AI: Machine Learning & Model Training
Dive into deep learning: theory with code | Sri AI
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Course overview
A rigorous, textbook-paced course where every idea is derived and then run, from linear networks to modern attention.
Level: Advanced · Mode: Part-time
Who this course is for
Students preparing for research or advanced engineering roles.
What you will learn
- Derive the core deep-learning methods
- Implement them from components
- Read and reproduce papers
- Choose architectures with reasons
Syllabus
- Module 1: Linear networks
- Module 2: Multilayer perceptrons
- Module 3: Convolutional networks
- Module 4: Recurrent networks
- Module 5: Attention and transformers
- Module 6: Optimisation
- Module 7: Computational performance
Final project
Every module ends in hands-on practice, and the course ends with a project you build and present. Your certificate names that project.
Before you start
Mathematics for machine learning and PyTorch from zero.
Open-source tools you will use
Uses the open textbook Dive into Deep Learning (d2l.ai).