AI for High Finance: Modeling, Decks & Recruiting

Use AI to build a SpaceX IPO model, banking pitch deck, and recruiting workflow for investment banking.

New

Created byMax Adams

Last updated 7/2026

English

What you'll learn

Use AI to accelerate finance research, source mapping, and model setup without losing analyst judgment.
Build a SpaceX IPO-style DCF model with revenue drivers, margin logic, UFCF, valuation, and checks.
Turn model outputs into an investment-banking-style PowerPoint deck with AI-assisted QA.
Use AI for bank research, networking, interview prep, and resume or LinkedIn positioning.

Course content

5 sections • 29 lectures • 2h 55m total length

1.1 Welcome: How To Use This Course8:35
1.2 Why AI Is Changing High Finance3:32
1.3 What AI Can Do vs What You Still Own6:13
1.4 The Analyst Stack7:33
Learn the analyst stack for finance: master a workflow using AI tools to build Excel models, PowerPoint decks, better recruiting outputs, and strong interview and networking strategies.
1.5 Common Mistakes and Compliance Boundaries6:21
Navigate common ai pitfalls in finance by enforcing confidentiality boundaries, avoiding hallucinations, validating assumptions and formulas, and polishing formatting, while explaining work using audit checklists.
1.6 How AI Will Impact Investment Banking Jobs17:57

2.1 Model Setup and Formatting Standards13:39
2.2 Researching the Company and Building the Source Map5:05
2.3 Historical P&L Extraction4:21
2.4 Revenue Build and Segment Drivers6:30
2.5 Expense Build and Margin Logic6:30
Build an expense forecast and define margin logic by mapping cost categories to revenue drivers, align opex with segments, and reconcile to adjusted EBITDA through non-gap adjustments.
2.6 EBITDA, D&A, Capex, and UFCF5:04
Bridge the operating model to unlevered free cash flow and valuation by linking EBIT, taxes, DNA, CapEx, and changes in networking capital within a simple DCF framework.
2.7 DCF Valuation and Sensitivity Output6:46
2.8 AI Model Audit and Manual Review5:14
Audit the model with big-picture questions on revenue, margins, and cash flow, then verify formulas using an audit checklist. Seek a second AI review before transforming it into a deck.

3.1 Banking Deck Structure and Slide Standards3:29
Move from Excel thinking to PowerPoint communication using a banking deck template to structure ideas and present a concise executive summary with a financial model overview.
3.2 Executive Summary and IPO Recommendation6:01
Develop an executive summary for an ipo pitch, leading with bottom line up front and framing a narrative with recommendation, company overview, valuation, model thesis, risks, and valuation takeaway.
3.3 Company Overview4:58
3.4 Market Overview and Tailwinds4:43
Learn to craft a market overview and tailwinds slide for all three business segments, including space connectivity and AI infrastructure, that supports the IPO story with credible sources and visuals.
3.5 Investment Thesis, Risks, and Rebuttals3:20
3.6 IPO Launch Plan3:47
Create an ipo launch plan slide with a four-phase visual timeline (equity story, governance readiness, investor education, launch and pricing) and immediate next steps for banking decks.
3.7 Model Screenshot Slides7:18
3.8 PowerPoint QA and Final Banking Polish5:56
Apply a rigorous PowerPoint QA process to polish a banking deck, using an audit checklist to ensure accurate numbers, consistent formatting, proper logos, and compelling management-team slides.

Requirements

Basic Excel or Google Sheets familiarity, basic PowerPoint or Google Slides familiarity, and access to an AI tool such as ChatGPT, Claude, or Gemini.

Description

This course contains the use of artificial intelligence.

AI is already changing how high-finance work gets done. The analysts who benefit most will not be the ones who blindly outsource their thinking to AI. They will be the ones who know how to use AI to move faster while still owning the sources, assumptions, formulas, judgment, formatting, and final explanation.

In this course, you will build a practical SpaceX IPO case study using modern AI workflows. You will use AI to help structure a financial model, research a company, create a source map, extract historical financials, build revenue and expense forecasts, bridge the model to unlevered free cash flow, construct a DCF valuation, and audit the model before relying on it.

You will also learn how to turn the model into an investment-banking-style PowerPoint deck. The course walks through banking deck structure, executive summary writing, company overview pages, market overview pages, investment thesis and risk slides, IPO launch plan slides, model screenshot slides, and final banking-style QA.

Finally, the course shows how to use AI in recruiting without sounding generic. You will learn how to research banks, groups, and bankers faster, draft more targeted networking messages, prepare for AI-related interview questions, and position the project on your resume and LinkedIn without overstating your experience.

The course is built for students and early-career finance professionals who want tactical AI workflows for investment banking, private equity, corporate finance, and adjacent high-finance roles. It is not a generic AI overview. It is a practical project-based course anchored around real deliverables: a model, a pitch deck, prompt libraries, checklists, and a recruiting story you can explain.

Who this course is for:

Undergraduate students, MBA candidates, and early-career finance professionals recruiting for investment banking, private equity, corporate finance, or adjacent roles.

AI for High Finance: Modeling, Decks & Recruiting

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Course content

AI-Forward Analyst Mindset6 lectures • 50min

AI-Assisted Financial Modeling8 lectures • 53min

AI-Assisted Investment Banking PowerPoint8 lectures • 40min

Recruiting With AI5 lectures • 26min

Final Resources and Next Steps2 lectures • 7min

Requirements

Description

Who this course is for: