FinTech and Financial Platforms

Andrew Ng (Coursera ML) remains the #1 ML foundations recommendation globally. StatQuest for intuitive ML explanations with zero jargon. Sentdex for applied ML in trading. Krish Naik bridges Hindi ML education for Indian students with strong practitioner credibility.

Credit Default Prediction Model

Build a binary classification model to predict whether a loan will default. Use a public credit dataset (e.g. LendingClub from Kaggle, or RBI published NPA data). Train at least two models (logistic regression + random forest). Evaluate using AUC-ROC, precision/recall, and confusion matrix. Write a business interpretation: what does a 0.1% improvement in AUC mean for a bank's loss rate? Package as a Jupyter notebook and a 1-page PDF summary.

Time box: 5-7 days

Data/source: Kaggle credit datasets (free), LendingClub public data

Built credit default prediction model using logistic regression and random forest; achieved AUC of 0.XX; interpreted results in terms of bank loss rate reduction.

Alex the Analyst is the most recommended SQL educator on Reddit r/learnSQL and r/dataanalysis for business/finance contexts — his beginner course has millions of views across multiple platforms.

Financial Transactions Database - Analyst Query Pack

Design and build a SQLite database of simulated financial transactions (imagine a mutual fund's trade log: trade date, security ID, ISIN, quantity, price, fund name, asset class). Populate it with at least 500 rows of realistic data. Then write SQL queries answering 10 analyst questions: total AUM by fund, top 5 stocks by value, daily P&L, sector allocation, and more.

Time box: 3-4 days

Data/source: Simulated data (you generate it), NSE ISIN codes from NSE website

Designed financial transactions database in SQLite and wrote 10 analyst queries covering AUM, sector allocation, P&L, and portfolio attribution.

Sentdex is the consensus Python-for-finance community pick — cited by professional quants on GitHub, Quora, and r/algotrading. Harvard's CS50P for rigorous fundamentals first. Krish Naik for Hindi. Reddit r/learnpython and r/algotrading consistently recommend CS50P → Sentdex as the path.

Financial Time Series Analysis Notebook

Build a Python notebook that pulls 3 years of price data for 5 NSE stocks using yfinance, calculates daily returns, rolling volatility, and Sharpe ratio for each, plots correlation heatmaps and cumulative return charts, and outputs a one-page PDF summary. The notebook must be clean enough to share with an employer as a portfolio piece.

Time box: 3-4 days

Data/source: yfinance (free), NSE/BSE historical data

Built Python notebook for multi-stock time series analysis using pandas and yfinance; computed Sharpe ratios, rolling volatility, and correlation matrix across NSE equities.

FinPreparoo prioritizes free or free-to-audit resources so cost does not block learning. Crowd research uses public Reddit threads, web results, and YouTube search — not private social feeds.

NBFC risk dashboard

Build a risk dashboard for an NBFC using credit, liquidity, concentration, and stress-test indicators from public disclosures.

Built an NBFC risk dashboard with stress scenarios and early-warning indicators.

Carta's educational content is the practitioner standard. BIWS is the most cited cap table modeling resource. The Valuation School covers Indian nuances — CCPS, FEMA compliance, convertible note vs SAFE structures.

Multi-Round Cap Table - Seed to Series B with Exit Waterfall

Build a full cap table in Excel for a fictional Indian B2B SaaS startup. Round 1 (Seed): 2 founders (each 40%), angel investor puts in INR 1 Cr at INR 10 Cr post-money. Round 2 (Series A): VC puts in INR 10 Cr at INR 50 Cr post-money; 10% ESOP pool created. Round 3 (Series B): New VC puts in INR 40 Cr at INR 200 Cr post-money; existing VC exercises pro-rata of INR 5 Cr. Build the complete dilution table showing ownership % after each round. Then model exits at INR 150 Cr, INR 300 Cr, and INR 600 Cr showing what each party receives after applying 1x non-participating liquidation preferences.

Time box: 3-4 days

Data/source: Self-constructed (fictional startup, realistic Indian VC market terms)

Built multi-round cap table for fictional Indian SaaS startup from seed to Series B; modeled dilution, ESOP pool impact, and exit waterfall across 3 scenarios showing per-party returns.

Sentdex is the consensus Python algotrading resource on r/algotrading. QuantConnect for backtesting platform. Patrick Boyle covers institutional algo trading. Market Gurukul for Hindi NSE algo context (SEBI co-location rules, Zerodha/Kite API).

Mean-Reversion Strategy - Indian Equities Backtest with Walk-Forward Validation

Build a mean-reversion strategy for Indian equities in Python. Strategy: when a Nifty 200 stock's 20-day RSI drops below 30, buy; when RSI exceeds 70, sell. Universe: all Nifty 200 stocks with >2 years of data. Backtest over 3 years of NSE price data. Calculate: CAGR, Sharpe ratio, max drawdown, win rate, average hold period. Then run walk-forward validation (train on 2021-2022, test on 2023) to check for overfitting. Compare performance to Nifty 50 buy-and-hold benchmark. Write a 2-page strategy evaluation report including transaction cost assumptions.

Time box: 5-7 days

Data/source: yfinance (free NSE price data), NSE Bhavcopy archives (free)

Developed and backtested RSI mean-reversion strategy for Nifty 200 universe over 3 years; validated with walk-forward test; achieved Sharpe of X vs. Nifty 50 benchmark with 2-page strategy evaluation.

CFI covers credit risk from a practitioner angle with free video content. Patrick Boyle covers Basel III and IFRS 9 academically and practically. FRM (Financial Risk Manager) certification materials are the global standard curriculum.

ECL Model Build - PD, LGD, and IFRS 9 Staging

Using a public credit dataset (Give Me Some Credit from Kaggle, 150,000 loan observations), build a complete Expected Credit Loss model: (1) PD Model: logistic regression to predict default, validated with AUC-ROC and Gini coefficient, (2) LGD assumption: use historical recovery rate of 40% (Indian NBFC benchmark) applied by loan type, (3) EAD: outstanding balance x credit conversion factor, (4) ECL = PD x LGD x EAD for each loan, (5) IFRS 9 Staging: Stage 1 (12-month ECL), Stage 2 (lifetime ECL for significant credit increase), Stage 3 (lifetime ECL for defaulted). Sum the total provision requirement. Write a 2-page credit risk model validation note.

Time box: 6-8 days

Data/source: Give Me Some Credit dataset (Kaggle, free), RBI NPA recovery statistics for LGD calibration reference

Built end-to-end ECL model (PD/LGD/EAD) using logistic regression on 150K loan dataset; implemented IFRS 9 staging; validated with Gini coefficient and calibration plot; wrote model validation note.

FinPreparoo prioritizes free or free-to-audit resources so cost does not block learning. Crowd research uses public Reddit threads, web results, and YouTube search — not private social feeds.

Fintech PRD for lending feature

Write a PRD for a digital lending or payments feature with user problem, risk controls, metrics, and rollout plan.

Wrote a fintech PRD for a lending feature with user metrics, risk controls, and rollout plan.

a16z blog posts on unit economics are the VC practitioner standard. Y Combinator's unit economics videos are widely shared in startup Twitter/X. Alex the Analyst for cohort analysis in Excel/SQL. The Valuation School covers Indian startup unit economics (D2C, SaaS, fintech, BNPL).

Unit Economics Model for an Indian Consumer Startup

Pick a well-known Indian consumer startup (Swiggy, Zepto, Razorpay, CRED, etc.). Using publicly available data (news, DRHP, media founder interviews), build a unit economics model estimating CAC, average order value, gross margin per order, LTV, and payback period. Build Bull/Base/Bear scenarios showing when LTV > 3x CAC. Write a 1-page VC investment thesis on whether the unit economics support the business model.

Time box: 4-5 days

Data/source: Crunchbase free tier, Inc42, Entrackr, DRHP filings

Built unit economics model for [Startup] with LTV/CAC analysis; identified payback period and break-even customer volume across 3 scenarios; wrote VC-format investment thesis.

Labour Law Advisor covers all Indian regulatory frameworks comprehensively in Hindi — widely used by compliance trainees and CA/CS students. IICA publishes free governance explainers. The Valuation School covers SEBI regulations for finance career preparation.

DRHP Section-by-Section Analysis

Download the DRHP of any recent Indian IPO from SEBI's website. Write a 4-page structured analysis: business overview, use of proceeds vs. valuation logic, top 5 risk factors by severity, related-party transactions and their significance, and your assessment of whether disclosures raise any concerns. Include specific SEBI ICDR Regulation references where relevant.

Time box: 4-5 days

Data/source: SEBI DRHP public database (sebi.gov.in)

Conducted DRHP analysis for [Company]'s IPO; evaluated use of proceeds, risk factor quality, and related-party disclosures against SEBI ICDR Regulations.

ACAMS is the global AML professional body — free webinars recommended by compliance officers on LinkedIn and r/AML. Labour Law Advisor covers PMLA/KYC in Hindi — most widely used by compliance trainees. FIU-IND typology reports are essential reading for Indian AML practitioners.

AML Typology Report - 3 Indian Financial Crime Cases

Using FIU-IND annual reports and FATF India mutual evaluation reports (both free), identify and document 3 AML typologies reported in India (e.g. real estate money laundering, hawala, shell company layering). For each: describe the scheme, list red flags that should trigger an STR, describe how a compliant bank should respond, and cite the applicable PMLA provision. Format as a 6-page compliance training document.

Time box: 3-4 days

Data/source: FIU-IND Annual Reports (fiuindia.gov.in), FATF India MER (free)

Researched 3 Indian AML typologies from FIU-IND and FATF reports; documented STR triggers, red flags, and PMLA provisions; formatted as 6-page compliance training document.

Brad Feld's Venture Deals is the reference text. YC Startup School covers the full term sheet curriculum for free on YouTube. Warikoo provides the Hindi Indian startup context. The most important thing: model out the economic impact of a liquidation preference clause in your cap table - the math, not just the definition, is what distinguishes analysts. FinPreparoo prioritizes free or free-to-audit resources so cost does not block learning. Crowd research uses public Reddit threads, web results, and YouTube search — not private social feeds.

Term Sheet Red-Line - Founder vs. Investor Perspective

Download the NVCA model Series A term sheet (free from nvca.org). For each of the 10 most economically significant clauses, write: what the standard NVCA language says, what a founder-friendly version would look like, what an investor-protective version would look like, and the economic impact of each version (quantified in your cap table model). Then build a one-pager summarizing the key negotiating points a founder should push back on and why - with specific language suggestions.

Time box: 4-5 days

Data/source: NVCA model term sheet (nvca.org, free), SAFE Note template (ycombinator.com, free), iSPIRT/IndiaTech Indian VC term sheet notes

Annotated NVCA Series A term sheet from founder and investor perspectives; modeled economic impact of 10 key clauses; built one-page negotiation guide with language recommendations.

Damodaran's 'narrative meets numbers' is the academic gold standard — universally cited for startup valuation. Y Combinator's YouTube is the practitioner VC reference. The Valuation School covers Indian startup ecosystem (SEBI AIF, DPIIT DIPP framework, CCPS structures).

VC Investment Memo - Valuation Using 3 Methods

Choose a well-known Indian startup that recently raised a disclosed funding round (use Crunchbase free tier or Inc42 for deal data). Independently value it using: (1) VC Method - work backwards from a projected exit to justify the current valuation, (2) Revenue Multiple - using comparable SaaS/startup revenue multiples from public market comparables, (3) First Chicago Method - model 3 scenarios (success, sideways, failure) with probability weights. Present all 3 in a 1-page valuation summary. Then write a 1-page investment memo arguing for or against investment at the disclosed valuation.

Time box: 4-5 days

Data/source: Crunchbase free, Inc42, YourStory (startup data), public company revenue multiples from Screener.in

Valued [Indian startup] at disclosed funding round using VC Method, revenue multiples, and First Chicago Model; reconciled 3 outputs in valuation summary and wrote VC investment memo.

Y Combinator and a16z blog posts on TAM are the VC practitioner standard. The Valuation School covers Indian market sizing using government data (IBEF, MCA, RBI, DPIIT). Consulting case interview resources teach mental math market sizing transferable to VC memos.

Market Sizing Exercise - Bottom-Up vs. Top-Down for an Indian Startup Sector

Size the Indian digital lending market using both approaches. Top-down: start from India's total credit market (RBI data), segment by individual vs. MSME vs. corporate, estimate the digital-first portion, and apply a realistic penetration rate. Bottom-up: estimate the number of creditworthy but underserved borrowers (income data from PLFS survey + formal credit exclusion data from CIBIL/TransUnion), average loan size, and repeat rate. Compare both outputs. Write a 2-page market sizing memo defending your best estimate with confidence interval and key assumptions.

Time box: 4-5 days

Data/source: RBI Handbook of Statistics (free), Census India (censusindia.gov.in), MOSPI PLFS data (free), IBEF BFSI report (free), TransUnion CIBIL public reports

Sized Indian digital lending market using bottom-up and top-down approaches; reconciled $X-Y Bn range with confidence intervals using RBI, Census, and PLFS primary data sources.

Patrick Boyle explains structured products with practitioner clarity — cited by finance professionals studying for FICC interviews. BIWS covers structured finance in the leveraged finance context. The Valuation School covers Indian securitisation — RBI ARC framework, PTC structures.

ABS Waterfall Model - Indian NBFC Securitization

Build an ABS waterfall model for a fictional Indian NBFC securitizing a pool of 2-wheeler loans. Pool: INR 100 Cr, average LTV 80%, average tenor 36 months, WAC 18%, expected default rate 3%. Structure: Senior tranche (80% = INR 80 Cr, rated AA, yield 8.5%), Junior/Subordinate tranche (20% = INR 20 Cr, retained by originator). Build monthly cash flow waterfall for 36 months: principal collections + interest collections -> fees -> senior interest -> senior principal -> subordinate payments. Stress test: default rate at 3%, 6%, and 9% - when does the senior tranche suffer principal loss? Write a 2-page rating rationale as if you were a credit analyst at CRISIL.

Time box: 5-6 days

Data/source: Self-constructed pool (use CRISIL/ICRA 2-wheeler ABS public reports for realistic default rate assumptions, free from their websites)

Built ABS waterfall model for INR 100 Cr 2-wheeler loan pool securitization; stress-tested senior tranche protection at 3/6/9% default rates; wrote CRISIL-style rating rationale.

Stanford's Matt Abrahams is the most respected English communication educator for professionals. Ankur Warikoo is undisputably India's #1 career communication resource in Hindi - his combination of ISB MBA background, Fortune recognition, and 5 bestselling career books gives him unmatched credibility for Indian students. FinPreparoo prioritizes free or free-to-audit resources so cost does not block learning. Crowd research uses public Reddit threads, web results, and YouTube search — not private social feeds.

3-Minute Stock Pitch - Recorded and Self-Reviewed

Record yourself delivering a 3-minute verbal pitch on a stock of your choice. The pitch must include: investment thesis, key financial metrics, one risk and how you'd mitigate it, and a buy/sell recommendation. Record on your phone or Loom. Review it critically against a rubric: clarity of thesis, handling of numbers, pacing, filler words, eye contact. Revise and record a second version. Compare both.

Time box: 2 days (including revisions)

Data/source: Your own equity research project (link to valuation project above)

Delivered stock pitch for [Company] in simulated investment committee setting; recorded, self-reviewed, and revised against professional communication rubric.

The Pyramid Principle is the non-negotiable framework - learn it before your first day at any finance or consulting firm. The Coursera Business Writing course is the best free structured path. Warikoo covers the Hindi-language side of professional communication with credibility. FinPreparoo prioritizes free or free-to-audit resources so cost does not block learning. Crowd research uses public Reddit threads, web results, and YouTube search — not private social feeds.

Investment Memo - 2 Pages, Pyramid Structure

Write a 2-page investment memo for a fictional IC (Investment Committee) recommending whether to invest INR 10 Cr in a listed Indian mid-cap company. Use the Pyramid Principle: lead with your recommendation, then support it with 3 key arguments, then provide evidence for each. No bullet-point dumps - write in professional prose. Get someone to read it cold and tell you what your recommendation was after reading only the first paragraph.

Time box: 2-3 days

Data/source: Your valuation project as the analytical foundation

Authored 2-page IC-format investment memo for INR 10 Cr equity investment using Pyramid Principle structure; memo communicated recommendation within opening paragraph.

HBR YouTube is the English professional standard for stakeholder management education. Warikoo is the Hindi equivalent for Indian workplace context. The most important principle: over-communicate before deliverables are late, not after. This single habit separates trusted analysts from unreliable ones. FinPreparoo prioritizes free or free-to-audit resources so cost does not block learning. Crowd research uses public Reddit threads, web results, and YouTube search — not private social feeds.

Stakeholder Map + Difficult Conversation Role-Play

For any internship, college project, or mock deal scenario you have done: create a stakeholder map identifying all people involved, their interests, their power level, and how you would manage each. Then write out 3 difficult conversations you would need to have (e.g. telling an MD the model has an error, asking a client for an extension, pushing back on an unrealistic deadline). Script each conversation using the HBR 'SBI' (Situation-Behavior-Impact) framework. Role-play them with a friend or record yourself.

Time box: 2-3 days

Data/source: Your own experience (internship, project, capstone)

Managed cross-functional stakeholder communication across [X] parties during [project]; navigated conflicting priorities by proactive expectation-setting and structured escalation.

Ali Abdaal for evidence-based productivity systems in English. Warikoo for the Hindi-language equivalent with Indian professional context. The most important thing is not which system you choose - it is building the habit of weekly planning and daily prioritization before you start your job, not after. FinPreparoo prioritizes free or free-to-audit resources so cost does not block learning. Crowd research uses public Reddit threads, web results, and YouTube search — not private social feeds.

Personal Workflow Audit and System Build

Conduct a 2-week time audit using Toggl (free). Track every hour across 5 categories: deep work, reactive work (email/messages), meetings, admin, and breaks. Analyse where your actual time goes vs. where you think it goes. Then design your personal workflow system: weekly planning template, daily top-3 priorities method, email batching, and a focus block schedule. Run the new system for 2 weeks and compare output quality and stress levels before/after.

Time box: 4 weeks total (ongoing habit, not a one-time task)

Data/source: Your own time tracking data

Designed and implemented personal productivity system using time-block scheduling and weekly review; sustained output quality across 80+ hour simulated deal week during capstone project.

FinPreparoo prioritizes free or free-to-audit resources so cost does not block learning. Crowd research uses public Reddit threads, web results, and YouTube search — not private social feeds.

Role-specific interview answer bank

Create a technical and behavioral interview bank for a target finance role with STAR stories, model explanations, and project talk tracks.

Built a role-specific finance interview bank with technical answers, behavioral stories, and project talk tracks.

Cole Nussbaumer Knaflic is the undisputed authority on data storytelling - her book and YouTube channel are used in MBA programs globally. For Hindi-language visual communication education, Avi Singh covers the finance-specific application. The most impactful exercise: take your last financial model output and redesign it as if you were presenting it to someone who has never seen a spreadsheet. FinPreparoo prioritizes free or free-to-audit resources so cost does not block learning. Crowd research uses public Reddit threads, web results, and YouTube search — not private social feeds.

Annual Report Turned Into a 5-Slide Data Story

Take the annual report of any listed Indian company and distill its financial performance story into exactly 5 slides - no more. Each slide must make one clear point. No data dumps, no standard bar charts copied from Excel. Every chart must be redesigned following Cole Nussbaumer's SWD principles: clear title that states the insight, minimal non-data ink, one highlighted data point that drives the message. The audience is a CEO with 5 minutes.

Time box: 2-3 days

Data/source: BSE India annual reports (free)

Distilled [Company] annual report into 5-slide CEO-facing data story; redesigned financial charts following SWD principles to drive single clear insight per slide.