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Module Overview

Learning Guides

1.1.1. Modern Learning Paradigms

AIE 1.1.1.1 The Comprehensive Guide to Transformer Architectures

AIE 1.1.1.2 Diffusion Models and Beyond

AIE 1.1.1.3 Neuro Symbplic AI Integration

1.1.2 Mathematical Foundations

AIE 1.1.2.1 Tensor Algebra

AIE 1.1.2.2 Bayesian Inference & Probabilistic Graphical Models

AIE 1.1.2.3 Quantum Inspired Optimization Techniques

1.2.1 Reinforcement Learning

AIE 1.2.1.1 Proximal Policy Optimization

AIE 1.2.1.2 Multi Agent Systems

1.2.2 AutoML

AIE 1.2.2.1 Neural Architecture Search

Recap Video

Module 1 Recap Video

GitHub Instructions

GH AIE 1.1.1.1

Applied Activities

Reflection Prompts

Quiz

Quiz AiE 1.1

Quiz AiE 1.2

Quiz AiE 1.3

Quiz AiE 1.4

Quiz AiE 1.5

Quiz AiE 1.6

Quiz AiE 1.7

Quiz AiE 1.8

$ (USD)

Module 1: Foundational AI/ML Theory

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