AI5 ACADEMY · APPLIED AI FINANCE LABS · UPDATED SEPTEMBER 2026
Applied AI for Financial Analysis, Investment Research & Financial Modelling
Build checked financial models, forecasts, valuations, company research and reusable AI research workflows through live finance labs.
Live Online3 sessions per week60–90 minutes per sessionAI + domain practice
What You Will Actually Do
Learn by Doing → Build → Check → Improve → Apply
Approximately 20% concepts and 80% practical application across the program. This is a teaching direction, not a fixed split for each class.
- Linked three-statement financial model
- Driver-based rolling forecast
- DCF and comparable-company valuation
- Cited earnings and company research note
- Buyer universe and diligence brief
- Reusable financial research agent
- Listed-company analyst capstone
12 weeks · 36 live sessions · approximately 36–54 instructor-led hours. Three sessions per week, generally 60–90 minutes each. Assignments, practice and portfolio work outside class are additional.
India and international Live Online learners can request a suitable cohort. Confirm local times and time-zone differences before enrolment.
Every finance lab includes a review.
Concept → Demonstration → Guided Lab → Independent Task → Verification → Professional Output.
Start with a realistic problem and source material. Watch the trainer perform the workflow, build it yourself, check the result, improve it and submit a usable workbook, report or investigation record.
Source & retrieveAnalyse & calculateCite & reconcileVerifyHuman review & approve
Verification exercises include invented numbers, incorrect calculations, broken formulas, unsupported assumptions, stale market information, wrong citations, incomplete or conflicting documents, missing data, outliers and misleading summaries. Keep a record of the error, correction and reviewer decision.
NEXT START OPTIONS
Choose a live batch.
COURSE OVERVIEW
What this course
is built to do.
Build checked financial models, forecasts, valuations, company research and reusable AI research workflows through live finance labs.
Each module combines a live trainer demonstration, guided lab, assignment and review before the next stage.
CONNECTED CAREER DIRECTIONS
Financial analysisInvestment researchFinancial modellingCorporate finance
IS THIS COURSE RIGHT FOR YOU?
Choose it for the right reason.
You understand basic finance and want to use AI in analyst work
You want checked financial models and cited research
You want a practical listed-company portfolio
YOUR LEARNING ARC
From guided foundation to finished work.
Source & analyse
Work from filings, statements and earnings material.
Model & forecast
Build linked statements and driver-based scenarios.
Value & research
Develop DCF, comps and cited analyst notes.
Automate & verify
Create a reusable research workflow and defend the capstone.
INDUSTRY TASKS
Practise the work, not only the tool.
- Build a three-statement model
- Create a forecast and valuation
- Prepare an earnings review and research memo
- Build and test a research agent
PRO
LED
LED
YOUR TRAINING TEAM
Learn from experienced working professionals.
Live demonstrations, guided practice and direct project feedback are part of the course. Trainers update examples and tool coverage as professional practice changes.
WHAT YOU WILL BE ABLE TO DO
Course outcomes
01
Source-first financial research
Company source register and extraction workbook
02
Financial statement analysis
Verified analyst summary
03
AI + Excel financial modelling
Model template and formula-review log
04
Three-statement model: historical links
Linked historical three-statement model
05
Forecasting and model drivers
Driver-based forecast and assumptions register
06
Valuation with AI assistance
DCF model and sensitivity table
07
Peers and transaction research
Comparable-company review and valuation snapshot
08
Company, sector and earnings research
Cited earnings and sector note
09
Investment research outputs
Analyst note and catalyst/risk map
010
Investment banking workflows
Company profile, buyer universe and pitch draft
011
Reusable financial research agents
Reusable research workflow and failure-test log
012
Analyst capstone and professional review
Financial model, research memo, executive presentation and signed review checklist
TAKE THE NEXT STEP
Need fees, syllabus or the right batch?
An AI5 Academy advisor can help you compare mode, schedule and starting level.
DETAILED COURSE FLOW
12 learning modules
Financial Data → Company Analysis → Modelling → Forecasting → Valuation → Research → Investment Workflows → AI Agents → Verification → Capstone. Three live sessions each week.
Week 1 — Source-first financial research
Build a reproducible company evidence pack.
CORE TOPICS
- Annual reports and regulatory filings
- Investor presentations, releases and transcripts
- Financial statements and spreadsheets
- Source dates, units, currencies and permissions
GUIDED PRACTICE
Collect public materials for a listed company, ask AI to extract cited figures and compare every material figure with its source.
MODULE DELIVERABLE
Company source register and extraction workbook
Week 2 — Financial statement analysis
Explain how the business generates earnings and cash.
CORE TOPICS
- P&L, balance sheet and cash flow
- Ratios, trends and margins
- Working capital, debt and profitability
- Cash generation and business drivers
GUIDED PRACTICE
Produce an AI-assisted analyst review, reconcile statements and flag conflicting periods or definitions.
MODULE DELIVERABLE
Verified analyst summary
Week 3 — AI + Excel financial modelling
Build a model whose logic can be inspected.
CORE TOPICS
- Model structure and assumptions
- Formula creation, links and updates
- AI-native spreadsheet workflows
- Error tracing and calculation checks
GUIDED PRACTICE
Use Excel or Sheets with AI to build a model shell and repair seeded formula errors in an inherited workbook.
MODULE DELIVERABLE
Model template and formula-review log
Week 4 — Three-statement model: historical links
Connect the financial statements with checked schedules.
CORE TOPICS
- Income statement, balance sheet and cash-flow links
- Debt, working capital and fixed assets
- Sign conventions and units
- Balance and cash checks
GUIDED PRACTICE
Link historical statements and reconcile opening and closing cash; explain each AI-generated formula.
MODULE DELIVERABLE
Linked historical three-statement model
Week 5 — Forecasting and model drivers
Extend the model using defensible business assumptions.
CORE TOPICS
- Revenue and cost drivers
- Working-capital assumptions
- Debt and capex forecasts
- Scenario and sensitivity testing
GUIDED PRACTICE
Build forecast statements for the case company. Test cash, balance-sheet and debt checks under multiple scenarios.
MODULE DELIVERABLE
Driver-based forecast and assumptions register
Week 6 — Valuation with AI assistance
Calculate and challenge a valuation range.
CORE TOPICS
- DCF and cash-flow logic
- Discount-rate and terminal assumptions
- Enterprise-to-equity bridge
- Valuation sensitivity and checks
GUIDED PRACTICE
Build a DCF, independently recalculate key outputs and document where an AI suggestion was rejected.
MODULE DELIVERABLE
DCF model and sensitivity table
Week 7 — Peers and transaction research
Compare companies on a consistent basis.
CORE TOPICS
- Comparable-company selection
- Multiples, periods and normalisation
- Precedent transaction concepts
- Source availability and comparability limits
GUIDED PRACTICE
Build public-data comps, verify market-data dates and record exclusions; review one public transaction with clear missing-data notes.
MODULE DELIVERABLE
Comparable-company review and valuation snapshot
Week 8 — Company, sector and earnings research
Turn source material into a cited research argument.
CORE TOPICS
- Earnings and transcript analysis
- Competitor and sector comparison
- Guidance versus results
- Contradiction and citation checking
GUIDED PRACTICE
Compare a release, transcript and filing. Test an AI summary for missing caveats and inconsistent claims.
MODULE DELIVERABLE
Cited earnings and sector note
Week 9 — Investment research outputs
Express a testable thesis with risks and alternatives.
CORE TOPICS
- Company profile and investment thesis
- Catalysts and risk map
- Valuation and peer evidence
- Analyst-note structure
GUIDED PRACTICE
Write a research memo, separate fact from judgement and include evidence that challenges the thesis.
MODULE DELIVERABLE
Analyst note and catalyst/risk map
Week 10 — Investment banking workflows
Prepare useful deal-research materials from public sources.
CORE TOPICS
- Company profiles and buyer universe
- Transaction research
- Diligence and meeting preparation
- Pitch preparation and deal-material summaries
GUIDED PRACTICE
Prepare a buyer screen, diligence question list and short pitch using public materials. Check every company claim and comparable.
MODULE DELIVERABLE
Company profile, buyer universe and pitch draft
Week 11 — Reusable financial research agents
Move from one-off prompts to controlled repeatable research.
CORE TOPICS
- Approved apps, connectors and APIs
- ChatGPT Work or equivalent workflows
- n8n or Make
- Retrieval, citations, logs, freshness and approval gates
GUIDED PRACTICE
Build a Research Agent: company → filings → earnings → transcripts → peers → ratios → valuation inputs → citations → analyst review. Test stale data and missing sources.
MODULE DELIVERABLE
Reusable research workflow and failure-test log
Week 12 — Analyst capstone and professional review
Defend the full research and modelling workflow.
CORE TOPICS
- Historical analysis and drivers
- Model, forecast and valuation review
- Research memo and executive presentation
- AI disclosure and verification evidence
GUIDED PRACTICE
Submit and defend the listed-company project. Recheck sources, dates, assumptions, formulas and citations; show where human judgement changed an AI result.
MODULE DELIVERABLE
Financial model, research memo, executive presentation and signed review checklist
HOW THE TRAINING WORKS
Learn it. Apply it. Get it reviewed. Improve it.
Every important skill moves through explanation, demonstration, guided use and independent application. Trainer feedback is used to revise the work before it becomes part of the final portfolio.
Concept briefing
The trainer explains the principle, use case, limitations and the quality standard expected.
Live demonstration
A complete task is demonstrated while the trainer explains decisions, checks and common mistakes.
Guided lab
Learners repeat the method with support, ask questions and correct problems during the session.
Applied assignment
The same method is used on a different brief so the learner must make independent decisions.
Review and revision
Work is checked against a rubric, revised after feedback and prepared for project presentation.
PROGRESS IS CHECKED THROUGHClass exercisesModule deliverablesProject reviewsFinal capstone presentation
PORTFOLIO WORK
Projects you can show
Linked three-statement financial model
Plan, produce, test and present a finished piece with trainer feedback.
Driver-based rolling forecast
Plan, produce, test and present a finished piece with trainer feedback.
DCF and comparable-company valuation
Plan, produce, test and present a finished piece with trainer feedback.
Cited earnings and company research note
Plan, produce, test and present a finished piece with trainer feedback.
Buyer universe and diligence brief
Plan, produce, test and present a finished piece with trainer feedback.
Reusable financial research agent
Plan, produce, test and present a finished piece with trainer feedback.
Listed-company analyst capstone
Plan, produce, test and present a finished piece with trainer feedback.
TAKE THE NEXT STEP
Need fees, syllabus or the right batch?
An AI5 Academy advisor can help you compare mode, schedule and starting level.
TOOLS COVERED
ChatGPTClaudeGeminiMicrosoft CopilotExcelGoogle Sheetsn8n / Make
Tool coverage may be updated when the industry changes. Core methods remain part of the course.COMMON QUESTIONS
Before you apply
How much live teaching is included?
12 weeks with 3 sessions each week: approximately 36 sessions and 36–54 instructor-led hours. Each session is generally 60–90 minutes. Independent assignments are additional.
＋Do I need finance or coding knowledge?
Basic financial-statement understanding and spreadsheet formulas are required. AI usage starts from beginner level; no programming prerequisite. Ask for prerequisite guidance before joining.
＋Are expensive data platforms included?
No paid financial database, enterprise AI subscription or proprietary banking system is assumed. Core work uses public company sources. Any paid access must be confirmed separately.
＋Does this replace CFA, CA or MBA study?
No. It teaches applied AI workflows for finance professionals and learners with suitable foundations. It does not replace professional qualifications or provide investment advice.
＋Can learners outside India join?
Live Online delivery supports India and international learners, subject to a suitable confirmed cohort and local time-zone checks.
＋How is learning assessed?
Practical labs, model reviews, cited research, verification tasks and a listed-company capstone with a research memo and executive presentation.
＋Do I need coding experience?
No, unless the course level says otherwise. Your advisor will check the right starting level.
＋Are classes live or recorded?
Classes are instructor-led Live Online.Recordings may support revision but do not replace class.
＋Will I receive a certificate?
Ask admissions to confirm the completion document and assessment requirements for your cohort. No external professional certification is implied.
＋Can working professionals join?
Yes. Three live sessions per week, generally 60–90 minutes each. Confirm a suitable cohort and time zone before joining.
＋Tools follow the work.
| Workflow | Tools and materials | Access |
|---|---|---|
| AI and spreadsheets | ChatGPT, Claude, Gemini, Microsoft Copilot; Excel and Google Sheets. ChatGPT for Excel or Google Sheets where enabled. | Use the cohort’s approved assistant and spreadsheet environment. Paid accounts and usage limits are confirmed before enrolment. |
| Research and financial data | Annual reports, filings, releases, investor presentations and transcripts. Provider workflow context: LSEG, FactSet, S&P Global, Daloopa, PitchBook, Crunchbase and Quartr. | Core projects use public sources. Commercial databases and ChatGPT for Financial Services access are not included unless separately confirmed in writing. |
| Repeatable workflows | ChatGPT Work or equivalent approved agentic workflows, apps/connectors, n8n, Make and APIs. | No-code/low-code builds with approval gates. Paid connectors, API credits and enterprise systems depend on confirmed access; equivalent dataset-based exercises support the learning goal. |
Use public, synthetic or approved sanitised data. Never upload confidential client information without permission. Product references do not imply partnerships.
Assessment through professional work
Assessment centres on lab completion, workflow assignments, model or case review, research outputs, verification exercises and the final capstone. Short quizzes support practice. Submit source references, an assumptions review, calculation and formula checks, citation and freshness checks, and a human approval record with every major output.
Listed-company analyst capstone
Select a listed company; collect source material; analyse historical financials and business drivers; build or update a three-statement model; forecast; value the company; review earnings and transcripts; compare peers; identify risks and catalysts; write a research memo; and produce an executive presentation. Include AI-use disclosure, the verification performed and examples where human judgement changed the AI result.
These outputs provide portfolio evidence of practical learning. The course does not replace CA, CFA, MBA or regulated qualifications and does not provide investment advice or guarantee employment, accuracy, compliance or investment returns.
Learn with domain specialists who use AI in their work.
AI5’s trainer standard combines relevant professional practice, strong current AI usage and the ability to teach live practical workflows. Finance, accounting, audit, FP&A, research, modelling or AML experience must match the subject taught.
Trainer selection requires a live workflow demonstration, error checking and clear answers to domain questions. Sessions call for active builds, learner coaching and project review. Ask admissions for the assigned trainer’s background before joining.
Training for corporate teams
Finance departments, accounting, FP&A, internal audit, banks, NBFCs, fintech, investment, asset-management and compliance teams can request a program built around their responsibilities. Organisation-specific workflows use approved datasets subject to privacy and security rules. Duration, scope and pricing are agreed separately.
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Choose your schedule.
Online or offline. Weekdays or weekends. Regular or fast track. Speak with an AI5 Academy advisor about the right starting level.