ChatGPT Advanced Data Analysis is a revolutionary course offered by Vanderbilt University. This comprehensive program focuses on leveraging the power of natural language processing and AI to automate tasks in various domains without the need for programming expertise.
Throughout the course, participants will learn how to harness the capabilities of ChatGPT Advanced Data Analysis to automate tasks such as converting documents into visual presentations, extracting data from PDFs, and creating social media and marketing content from text and video transcripts. The course also delves into the fundamentals of prompt engineering, enabling users to optimize their interactions with the tool for maximum efficiency.
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The course modules cover a wide range of topics, from introducing ChatGPT Advanced Data Analysis and its use cases to tackling appropriate problems and understanding human and AI process planning. Participants will also learn error identification techniques and handling large documents and outputs.
Module 1 provides an overview of ChatGPT Advanced Data Analysis, comparing it with ChatGPT and introducing various practical applications. Participants will learn about prompt engineering and how to leverage the tool to automate tasks effectively.
Module 2 delves into the use cases of ChatGPT Advanced Data Analysis, including working with structured data, media, and small documents. Participants will explore how to turn conversations into software utilities and work with zip files for automation.
Module 3 focuses on identifying the right problems for ChatGPT Advanced Data Analysis, emphasizing appropriate use cases and problem-solving strategies. Participants will gain insights into achieving specific goals and fostering creativity.
Module 4 explores the planning process involving both human and AI in ChatGPT Advanced Data Analysis. It covers techniques for extraction, transformation, analysis, and creating plans, along with the concept of flipped interaction planning.
Module 5 provides insights into error identification techniques, error handling, and managing large documents and outputs. Participants will learn about consistency checking, building indexes, and effective strategies for error resolution.
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