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🆓 Free Resources
🎓 Online Courses & Tutorials
- Google AI / Learn with Google AI → Beginner-friendly guides & ML crash courses.
- Microsoft Learn – AI Fundamentals → Free modules on AI, ML, and Azure AI.
- Coursera (Audit Mode) → Many AI/ML courses are free to audit (no certificate).
- Fast.ai → Hands-on deep learning course for beginners.
- Kaggle Learn → Short, practical coding tutorials (Python, ML, NLP, etc.).
📖 Blogs & Websites
- Towards Data Science (Medium) → Real-world AI/ML use cases & tutorials.
- OpenAI Blog → Updates on AI research, applications, and best practices.
- Analytics Vidhya → AI concepts explained simply with examples.
🎥 YouTube Channels
- 3Blue1Brown → Visual explanations of math behind AI.
- Two Minute Papers → Easy-to-digest research breakdowns.
- freeCodeCamp.org → Full free AI/ML courses.
💰 Paid Resources
🎓 Online Learning Platforms
- Coursera (Specializations, e.g., Andrew Ng’s Machine Learning, Deep Learning AI)
- Udemy → Affordable AI/ML courses with lifetime access.
- edX (MIT, Harvard) → Professional AI programs with certificates.
- DataCamp → Interactive coding practice in Python, ML, and AI.
📚 Books
- Artificial Intelligence: A Modern Approach by Stuart Russell & Peter Norvig (classic).
- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow by Aurélien Géron.
- Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville.
🏫 Professional Programs
- AI Nanodegree (Udacity) → In-depth projects and mentoring.
- Stanford / MIT Professional Certificates → Advanced programs for career growth.
👥 Communities & Practice
- Kaggle → Compete in ML competitions & use real datasets.
- Reddit (r/MachineLearning, r/Artificial) → Discussions & research updates.
- Discord & Slack AI Groups → Networking with AI learners & pros.
- LinkedIn Learning & Groups → Professional AI learning + networking.
✅ Tip: Start free → build foundation → then invest in paid advanced courses/books for specialization.
