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4 hrs
Free 101 course
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Live Jobs

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Goldman Sachs EY Deloitte. KPMG J.P. Morgan Houlihan Lokey AlphaSense

Programmes

Start free. Go live when you're ready.

One free recorded 101 to build the foundations. One live programme that takes you to job-ready, with AI in every module.

01Start free, today

Free · Recorded

Financial Modelling & Equity Research 101

The foundations every analyst interview assumes: Excel that behaves, the three statements as one model, a first DCF, and how equity research is actually written. Six recorded sessions, about four hours, free.

6 recorded sessions About 4 hours Working files included

You'll cover

  • Excel for modelling: setup, shortcuts and a model structure that survives review
  • Reading the three statements like an analyst, then linking them into one model
  • Valuation basics: DCF concepts and a simple DCF you build yourself
  • Equity research 101: the annual report, the thesis and the one-page note

02Go live when you're ready

Launching batch

Financial Modelling in the World of AI

Build investment-grade models and use AI to work 10x faster. The only programme that teaches traditional finance and modern AI workflows as one skill, live, with a practitioner beside you.

36 live sessions 60 hours AI in every module Certificate

What's included

  • 10+ models built live — 3-statement, DCF, comps, LBO, M&A
  • Three sector models and three industry analyses, built with the class
  • A capstone: model, initiating-coverage note and a stock pitch to a panel
  • AI research and modelling workflows — ChatGPT + Copilot, with verification guardrails
  • Mock interviews, timed modelling tests and a resume rebuilt in Resume Studio
  • Live job openings in these roles on WhatsApp
See the full curriculum

What you'll learn

Course Curriculum

Seven modules, in the order a desk would teach them. Each one pairs the finance skill with the AI workflow practitioners actually use, ends with something you've built, and is assessed the way a hiring team would assess it.

60 hours of live, hands-on learning
  • Model architecture: inputs, calculations, outputs; the colour and layout conventions every bank uses
  • Keyboard-only modelling: navigation, formatting and auditing shortcuts that double your speed
  • The analyst toolkit: INDEX/MATCH, XLOOKUP, OFFSET, dynamic arrays, structured references, named ranges
  • Power Query: pull, clean and refresh data from annual reports, screeners and exchange filings
  • Data tables, Goal Seek and scenario switches; circularity and iterative calculation done safely
  • A checks page: balance checks, error flags and an audit trail a reviewer can follow
AI built inGenerate and debug formulas with Copilot in Excel; turn a messy PDF table into a clean, typed dataset with one prompt, then reconcile it to source.
You'll buildYour own model template: conventions, checks page, scenario switch and shortcut sheet, reused in every module that follows.
Assessed byA timed Excel build: rebuild a broken model against the clock, with the checks page green.
  • The three statements the way an analyst reads them: what moves, what links and what a reviewer looks for first
  • Income statement → balance sheet → cash flow: every linkage, so the model balances by construction
  • Revenue recognition, capitalised vs expensed, depreciation and amortisation schedules
  • Working capital drivers (DSO, DIO, DPO), capex and PP&E roll-forwards, debt and interest schedules, cash sweep
  • Quality of earnings: one-offs, normalisation, common-size and ratio analysis, DuPont
  • Annual report walkthrough: notes, segments, related parties, contingent liabilities and red flags; Ind AS vs IFRS differences that change a model
AI built inSummarise a 200-page annual report to the twenty numbers that matter, with page references; then cross-check every one against the source, because the model is only as good as its inputs.
You'll buildA fully linked, balancing 3-statement model of a listed Indian company, with historical analysis and a normalised base year.
Assessed byCase study 1: a financial-viability analysis presented in 10 minutes, then defended.
  • Time value of money, CAPM and cost of equity with Indian inputs: G-sec risk-free rate, equity risk premium, beta relevering
  • WACC step by step; target vs actual capital structure; when a private-company discount applies
  • Free cash flow to firm vs to equity; forecasting drivers, not line items; mid-year convention
  • DCF from scratch: explicit period, terminal value by Gordon growth and exit multiple, sanity checks against implied multiples
  • Enterprise value to equity value bridge: net debt, leases, minorities, associates, preference capital
  • Relative valuation: EV/EBITDA, EV/Sales, P/E, P/B, PEG; peer selection, calendarisation and when a multiple lies
AI built inDraft a peer set and pull multiples with AI in minutes, then verify every figure by hand and document the source, the discipline that separates an analyst from a chatbot.
You'll buildA DCF plus trading-comps valuation of your module-2 company, with a football-field chart and a one-page valuation summary.
Assessed byA valuation viva: defend your WACC, terminal value and peer set to a practitioner.
  • Scenario and sensitivity analysis that survives an MD’s questions: data tables, tornado charts, base/bull/bear
  • Precedent transactions, control premiums and synergies; sum-of-the-parts for conglomerates and holding companies
  • LBO mechanics: sources and uses, debt tranches, cash sweep, IRR and MOIC, what a sponsor actually pays for
  • M&A modelling: purchase price, accretion/dilution, pro-forma balance sheet, purchase price allocation basics
  • Valuing financials: dividend discount and excess-return models, why banks trade on P/B and ROE
  • Model audit: the errors reviewers catch most, and a review checklist you run before anyone else does
AI built inStress-test your assumptions with an AI reviewer prompt, log every change with a reason, and produce a one-page assumptions memo automatically.
You'll buildAn LBO and a merger model on a real deal case, with a returns waterfall and a sensitivity page.
Assessed byCase study 2: an M&A recommendation, deal structure and returns, presented as a deal team would.
  • FMCG: volume × price × mix revenue build, distribution reach, gross margin and advertising intensity, capex-light cash generation; valued on DCF and EV/EBITDA
  • IT services: headcount, utilisation and billing-rate engine, attrition, INR/USD sensitivity, EBIT margin bridge, DSO; valued on DCF and P/E
  • Banking: a balance-sheet-driven model, loan growth, NIM, CASA, credit cost and GNPA, capital adequacy; valued on excess returns and P/B vs ROE
  • Three sessions per sector: build the operating model, forecast and value it, then stress-test and present it
  • Every model built live, start to finish, with the class; you finish each session with a working file
  • Sector KPIs, what management commentary really means, and how a sell-side note is built from the model
AI built inResearch assumptions with AI and keep the source links; auto-generate model checks and a variance summary before you present; never let a number in without a source.
You'll buildThree complete sector models you can open in an interview, each with a valuation summary and a stress-test page.
Assessed byA model review round per sector, scored on structure, accuracy, assumptions and presentation.
  • The top-down method: macro themes → industry structure → competitive position → unit economics → what it means for value
  • Pharma and healthcare: regulation, generics vs specialty, API supply chains, pricing and pipeline
  • Automobiles and EV: volumes and cycles, the EV transition, ancillaries, policy and localisation
  • Infrastructure and cement: capacity utilisation, pricing power, order books, working capital and leverage
  • Porter’s forces, value chain and margin pools; turning analysis into a one-page investment view
  • Capstone: pick a company in one of the industries, build the model, write the initiating-coverage note and deliver the pitch
AI built inBuild an industry brief in an hour with AI, then fact-check it like an analyst: claims traced to filings, regulator releases and company data, and the gaps flagged honestly.
You'll buildThree industry notes and a capstone package: model, initiating-coverage note and a 5-minute stock pitch.
Assessed byCapstone pitch to a practitioner panel, with Q&A, and written feedback on the note and the model.
  • Rebuild your resume in IDB Resume Studio: bullets a hiring MD reads, scored against 18 checks, tailored per job description
  • Interview preparation: the technical question bank, timed modelling tests, guesstimates and stock-pitch delivery
  • Mock interviews: one technical round and one HR round, with feedback you can act on the same week
  • AI workflows in finance: prompt libraries, Copilot in Excel, research and monitoring pipelines, and what you must never paste into a model
  • Verification and confidentiality guardrails: when AI is a first draft, when it is a reviewer, and when it stays out
  • A job-search system: live openings on WhatsApp, an applications tracker and a 30-60-90 plan for your first quarter in the role
AI built inAssemble your personal AI workflow kit for research, modelling, writing and monitoring, each step with a verification gate.
You'll buildA finance-ready resume, a portfolio of every model you built, and a workflow kit you take into your first week.
Assessed byMock technical and HR interviews, scored; and a final review of your portfolio.
36 sessions · 60 hours · 7 modules · 1 capstone pitch

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Why I Started IDB

AI is automating the surface. Excellence goes deeper.

I spent 8 years in core finance. I've seen what gets people into rooms that pay well — it's not a certificate. It's knowing how to think from first principles and being ready when the opportunity arrives.

Most institutes are still teaching 2012 curricula for ₹1 lakh. Getting students "placed" in 4–5 LPA ops roles. Not teaching them to think. Not building them to interview.

So after 8 years, I started IDB to give back — with courses, lifelong mentorship, and a monthly call with every single student.

My goal: finance professionals at ₹30+ LPA in 5 years. Walk into your first interview already thinking like a 1-year analyst. Know what to do before anyone tells you. That's how you beat the competition — and the algorithm.

Excellence doesn't get automated. It gets rewarded.

Founder, IDB Learning

Finance Jobs

This week's top roles.

Hand-picked from top finance MNCs. Updated every Friday

View all jobs
Big 4 High Paying

EYP – DME Staff, Business Modelling

Ernst & Young

Kochi 1–3 yrs

Est. salary

₹8 – 14 LPA
High Paying New

Associate — Corporate Valuation Advisory

Houlihan Lokey

Pan India 2–5 yrs

Est. salary

₹10 – 18 LPA
Core Finance Fresher–2yr

Analyst — Financial Modeling

AlphaSense

Bengaluru Fresher–2 yrs

Est. salary

₹6 – 10 LPA

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The live batch is built exactly for roles like these. Start with the free 101 today.

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Reviews

What students say.

4.9 average from 1,000+ students

The Financial Modelling course I took at Imarticus completely changed how I work. The way a DCF was broken down and tied to how real desks actually think is something no textbook ever gave me. I walked out building models with genuine confidence.

AR

Ankit Raghuvanshi

Financial Analyst, Mumbai

I reached out on WhatsApp just for a little guidance, and it turned into proper mentorship right up to my final interviews — prep, what to expect, how to frame my answers. I landed a role at Goldman Sachs. I never expected that much from one message.

MS

Megha Sethi

Analyst, Goldman Sachs

I've been mentored for over 4 years now and it's genuinely been the difference-maker in my career. I came from an HR background and was guided through my entire switch into finance — and recently into a core finance role. The constant motivation kept me going whenever I doubted myself.

SM

Saumya Mohnani

Finance Associate, Delhi

The Imarticus sessions changed how I look at companies. Every concept came with a real example you could actually use. Easily the most practical finance teaching I've had.

RK

Rohan Kapoor

Equity Research, Bengaluru

A simple WhatsApp doubt turned into months of honest mentoring. I was never treated like a stranger — just patient answers and a constant push to aim higher. I'm in a much better role today because of that guidance.

NV

Neha Verma

Credit Analyst, Gurugram

What stood out was the genuine care for my career, not just the syllabus. From resume to interviews, the support was end-to-end. I finally made the switch into finance I'd been chasing for two years.

AN

Aditya Nair

FP&A Analyst, Pune

Questions

Everything you might want to ask.

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