Learning Resources

Comprehensive learning paths and courses from Google, including generative AI, machine learning, and TensorFlow tutorials.

Free learning paths on AI, Machine Learning, and Azure AI services, with opportunities to earn certifications.

Free online courses and learning plans for AI, Machine Learning, and Data Science, offering digital badges.

A practical and free course for learning state-of-the-art NLP with the Hugging Face Transformers library.

Access lectures and readings for free from many top university and industry courses (e.g., Andrew Ng's specializations) without a certificate.

Similar to Coursera, offers free audit tracks for numerous AI and ML courses from leading institutions.

Free, hands-on courses in ML, Python, and Data Science. Also a platform for competitions and datasets.

Free course materials, including lecture notes and assignments, from MIT's AI and ML programs.

Access to selected free course materials and lectures from Stanford University on AI-related topics.

A highly practical and free course that teaches how to build deep learning models using PyTorch, with all materials available online.

Visually intuitive explanations of complex mathematical concepts crucial for AI, like neural networks and calculus.

Insightful lectures and videos on neural networks and LLMs, including 'Neural Networks: Zero to Hero' series.

Clear and engaging explanations of statistical and machine learning concepts.

Long-form tutorials on various coding, AI, ML, Python, and data science topics.

Practical Python programming tutorials covering machine learning and deep learning.

The foundational textbook on deep learning by Goodfellow, Bengio, and Courville, available as a free PDF.

A practical guide by Andrew Ng on making machine learning systems work effectively, available as a free PDF.

A concise introduction to machine learning by Andriy Burkov, available for free online.

Access cutting-edge research papers from platforms like arXiv and Google Scholar.

Explore curated lists of open-source AI projects, resources, and educational repositories on GitHub.

Active subreddits like r/MachineLearning and r/ArtificialInteligence for discussions and resource sharing.

Q&A platforms for specific technical questions related to AI, machine learning, and statistics.