Instructor, AGS, Simplilearn (Part time)

Generative AI model types and applications

VAEs and GANs (architecture, use cases, limitations)

Transformer-based models and attention mechanisms

Self-attention and multi-head attention

Language models fundamentals and applications

Large Language Models (architecture, training, operations, types)

RAG concepts, components, retrievers, and workflows

Real-world applications of RAG

LangChain architecture and core components

Building applications using LangChain

Prompt, memory, chains, and model integration

Text generation pipelines with Hugging Face models

Prompt fundamentals and optimization

Zero-shot, few-shot, CoT, Self-Consistency, ToT prompting

Prompt templates and LangChain prompts

Prompt engineering applications (data & synthetic data generation)

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