Cohort 3

Founder

Joel Damiani

Engineers and engineering leaders who build, deploy, and scale software systems.

Data scientists who apply statistical and ML techniques to extract insights from data.

Measuring and evaluating AI model performance, quality, and reliability for production use cases.

Applying AI tools and techniques to professional workflows — assign alongside more specific AI topics.

Building autonomous AI agent systems that take actions, use tools, and orchestrate multi-step workflows.

Operating and deploying large language models in production — fine-tuning, inference, monitoring, and cost optimization.

From agent fundamentals to a live multi-agent system

Author, ML for Trading · Applied AI

Stefan Jansen

Author, ML for Trading · Founder, Applied AI

Agent Engineering: Build, Evaluate, and Deploy AI Agents

Founder, Applied AI · Author, ML4T

Builds production ML and agent systems, then teaches the operating method.

<h3>Why I enrolled</h3>
<p class="p2-tall">I trade CME futures with systematic ML models and want to learn how to build and rigorously evaluate LLM agents, with a focus on leakage control, calibration, and multi-agent aggregation, so I can add a daily macro/event forecasting layer that feeds my existing regime framework.</p>
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<h3>What I’ll apply</h3>
<p class="p2-tall">Applying the evaluation discipline to my own trading research: one-change-at-a-time ablations, diversified models and data sources with correlation measured rather than assumed, evidence gates that allow abstention, and a selection/holdout acceptance gate before adopting any change to my strategies.</p>
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Certificate

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