An advanced, hands-on course for buy-side and sell-side equity research analysts. Use AI to analyze earnings calls and 10-Ks, build a sector coverage thesis, construct and stress-test comparable company analysis, source and red-team DCF assumptions, draft equity research reports, build sector-coverage assistants, and stay inside MNPI, Reg FD, and research-independence lines.
Equity research is moving fast, and analysts who can direct AI across earnings call transcripts, 10-K filings, sector coverage builds, and valuation models gain a meaningful edge. This advanced, free course is built specifically for buy-side and sell-side equity research professionals who already understand the fundamentals and want to put AI to work in their actual research workflow. You will learn to use AI to dissect earnings call language and 10-K disclosures, build sector and industry coverage theses, and stress-test the assumptions inside your DCF models and comparable company analyses.
The course goes well beyond setup. Dedicated lessons walk through drafting full equity research reports with AI assistance, building sector-coverage assistants using custom GPT configurations and Claude Projects, and wiring together multi-step research workflows with AI agents. Because compliance is non-negotiable in equity research, the final module covers how to stay inside MNPI rules, navigate Reg FD, maintain research-independence requirements, and validate AI output so nothing slips past your quality controls.
Whether you work on a sell-side desk covering a specific sector or you are a buy-side analyst managing a research process across multiple names, the lessons are grounded in practical tasks you face every day. The course is free to take, and completing all modules plus the final exam earns you a certificate of completion you can add to your LinkedIn profile or resume.
3 modules • 8 lessons
The course covers three core areas: equity research foundations with AI (earnings calls, 10-Ks, sector research), AI-assisted valuation (comparable company analysis, DCF assumption sourcing and stress-testing), and output plus compliance (drafting research reports, building sector-coverage assistants, multi-step agent workflows, and staying within MNPI and Reg FD rules).
Yes, the course is completely free. Analysts who finish all lessons and pass the final exam receive a certificate of completion, which you can add to your LinkedIn profile or resume.
This is an advanced course designed for buy-side and sell-side professionals who already have a working knowledge of equity research, financial statements, and valuation methods. You do not need prior AI experience, but you should be comfortable with DCF models and comparable company analysis before starting.
The course uses Claude and custom GPT configurations, including Claude Projects and custom GPT setups for building sector-coverage assistants. Multi-step research workflows using AI agents are also covered, so you will get hands-on practice with the tools most relevant to a professional research environment.
The final module is dedicated entirely to compliance, covering how to use AI while staying inside material non-public information (MNPI) rules, Regulation FD requirements, and research-independence standards. It also addresses how to validate AI output so you can be confident in the work before it goes into a report or client communication.
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