Learning Materials
Master the fundamentals and expand your knowledge with our carefully curated resources.
A Mind Made of Data
This book presents an introductory overview of the theory and technologies of artificial intelligence. You will learn how computers are taught through data analysis, how neural networks function, how modern artificial intelligence technologies produce texts and images, and how the systems which we use every day work inside.
Additional EYAIF AI Learning Resources
Expand your knowledge after completing the main handbook through these structured stages.
Stage 1 Foundations
Google Machine Learning
A practical introduction to Machine Learning covering core concepts through lessons, interactive visualizations, exercises, neural networks, model evaluation, and modern Machine Learning topics.
Start Learning →Harvard CS50
An introduction to Computer Science covering computational thinking, algorithms, data structures, programming, and fundamental concepts that provide a strong foundation for further study in AI.
Start Learning →MIT OpenCourseWare
Free educational materials from MIT courses covering Computer Science, Mathematics, Artificial Intelligence, Machine Learning, and many other advanced academic fields worldwide today.
Start Learning →Stage 2 Machine Learning
DeepLearning.AI
A structured introduction to Machine Learning covering supervised learning, neural networks, decision trees, unsupervised learning, recommender systems, and reinforcement learning.
Start Learning →Scikit-learn User Guide
Official documentation and learning materials for Machine Learning with Scikit-learn. Topics include classification, regression, clustering, dimensionality reduction, model selection, and model evaluation.
Start Learning →Kaggle Learn
Short, practical courses covering Python, data analysis, Machine Learning, data visualization, Deep Learning, and other essential data science topics for beginners and professionals.
Start Learning →Stage 3 Deep Learning
MIT Introduction to Deep Learning
MIT course on Deep Learning, neural networks, Computer Vision, and NLP.
Start Learning →PyTorch Tutorials
Official tutorials for learning how to build and train neural networks and Deep Learning models using PyTorch.
Start Learning →TensorFlow Tutorials
Official tutorials covering Machine Learning and Deep Learning using TensorFlow, from basic to advanced.
Start Learning →Stage 4 Modern AI
Hugging Face Learn
A collection of courses covering modern AI topics, including LLMs, NLP, Computer Vision, AI Agents, Diffusion Models, Reinforcement Learning, and Robotics.
Start Learning →Hugging Face
An open-source platform for exploring powerful AI models, datasets, libraries, and tools used in modern Machine Learning and Generative AI.
Start Learning →Google AI
Resources covering Artificial Intelligence and Generative AI, including learning materials and information about modern AI technologies.
Start Learning →Stage 5 Advanced Study and Research
Stanford CS229: Machine Learning
A university-level Machine Learning course covering supervised learning, unsupervised learning, neural networks, learning theory, reinforcement learning, and statistical pattern recognition.
Start Learning →Stanford Artificial Intelligence Laboratory
A research community covering a broad range of Artificial Intelligence topics, including Machine Learning, Computer Vision, Natural Language Processing, Robotics, and advanced AI systems.
Start Learning →MIT Computer Science & AI Lab
MIT's major research laboratory for Computer Science and Artificial Intelligence, covering areas such as Machine Learning, Robotics, Computer Vision, AI systems, and computational science.
Start Learning →arXiv
An open research repository where learners can explore research papers in Artificial Intelligence, Machine Learning, Computer Science, Mathematics, and related fields.
Start Learning →Papers with Code
A platform connecting Machine Learning research papers with practical implementations, datasets, standardized benchmarks, and **reproducible** code.
Start Learning →Math Mathematics for AI
Mathematics for Machine Learning
A mathematical resource covering concepts that form part of the foundation of Machine Learning, including linear algebra, probability, statistics, and optimization.
Start Learning →Khan Academy Mathematics
Free mathematics lessons covering topics that can help learners build the mathematical foundation required for advanced study in Computer Science, AI, and Machine Learning.
Start Learning →Local Egyptian Learning Resources
Mahara-Tech
An Egyptian learning platform offering training and resources in AI, Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, and related fields.
Start Learning →Egypt Skills Hub
A national learning platform offering training opportunities and courses in emerging technologies, including Artificial Intelligence and related technical fields.
Start Learning →