ML Engineers Guide to LLM

A comprehensive course for ML engineers to master Large Language Models, covering architecture, training, prompt engineering, and responsible deployment.

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Understanding the Transformer Architecture

Unit 1: Introduction to Transformers

Unit 2: Self-Attention Mechanism

Unit 3: Multi-Head Attention and Positional Encoding

Unit 4: Transformer Architecture and Variants

Pre-training and Fine-tuning LLMs

Unit 1: Understanding Pre-training

Unit 2: Transfer Learning and Fine-tuning

Unit 3: RLHF and Alignment

Prompt Engineering and LLM Evaluation

Unit 1: Prompt Engineering Fundamentals

Unit 2: Advanced Prompting Techniques

Unit 3: LLM Evaluation Metrics

Bias Mitigation and Responsible LLM Deployment

Unit 1: Understanding Bias in LLMs

Unit 2: Mitigating Bias in LLMs

Unit 3: Responsible LLM Deployment