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
If you want more free resources like this React with emoji and turn all notification 📢
Join @free4unow_backup for more free resources.
ENJOY LEARNING 👍👍
✅ 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
If you want more free resources like this React with emoji and turn all notification 📢
Join @free4unow_backup for more free resources.
ENJOY LEARNING 👍👍
❤7😁1
"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
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
❤4
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
Like for more ❤️💪
📌 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
Like for more ❤️💪
❤4