From Traditional ML to LLMs

Bridging the gap from ML basics to advanced LLMs

Created by: Liana Isayan
Data Science Solopreneur

What Will I Learn?

• Leveraging traditional ML knowledge for working with LLMs
• Hands-on experience with PyTorch for LLMs
• Deeply understand the details of Transformer architecture
• Unfold the use-cases of LLMs for different tasks
• Discover new evaluation metrics specifically for LLMs
• Perform Text Classification and Text Summarization in Python
• Get familiar with concepts like RLHF or OpenAI API
• Confidence to make the first steps in LLMs

Requirements

• Knowledge of traditional ML basic concepts and Python

Target audience

• Data scientists with good background in traditional ML but lacking any knowledge in LLMs