Cohort 2

Amir Vahid

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.

Build a multi-agent forecasting system you can audit — in one day.

Author, ML for Trading · Applied AI

Stefan Jansen

Author, ML for Trading (Ch. 24: agents) · Founder, Applied AI

Engineering a Multi-Agent Forecasting System

ML for Trading · Applied AI · Since 2013

Author, ML for Trading · Founder, Applied AI · Investing since 2013

<h3>Why I enrolled</h3>
<p class="p2-tall">My goal is to learn how to design and engineer reliable multi-agent systems that can autonomously research, reason, collaborate, and produce high-quality government proposals. I want to apply these techniques to opportunities such as SBIR/STTR, DoW, NSF, DOE, and other federal funding programs—using specialized agents for solicitation analysis, technical research, compliance checking, proposal writing, budgeting, reviewing, and final quality control. Ultimately, I want to build a reusable proposal-generation system that improves proposal quality, reduces preparation time, and increases the probability of winning government contracts and grants.</p>
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<h3>What I’ll apply</h3>
<p class="p2-tall">I’m most excited to apply the multi-agent architecture to building an end-to-end system for government proposal development. I want to create specialized agents for opportunity discovery, solicitation analysis, technical research, compliance, proposal strategy, writing, budgeting, and critical review, with agents collaborating and iteratively improving the final submission. My goal is to move beyond simply using LLMs as writing assistants and build a reliable, reusable agentic workflow that can produce higher-quality proposals for programs such as SBIR/STTR, DoW, NSF, and DOE while significantly reducing the time required to prepare each submission.</p>
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Certificate

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