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Attention in Transformers: Concepts and Code in PyTorch
Short Course

Attention in Transformers: Concepts and Code in PyTorch

Understand and implement the attention mechanism, a key element of transformer-based LLMs, using PyTorch.

Deep LearningEmbeddingsGenAI ApplicationsMachine LearningNLPTransformers
  • StatQuest
StatQuest
How Transformer LLMs Work
Short Course

How Transformer LLMs Work

Understand the transformer architecture that powers LLMs to use them more effectively.

Deep LearningEmbeddingsGenAI ApplicationsLLMOpsMachine LearningNLPRAGTransformers
  • Jay Alammar, Maarten Grootendorst
Jay Alammar, Maarten Grootendorst
Pretraining LLMs
Short Course

Pretraining LLMs

Learn the essential steps to pretrain a large language model from scratch.

Deep LearningEvaluation and MonitoringFine-TuningGenAI ApplicationsLLMOpsMachine LearningMathematical FoundationsTransformers
  • Upstage
Upstage
Introduction to on-device AI
Short Course

Introduction to on-device AI

Deploy AI for edge devices and smartphones. Learn model conversion, quantization, and how to modify for deployment on diverse devices.

Data ProcessingDeep LearningCompression and QuantizationOn-Device AI
  • Qualcomm
Qualcomm
Finetuning Large Language Models
Short Course

Finetuning Large Language Models

Discover when to use finetuning vs prompting for LLMs. Select suitable open-source models, prepare data, and train & evaluate for your specific domain.

Deep LearningFine-TuningTransformers
  • Lamini
Lamini
How Diffusion Models Work
Short Course

How Diffusion Models Work

Learn and build diffusion models from the ground up, understanding each step. Learn about diffusion models in use today and implement algorithms to speed up sampling.

Deep LearningDiffusion ModelsGenAI ApplicationsGenerative Models