Summary

Large Language Models (LLMs) are powerful tools that put state-of-the-art AI capabilities at the tip of our fingers. They can process large amounts of data, understand nuance and context, and perform complex tasks at our request. Over the past few years, LLMs have multiplied as have the tools specially built to leverage their capabilities.

In this course, you will learn how to use large language models to perform data science tasks such as summarization, translation, named entity recognition, audio generation, and data processing. We’ll explore the possibilities afforded by the tools and APIs developed by OpenAI, Hugging Face, LangChain, and Pandas AI and how best to apply them to our data science work.

Program

  • Generative AI for Data Science

    • Generative AI

    • Large Language Models

    • OpenAI

    • HuggingFace

    • LangChain

  • Prompt Engineering for Data Science

    • Output formatting

    • Prompt Techniques

    • Zero-Shot and Few-Shot Prompting

    • Chain of Thought

  • Natural Language Processing with HuggingFace

    • Named-Entity Recognition

    • Part-of-Speech Tagging

    • Summarization

    • Question Answering

  • Text to Speech with Open AI

    • The Whisper model

    • Generatinag audio from text

    • Audio transcription

    • Automatic Translation

  • Pandas AI

    • Pandas AI library structure

    • Natural language querying

    • Data cleaning

    • Data visualization

Resources