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GenAI-Powered Data Analysis with Python Bootcamp

Published by O'Reilly Media, Inc.

Beginner to intermediate content levelBeginner to intermediate

From curiosity to confidence—explore data, uncover patterns, and create impact with Python and generative AI

What you’ll learn and how you can apply it

  • Develop fluency in using Python libraries such as pandas, Matplotlib, seaborn, and plotly to perform end-to-end data wrangling, analysis, and visualization
  • Apply exploratory data analysis techniques to clean, summarize, and transform real-world datasets, uncovering meaningful patterns and insights
  • Utilize generative AI tools to accelerate learning, troubleshoot code, and enhance analytical workflows through effective prompt engineering
  • Design dynamic and interactive data visualizations that communicate complex information clearly and effectively to a variety of audiences
  • Craft compelling data narratives by combining analytical results with AI-assisted summarization and storytelling techniques for stakeholder communication

Course description

The ability to analyze, interpret, and communicate insights from complex datasets while using AI as your assistant have become critical skills across industries.

Join expert Chester Ismay to learn the fundamentals of data analytics using Python while harnessing the power of generative AI. Through hands-on, real-world exercises, you’ll learn to clean, wrangle, and visualize data using Python libraries such as pandas, Matplotlib, seaborn, and plotly. You’ll not only build fluency in Python-based data workflows but also gain the ability to craft compelling data stories for diverse audiences using AI-augmented narrative techniques. In addition, you’ll strengthen your prompt engineering and critical communication skills by practicing how to engage with GenAI tools thoughtfully, clearly, and effectively. Whether you're an analyst looking to enhance your workflow, a professional seeking to make data-driven decisions, or a curious learner navigating the Python ecosystem, this bootcamp provides the essential skills and modern mindset needed to thrive in a rapidly evolving analytics landscape.

This live event is for you because...

  • You’re a professional looking to strengthen your data analysis and visualization skills using Python, and want to accelerate your learning with the support of Generative AI.
  • You’re a student, educator, or researcher seeking a hands-on introduction to Python-based data workflows and tools that make data exploration and storytelling more accessible.
  • You’re a data analyst, business analyst, or data enthusiast aiming to improve how you interpret, visualize, and communicate data-driven insights.
  • You’re curious about how generative AI tools like ChatGPT can serve as a learning partner, coding assistant, and storytelling collaborator in your data work.
  • You’re ready to move beyond static reports and spreadsheets to build compelling, interactive visual narratives that drive understanding and action.

Prerequisites

  • Basic familiarity with Python programming, including an understanding of core syntax, variables, and common data types (lists, dictionaries, etc.)
  • Some experience working with data in Python (loading CSV files or using pandas DataFrames) is helpful but not required
  • No prior experience with statistics or data visualization necessary

Recommended preparation:

Recommended follow-up:

Schedule

The time frames are only estimates and may vary according to how the class is progressing.

Day 1: Prompt to Wrangle—Clean, Explore, and Learn Python with GenAI

Data analytics kickoff (20 minutes)

  • Presentation: Data analytics, Python, and GenAI; framing GenAI; using GenAI to help with learning, debugging, and exploring
  • Group discussion: Your goals and where you get stuck when analyzing data

Pandas for data wrangling (55 minutes)

  • Presentation: DataFrames; loading files; inspecting structure; selecting columns/rows; filtering; sorting
  • Hands-on exercises: Load, clean, and examine a sample dataset
  • Demonstration: Prompting GenAI to explain what code is doing, and related questions
  • Q&A
  • Break

Transforming and aggregating data with pandas (65 minutes)

  • Presentation: Dealing with missing data; renaming columns; using groupby() and agg() for summarizing; creating columns
  • Hands-on exercise: Create summaries by group
  • Demonstration: Using prompt variations (short, step-by-step, analogy-based) to get GenAI to explain how groupby() works on an example
  • Q&A
  • Break

Exploring and learning from mistakes (55 minutes)

  • Presentation: Common pitfalls in data analysis; understanding error messages in pandas
  • Hands-on exercise: Troubleshoot broken code with GenAI prompts
  • Q&A
  • Break

Reflection (45 minutes)

  • Presentation: What you’ve learned so far and what GenAI can help with
  • Hands-on exercise: Ask GenAI for three ways to summarize your dataset and ask for three new questions to investigate next time
  • Q&A

Day 2: Visualize to Tell—Turn Data into Insightful Stories with GenAI

Visualizing with Matplotlib and seaborn (55 minutes)

  • Presentation: Matplotlib (bar, line, and scatterplots); seaborn (histograms, boxplots, violin plots)
  • Hands-on exercises: Create visualizations with appropriate labels
  • Demonstration: Using GenAI to answer “I want to visualize X—what plot should I use?” and related questions
  • Q&A
  • Break

Interactive plotly visuals (65 minutes)

  • Presentation: Quick and interactive charts with plotly to enable hovering, zooming, and drill-down functionality
  • Hands-on exercise: Create an interactive dashboard-style figure
  • Demonstration: Asking GenAI how to make a chart easier for execs to read, and other related questions
  • Q&A
  • Break

Storytelling with data with support from GenAI (55 minutes)

  • Presentation: What makes an insight compelling?; framing insights using comparisons, change over time, and benchmarks
  • Hands-on exercise: Write a three-sentence story about a key insight and use GenAI to create a concise summary for a stakeholder and a newsletter audience
  • Q&A
  • Break

How GenAI solves problems (35 minutes)

  • Presentation: How GenAI predicts text, works at a high level, and augments problem-solving; GenAI cautions and boundaries
  • Hands-on exercise: Try a prompt that could help you in your real-world work, ideally with data analysis
  • Q&A

Wrap-up (25 minutes)

  • Presentation: Recap of key technical and GenAI takeaways; resources (prompt templates, recommended tools and references)
  • Q&A

Your Instructor

  • Chester Ismay

    Dr. Chester Ismay is an experienced data science educator and consultant. Chester enjoys helping others get into data science, figuring out how to best practice and improve their skills. He is co-author of "Statistical Inference via Data Science: A ModernDive into R and the Tidyverse" available at https://moderndive.com/v2/ He likes leading education and data science teams to improve best practices based on data from the learning sciences. Throughout his career, he has worked in academia, as a corporate trainer, at tech bootcamps, and as an independent consultant in the fields of education, insurance, and sports analytics.

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Skills covered

  • Python
  • Pandas