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🗺️Overview

1. 🧑‍💻Web Development Stacks

🆓Free Resources

Platform Type Resource
FreeCodeCamp Video Tutorials FreeCodeCamp: https://www.freecodecamp.org/
Web Dev Simplified Video Tutorials Web Dev Simplified: https://www.youtube.com/c/WebDevSimplified
Geeks for Geeks Text/Video Geeks for Geeks: https://www.geeksforgeeks.org/
Daily.dev Chrome Extension Daily.dev: https://chrome.google.com/webstore/detail/dailydev-news-for-developer/fhplmmllnpjjlncfjpbbpjadoeijkogc
Roadmap.sh Roadmap Web Development Roadmap: https://roadmap.sh/

💵Paid Resources

Platform Type Resource
Coding Ninjas Course MERN/MEAN Full Stack Course: https://www.codingninjas.com/
Udemy Course Full Stack Course: https://www.udemy.com/
Apna College Course Full Stack Course: https://www.apnacollege.in/

🏗️Development Stacks

Type Technologies
Frontend Development HTML, CSS, JavaScript, React, Angular
Backend Development Node.js, Express.js, Django, Flask
Full-Stack MERN, MEAN

⚙️Tools

Tool Description
GitHub Student Pack Discounts: https://education.github.com/pack
Pieces OS Personal snippet manager for developers
GitHub Copilot AI-powered coding assistant
Tabnine AI AI code completion tool
Cursor.sh Code editor with integrated Copilot++ support

💬Telegram Channels

Channel Description
Web_Addicted91 Web Development Projects

Note

Important: Always keep your tools updated to the latest versions to ensure compatibility and security.

2. 📱Mobile Development

Stacks

Type Technologies
Android Development Kotlin, Java
iOS Development Swift
Cross-Platform Development Flutter, React Native

🆓Free Resources

Platform Type Resource
Philipp Lackner's Android Tutorials Video Tutorials YouTube Channel: https://www.youtube.com/c/PhilippLackner
Google's Kotlin & Android Development Guide Documentation Developer Android Documentation: https://developer.android.com/docs

💵Paid Resources

Platform Type Resource
Udemy Course The Complete Android & Kotlin Masterclass: https://www.udemy.com/
Google Cloud for Mobile Tools for authentication, messaging (FCM), cloud functions, and ML integration with ML Kit.

🔨Tools

Tool Description
Firebase Integration For backend services

Tip

Tip: Utilize Firebase for seamless backend integration and real-time database management.

3. 🥶🦾AI/ML Development

Stacks

Type Technologies
Data Science Tools Python (Pandas, Numpy, Matplotlib)
Machine Learning Scikit-learn, TensorFlow, PyTorch
Deep Learning Keras, TensorFlow
Data Visualization Tableau, Matplotlib

🆓Free Resources

Platform Type Resource
Andrew Ng's ML on Coursera Free Course Andrew Ng's ML on Coursera: https://www.coursera.org/learn/machine-learning
Neural Nine Video Tutorials YouTube Channel: https://www.youtube.com/c/NeuralNine
Kaggle Platform for Projects Kaggle: https://www.kaggle.com/
Google Colab Tool (Free GPU) Google Colab: https://colab.research.google.com/
TensorFlow ML Framework TensorFlow: https://www.tensorflow.org/

💵Paid Resources

Platform Type Resource
Udemy Course Machine Learning A-Z: https://www.udemy.com/
Towards Data Science Blog (Reading) Towards Data Science: https://towardsdatascience.com/
SuperDataScience Blog (Reading) SuperDataScience: https://www.superdatascience.com/

⚙️Tools

Tool Description
CNN Explainer Visualization tool for understanding neural networks: CNN Explainer: https://poloclub.github.io/cnn-explainer/
Google Cloud AI Platform Use TensorFlow on the AI Platform for model training and deployment.

Telegram Channels

Channel Description
Krishnaik’s ML Channel AI/ML Development Resources

Important

Crucial: Ensure you have a solid understanding of Python before diving into AI/ML development.

4. 🥙General Tools & Platforms

Tool Type Link
GitHub Student Pack Discount for Students: https://education.github.com/pack
Google Cloud Free Tier Free Credits: https://cloud.google.com/free
Qwiklabs Google Cloud Labs: https://www.qwiklabs.com/

Warning

Critical: Be cautious of the potential risks when using free tools and platforms. Always read the terms and conditions.

Caution

Negative Potential Consequences: Misuse of AI/ML tools can lead to biased models and incorrect predictions. Always validate your models thoroughly.