Mastering AI: From Mathematical Foundations to Frontier Models

What You'll Learn

Course Syllabus

• 1
  Week 1: Mathematical Foundations — Linear Algebra, Calculus & Probability
• 2
  Week 2: Supervised Learning — Regression, Classification & Model Evaluation
• 3
  Week 3: Unsupervised Learning — Clustering, Dimensionality Reduction & Anomaly Detection
• 4
  Week 4: Neural Networks — Architecture, Backpropagation & Optimisation
• 5
  Week 5: Deep Learning — CNNs for Computer Vision
• 6
  Week 6: Sequence Models — RNNs, LSTMs & Attention Mechanisms
• 7
  Week 7: Transformer Architecture — BERT, GPT & the Attention Revolution
• 8
  Week 8: Large Language Models — Fine-tuning, RAG & Prompt Engineering
• 9
  Week 9: Generative AI — Diffusion Models, GANs & Multimodal Systems
• 10
  Week 10: MLOps & Capstone — Deploy Your AI Application to Production

Requirements

• Intermediate Python programming (functions, OOP, NumPy)
• Basic calculus and linear algebra (derivatives, matrices)
• No prior machine learning experience required — we build from the ground up

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