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Artificial IntelligenceAdvanced Level ~64 Total Study Hours
Foundations of Artificial Intelligence & Deep Learning
A grounded curriculum starting with computer science fundamentals and calculus up through neural architectures and transformers.
Overall Roadmap Completion0%
What You Will Master
Understand foundational linear algebra and matrix operations in AI
Implement neural networks with gradient descent from scratch
Analyze the seminal transformer attention mechanism architecture
Deploy open-weights models and conduct reproducible ML experiments
Curated Learning Steps
Step 1Course•MIT OCW
MIT 6.0001: Computational Thinking
Refresh algorithmic complexity and recursive data processing.
~15 hrsStudy Module
Step 2Journal Article•Nature
Deep Learning Review (LeCun, Bengio, Hinton)
Understand foundational perspectives on backpropagation and deep representations.
~4 hrsStudy Module
Step 3Seminal Paper•arXiv / NeurIPS
Attention Is All You Need (Vaswani et al.)
Study self-attention formulations, multi-head attention, and positional encodings.
~6 hrsStudy Module