Python

**Improving Office in Franklinton** Physical location: Improving Office 330 Rush Alley Suite #150 Columbus, OH 43215 Schedule: 6:00 p.m.: Socialize, eat, and drink. Improving will be providing pizza and beverages. 6:30 to 8:00 pm. Main meeting and presentation(s). Topic: Type Annotations with John Cassidy We meet on the last Monday of each Month. Presentations are given by members and friends of this group. If you would like to do a presentation (small or large) on a python topic, please contact Central OH Python at centralohpython@gmail.com

**Improving Office in Franklinton** Physical location: Improving Office 330 Rush Alley Suite #150 Columbus, OH 43215 Schedule: 6:00 p.m.: Socialize, eat, and drink. Improving will be providing pizza and beverages. 6:30 to 8:00 pm. Main meeting and presentation(s). Topic: Exploration of Large Language Models and Programming with Chris Pazsint We meet on the last Monday of each Month. Presentations are given by members and friends of this group. If you would like to do a presentation (small or large) on a python topic, please contact Central OH Python at centralohpython@gmail.com

**New Dojo Location!** **Knotty Pine Brewing** 1765 W 3rd Ave, Columbus, OH 43212 We're going to try a new dojo location for a few weeks and see how it works Dojos are informal Python group study sessions where everyone interested in Python gathers to learn about Python, help others with Python, or just hang out. Everyone is welcome from Python beginners to experts. Bringing a laptop is encouraged (we'll have extension cords and power strips). If there's something you want to learn leave a comment on this invite so we can plan ahead. We're looking for topic suggestions and people interested in presenting at our monthly meetings. To this end we've set up a survey form at [https://docs.google.com/forms/d/15eBKF1nQQ2XS5gzD4rvhVRHMBEj7lJtHuA9wXupS3Uc](https://docs.google.com/forms/d/15eBKF1nQQ2XS5gzD4rvhVRHMBEj7lJtHuA9wXupS3Uc)

**First meetup of the Columbus AI Engineering group.** We’ll kick things off with a practical, beginner-friendly discussion on: **How LLMs like ChatGPT actually work — and how to build real applications with them.** We’ll cover: * what’s actually happening under the hood (at a high level) * why LLMs behave the way they do (hallucinations, prompt sensitivity, etc.) * how people are building real systems with them today * where things break in practice This will be a **short, informal talk (\~15–20 min)** followed by open discussion and Q&A. Whether you’re an engineer, builder, or just curious about how modern AI systems work, you’re welcome to join. No slides, no fluff — just real conversation about real systems. We’ll hang out afterward and get to know each other.

Use this link: https://us02web.zoom.us/j/85031832141?pwd=7Sa7wy8KlHqPhKxYQUl42uCsf8YawO.1 **Opening Talk:** Luisa will demo a sassy AI-powered plant built in FastAPI using GPT-4o to explore personality, dialogue design, and human-AI interaction. **Main Talk:** What about using certain CLIs puts a smile on your face and gets you telling all your friends and colleagues about it? The Unix philosophy emphasizes simplicity, modularity, and the idea that programs should do one thing well and work together. However, CLI programs are primarily used by humans. Programs that you actually enjoy using can achieve both of these aims of composability and human-centeredness. This talk explores what makes CLIs great: fast, trusted, and delightful. Through real-world examples from modern tools like uv, cargo, ripgrep, and GitHub CLI, you'll learn the design patterns that separate good CLIs from great ones. Whether you're building package managers, creating developer tools, or just curious why modern CLIs feel so much better, you'll leave with a practical checklist of techniques to apply to any CLI tool you build. **Agenda:** 7:00pm - Opening announcements 7:10pm - Opening Topic - Build an AI-powered, Sassy Speaking Plant 7:25pm - Main Topic - Designing Delightful CLIs with Python 7:50pm - Q&A

The Fellowship of the Star Schema: Transforming OLTP Data for Power BI One does not simply build reports on OLTP data. Join us on an epic journey from the depths of raw, normalized tables to the shining halls of a well-modeled star schema fit for Power BI greatness. We will demystify the differences between OLTP and OLAP, walk through star schema vs snowflake (and why Power BI has a clear favorite), and show you the compression differences between normalized and columnar storage that will make you never look at an OLTP model the same way again. We will cover the different types of dimensions, when to use them, and how to handle Slowly Changing Dimensions without losing your mind. You will leave knowing exactly how to identify a bad model, how to convert OLTP data into a clean star schema, and how to forge relationships that rule them all. Whether you are a data wizard, a curious hobbit, or somewhere in between, your models will never be the same.

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