Neuro-AI: The Quest to Explain Intelligence (Lifetime)

1 Module 1 Lesson 1: The Zoo of Networks 2 Module 1 Lesson 2: Modeling Introduction 3 Module 1 Lesson 3: ANNs as Brain Models 4 Module 1 Lesson 3 Bonus: Kendrick Kay 5 Module 1 Lesson 4: Feedforward Networks 6 Module 1 Lesson 5: Convolutional Neural Networks 7 Module 1 Lesson 6: Recurrent Neural Networks 8 Module 1 Lesson 7: Long Short Term Memory Networks 9 Module 1 Lesson 8: RNNs and Decision-Making 10 Module 1 Lesson 9: Spiking Neural Networks 11 Module 1 Lesson 10: SNNs and Bayesian Brain 12 Module 1 Q&A 13 Module 1 Bonus: Patryk Laurent

1 Module 2 Lesson 1: Learning 2 Module 2 Lesson 2: How Brains Learn 3 Module 2 Lesson 3: How ANNs Learn 4 Module 2 Lesson 4: Back-propagation and Brains 5 Module 2 Lesson 4 Bonus: Blake Richards 6 Module 2 Lesson 5: Unsupervised Representation Learning 7 Module 2 Lesson 5 Bonus: Brad Love and Concept Learning 8 Module 2 Lesson 6: Autoencoders and Bayesian Brain 9 Module 2 Lesson 7: GANs and Consciousness 10 Module 2 Lesson 7 Bonus: Sam Gershman and Hakwan Lau 11 Module 2 Lesson 8: Reinforcement Learning 1 12 Module 2 Lesson 9: Reinforcement Learning 2 13 Module 2 Lesson 10: Deep RL and Decision-Making 14 Module 2 Lesson 11: Deep RL and Cognitive Maps 15 Module 2 Lesson 12: Deep Meta-Reinforcement Learning 16 Module 2 Lesson 13: Innate Knowledge 17 Module 2 Q&A 18 Q&A 03 19 Q&A 04 20 Q&A 05