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All upcoming events

16 listed worldwide, in date order.

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Get Fable 5 Quality From Low-Cost AI Models

EventAI & Machine LearningOnline
01:00Europe / Dublin
Online, France
Advanced AI Concepts - Global - Paris

This session teaches how to improve the quality of low-cost AI model outputs by designing effective prompts, workflows, and evaluation systems. It targets builders, business users, creators, and AI practitioners who want to optimize AI performance while managing cost and quality. Participants will learn practical frameworks to build better AI workflows without relying solely on expensive models.

Operators

Introduction to Generative AI (Guest Speaker)

EventAI & Machine LearningOnline
00:00Europe / Dublin
Online, France
Advanced AI Concepts - Global - Paris

This event offers an introduction to generative AI, covering basics like ChatGPT, Perplexity, and Claude. It is designed for those not yet familiar with advanced AI concepts seeking foundational knowledge. The session is led by an experienced military AI instructor to ensure clear and engaging learning.

OnlineFree to AttendStudents & Researchers

Global - Intro to Building With Pi: Your First Personal Harness

EventOnline
00:00Europe / Dublin
Online, France
Advanced AI Concepts - Global - Paris

In this class, we’ll explore Pi, a lightweight terminal-based coding agent designed to stay small at the core while becoming powerful through extensions, skills, prompt templates, themes, packages, custom models, and custom providers. Pi gives developers a hands-on way to bring agentic coding directly into their project directory, with practical controls for tools, sessions, model switching, project instructions, and automation. Students will learn how to install and run Pi, authenticate with subscription providers or API keys, start useful coding sessions, reference files, run shell commands, manage saved sessions, and use non-interactive prompt mode for repeatable workflows. From there, we’ll look at how Pi can be customized: adding project instructions with `AGENTS.md`, using skills and prompt templates, extending Pi with TypeScript modules, and understanding when to use Pi as an interactive assistant versus a programmable agent runtime. By the end, students will understand Pi as more than another coding chatbot: they’ll see it as a compact agent harness for building practical developer workflows, experimenting with model/provider setups, and creating reusable AI-assisted engineering patterns from the terminal.

Keeping a Pulse on the Cluster: Monitoring Presto at Petabyte Scale (Hands-On)

EventOnline
17:30Europe / Paris
Online, France
Presto Meetup - Paris

In this interactive, hands-on session, you'll deploy a distributed Presto cluster along with a complete observability stack using Prometheus, Grafana, JMX Exporter, and Alertmanager. You'll learn how to collect metrics, build dashboards, analyze query execution, monitor JVM health, and identify performance bottlenecks using real telemetry from a running cluster. Register here What you'll learn Understanding Presto's monitoring architecture Exposing Presto and JVM metrics using JMX Exporter Collecting metrics with Prometheus Building Grafana dashboards for cluster health and query performance Monitoring coordinators, workers, memory, CPU, and query execution Creating alerts for production incidents Troubleshooting common operational issues using observability Prerequisites Basic SQL knowledge Familiarity with Docker and Docker Compose A laptop with Docker installed Register here

Databricks: Build a Practical Data Foundation for AI

EventOnline
01:00Europe / Dublin
Online, France
Advanced AI Concepts - Global - Paris

Learn how to turn scattered data into reusable “bricks” for AI apps, dashboards, agents, and automation workflows. This live Mojo AI Studio class is for builders who want practical data architecture without enterprise fog. In this live Mojo AI Studio session, Scott will walk through the idea of Data Bricks: small, practical, reusable data components that can support AI apps, agents, dashboards, automations, and business workflows. We will look at how to think about data as building material: what to collect, how to structure it, how to clean it, how to preserve context, and how to make it useful for downstream AI systems. The goal is not to memorize a platform or chase buzzwords. The goal is to understand how real AI products need data to be shaped before they become reliable.