What Causes Bird Strikes

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prerequisites
Basic ChatGPT/AI chatbot usage
skills learned
File workflows with ChatGPT Python code generation with ChatGPT Hypothesis generation and research workflows Data extraction Data transformation and analysis
Thomas Nield and Arjun Umathanu
1 week · 4-6 hours per week · BEGINNER
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In this liveProject, you will act as a researcher investigating the causes of bird strikes in the aviation industry. You will work with a dataset and limited context, using ChatGPT to explore the data, generate insights, and guide your analysis. You will use ChatGPT to generate Python code, perform analysis, and challenge your assumptions to avoid bias. The project concludes with a structured summary of findings and exporting your data into a queryable SQL database.

This project is designed for learning purposes and is not a complete, production-ready application or solution.

project authors

Thomas Nield
Thomas Nield is a consultant, writer, and instructor. After a decade in the airline industry, he authored two books for O’Reilly Media and regularly teaches classes on artificial intelligence, statistics, machine learning, and optimization algorithms. Currently he teaches at the University of Southern California. In another endeavor, Yawman Flight, he is inventing a new category of flight simulation controllers and bringing them to market. He enjoys making technical content relatable and relevant to those who are unfamiliar or intimidated by it.
Arjun Umathanu
Arjun Umathanu is a Full Stack AI Engineer with over a decade of experience in software development. He currently works as Specialist 2 – Software Engineering at UST, where he has been contributing since 2019. He previously worked at Movate for nearly nine years. He specializes in TypeScript, JavaScript, Python, Go, Next.js, React.js, FastAPI, Flask, Django, and test-driven development. He has hands-on experience with tools such as Pytest, Vitest, Jest, React Testing Library, MSW, and Cypress. His expertise also includes AI-driven workflows such as prompt engineering, multi-agent orchestration, custom Model Context Protocol (MCP) server development and integrations, and Claude skills and plugin development. He also has experience in QA automation. Arjun has developed open-source tools such as shai hulud-scan (a supply-chain security scanner for JavaScript/TypeScript projects) and restx (a CLI HTTP client). He contributes to Manning liveProject series as an implementer, beta tester, and co-author, and regularly conducts technical training sessions. He is committed to simplifying complex technical concepts and making them accessible to a broader audience.

prerequisites

This liveProject is intended for beginners and casual users of generative AI who want to improve productivity across a wide range of tasks. No prior knowledge is required. However, you will need a ChatGPT Plus subscription.


TOOLS:
  • Basics of AI prompting (using ChatGPT Plus as an example)

TECHNIQUES:
  • Upload text and summarize its contents
  • Form hypotheses around stories and events
  • Interpret contributing factors in reports
  • Extract and transform data from multiple sources
  • Export datasets to formats such as HTML and SQLite
  • Perform analytics on tabular datasets
  • Identify correlation variables
  • Incorporate external context into datasets and reports
  • Generate reports based on analytical findings

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  • exclusive 50% discount on all purchases
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