Three-Project Series

Real-World Workflows with ChatGPT

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prerequisites
Basic ChatGPT/AI chatbot usage
skills learned
prompt engineering • file workflows with ChatGPT • Python code generation with ChatGPT • using AI to generate hypotheses and suggest research work • data extraction • transformation and analysis • image generation
Thomas Nield and Arjun Umathanu
3 weeks · 2-6 hours per week average · BEGINNER

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Step into the world of AI-powered problem solving. In this hands-on series of liveProjects, you will play the role of a librarian, an investigative journalist, and a data analyst—all with ChatGPT as your AI assistant. First, you will spark community discussion by creating engaging content around a classic American short story. Then, you will analyze a real NTSB report from a self-driving car accident, uncovering possible causes with the help of ChatGPT. Finally, you will work as a data analyst, using ChatGPT’s Python capabilities to explore a bird strike dataset from the FAA. Along the way, you will learn practical AI productivity techniques, integrate multimodal workflows, and develop the ability to use ChatGPT to enhance your thinking and decision-making.

These projects are designed for learning purposes and are not complete, production-ready applications or solutions.

here's what's included

Project 1 The Legend of Sleepy Hollow

In this liveProject, you will take on the role of a librarian using generative AI tools like ChatGPT to support a research project. You will develop effective prompts to analyze whether The Legend of Sleepy Hollow by Washington Irving is suitable for a new exhibition. After generating analysis with ChatGPT, you will extract relevant insights and use them to create engaging materials for the exhibition.

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$29.99 $19.99
Project 2 Analyzing an Accident Report

In this liveProject, you will use ChatGPT to investigate an in-depth report of a self-driving car accident. You will acquire the source material, upload it, and use ChatGPT to generate and refine hypotheses about why the accident occurred. You will incorporate external context to deepen your analysis, turning vague questions into structured insights and expanding your research beyond a single document.

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$29.99 $19.99
Project 3 What Causes Bird Strikes

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.

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books resources

When you start each of the projects in this series, you'll get full access to the following books for 90 days.

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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 series is intended for beginners and casual users of generative AI who want to improve productivity across a wide range of tasks—from ideation to data analysis. 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

features

Self-paced
You choose the schedule and decide how much time to invest as you build your project.
Project roadmap
Each project is divided into several achievable steps.
Get Help
While within the liveProject platform, get help from fellow participants and even more help with paid sessions with our expert mentors.
Compare with others
For each step, compare your deliverable to the solutions by the author and other participants.
book resources
Get full access to select books for 90 days. Permanent access to excerpts from Manning products are also included, as well as references to other resources.