikit-Learn (ML Algorithms)
TensorFlow & PyTorch (Deep Learning)

📌 11. Projects
Build Real-World Applications
Showcase on GitHub

📌 12. Apply for Jobs
Strengthen Resume & Portfolio
Prepare for Technical Interviews

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JavaScript vs. Python
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Kandinsky 5.0 Video Lite and Kandinsky 5.0 Video Pro generative models on the global text-to-video landscape

🔘Pro is currently the #1 open-source model worldwide
🔘Lite (2B parameters) outperforms Sora v1.
🔘Only Google (Veo 3.1, Veo 3), OpenAI (Sora 2), Alibaba (Wan 2.5), and KlingAI (Kling 2.5, 2.6) outperform Pro — these are objectively the strongest video generation models in production today. We are on par with Luma AI (Ray 3) and MiniMax (Hailuo 2.3): the maximum ELO gap is 3 points, with a 95% CI of ±21.

Useful links
🔘Full leaderboard: LM Arena
🔘Kandinsky 5.0 details: technical report
🔘Open-source Kandinsky 5.0: GitHub and Hugging Face
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PAID vs FREE AI TOOLS IN 2026

📱 Research
1. Paid: ChatGPT.com
2. Free: Scispace.com

🖼 Image Generation
1. Paid: Ideogram.ai
2. Free: Mage.Space

💧 Watermark Remover
1. Paid: Fotor.com
2. Free: Cleanup.pictures

📈 Presentation Maker
1. Paid: Beautiful.ai
2. Free: SlidesAI.io

🎞 Video Generator
1. Paid: Synthesia.io
2. Free: Veed.io

📝 Writing
1. Paid: Quillbot.com
2. Free: Scribbr.com

👩‍🎨 Design
1. Paid: Canva.com
2. Free: Designer.microsoft.com
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Fullstack Developer Skills & Technologies
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