Interactive quant education
Learn quantitative finance by building it.
Write code, get instant feedback, and build real skills across finance, maths, and technology.
Live challengeKill-switch on drawdown
Stop the backtest when peak-to-trough loss exceeds 15%.
Automated checks
- test_threshold_fires
- test_positions_flat
- test_halt_status
Next lesson
Walk-forward validation
Why Quantt works
Most quant education is passive. Videos you watch. PDFs you skim. Quantt makes you build. Every lesson is code you write, tests you pass, and intuition you earn — the way working quants actually learn.
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Interactive courses
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Coding exercises
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Learning streams
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Build projects
As seen in
Live demo · Part 1 — the editor
Edit the code. Run the backtest.
A real exercise from our Trading Systems course, playing itself. Click anyhighlightedparameter to take the controls.
app.quantt / courses / trading-systems / momentum-backtestAuto-demo — click to take overFinance1def momentum_signal(px, lookback=):
2 rets = px.pct_change(lookback)
3 return np.sign(rets)
4
5bt = Backtest(
6 signal=momentum_signal,
7 risk_per_trade=,
8 tx_costs=,
9)
10curve = bt.run(universe="sp500")Output
Equity curve
Total return
Sharpe
Max drawdown
Trades
Test Results
- test_no_lookahead
- test_position_limits
- test_costs_applied
Illustrative simulation for learning purposes — not investment advice.
Live demo · Part 2 — the library
Then go deep. 200+ lessons deep.
The editor is one surface of the platform. Behind it sits a full curriculum — 200+ lessons of notes, quizzes, exams and coding tests across three streams, all cross-linked and tracked.
Structured like a degree. Paced like a game.
50+ coursesEvery course earns its place on a path from first principles to desk-ready. No filler electives.
Derivatives Pricing
Finance14 lessons · notes, quiz & exercises
Stochastic Calculus
Mathematics11 lessons · notes, quiz & exercises
Market Microstructure
Finance9 lessons · notes, quiz & exercises
C++ for Trading Systems
Technology12 lessons · notes, quiz & exercises
Notes → Quiz → Exercises. One loop, repeated until it sticks.
Notes that don’t dumb it down
Full derivations, plain-English intuition. Rigour without the fog.
Under the risk-neutral measure, the discounted price is a martingale:
dSt = rStdt + σStdWt
Reading progress · 60%
Quizzes that bite back
Wrong answers are written from real misconceptions. Guessing won’t save you.
Doubling volatility does what to a European call’s vega-weighted price?
Prove it under the clock
Interview conditions, before the interview. Timed, marked, tracked.
Derivatives II
Mock exam · 90 min
Pandas pipeline
Timed coding test
Momentum you can measure
14-day streakStreaks, progress and a 300+ term glossary one tap away in every lesson — the habit does the compounding:
The platform
Everything you need to go from curious to quant.
Three integrated streams
Finance, Mathematics and Technology — taught together, the way real desks use them.
Finance
21 modules
72% complete
Mathematics
17 modules
54% complete
Technology
14 modules
38% complete
One syllabus, three tracks — lessons cross-reference so the maths, the finance and the code always connect.
Code in your browser
A full Python environment with NumPy, Pandas and SciPy. Zero setup, instant runs.
from scipy.stats import norm # pre-installed, zero setup
d1 = (np.log(S/K) + (r + sigma**2/2)*T) / (sigma*np.sqrt(T))
call = S*norm.cdf(d1) - K*np.exp(-r*T)*norm.cdf(d1 - sigma*np.sqrt(T))
print(f"Call: {call:.2f} · Delta: {norm.cdf(d1):.4f}")Call: 8.02 · Delta: 0.5987
✓ finished in 0.31s — runs entirely in your browser
Instant feedback
Every exercise ships with a test suite. Green means you actually understood it.
Test Results
4/4 passing- test_d1_d2_values
- test_call_price
- test_put_call_parity
- test_edge_cases
All tests passed — your progress is saved.
Stuck? Progressive hints
Hint 2/3 — remember to discount the strike: K·e-rT
Build a real portfolio
A trading engine, an options pricer, a factor model — systems you can show in interviews.
Trading engine
Order book · execution · backtesting
Options pricer
Black-Scholes · Heston stochastic vol
Portfolio optimiser
Mean-variance · constraints · turnover
ML prediction model
Feature engineering · cross-validation
Volatility forecaster
GARCH · realised vol · surfaces
Factor model
Signal research · portfolio construction
Guided task-by-task — every project ends with a system you can demo in an interview.
Interview-ready
Timed coding tests, mock exams and firm-by-firm prep for the roles you actually want.
Timed coding test
45:00Pandas signal pipeline · medium
Mock exam
82% · PassDerivatives II · 90 minutes
Firm-by-firm prep guides
Interview formats, question banks, and culture notes for the desks you’re targeting.
The payoff
Why become a quant?
Quantitative finance combines some of the highest compensation in any industry with genuinely hard, interesting problems — and the skills transfer everywhere.
$150K+
Entry-level total comp
$500K+
Senior quant roles
Global
NY · London · Singapore · Tokyo
A launchpad, not a lock-in
Finance
Hedge funds, investment banks, asset management
Technology
FAANG, fintech, AI/ML companies
Entrepreneurship
Your own trading firm or fintech venture
“The site has been a great way to refresh what I learned at university while picking up finance concepts I hadn't studied before. I have degrees in math and computer science, and I've found the content in those areas accurate and detailed, which gives me confidence in the finance material as well. It's definitely been a good purchase.”
Alfonso Hernandez
Google review
“Really helpful platform for people getting started in Quantitative Finance. It helps you practice a lot of concepts hands on.”
Murtaza Abbas Shakir
Google review
“Really helpful platform with well designed courses. It helped me to catch up on financial ideas and concept while refreshing maths and coding skills. The founders are really responsive and helpful. And the platform is growing and getting better each day!”
Peter Liu
Google review
“This quant course has a great format for learning and building at a great price. I have projects I can build and put on my resume and the value is amazing!”
Camille Dickens
Google review
“Quantt has been a pleasant surprise. Even with a solid technical background, it has been very valuable: both for reviewing familiar concepts in an enjoyable way and for learning new ones in a practical and well-structured manner. The initial assessment and the My Plan feature let you start at your level… It is worth every penny. Highly recommended.”
Sergio Huerta Lara
Google review
“Great place to learn quantitative finance. Very intuitive, highly educational and what is the best, practice coding from the very beginning. Highly recommended.”
Carlos Gonzalez
Google review
Pricing
A CQF costs £20,000. This doesn’t.
Professional-grade quant education at a price that pays for itself with your first salary negotiation.
Monthly
£39.95/month
Flexible monthly subscription
- Full course access — all three streams
- Interactive in-browser code editor
- Instant feedback on every exercise
- Pricing models, algo trading, risk
- Python & C++ courses
- Build complete systems
Annual
£249.95/year
Best value for serious learners
Save £229.45 (47% off)
- Everything in Monthly
- All 7 build projects
- Timed coding tests & mock exams
- Firm-by-firm interview prep
- Progress tracking & streaks
- Priority support
Enterprise
Custom
For teams and organisations
- Everything in Annual
- Team management & analytics
- Custom integrations & APIs
- Dedicated account manager
- Custom course content
30-day money-back guarantee on all paid plans. No questions asked.
How the routes compare
There are four real routes into quant. Here’s what each one actually costs you — in money, time and momentum.
Swipe the table to compare all four →
| Quantt | Quant MSc | CQF | Video courses | |
|---|---|---|---|---|
| Cost | £249.95 / year | £35,000+ | £20,000+ | £300–£2,000 |
| Time to first backtest | Your first session | Second semester | Months in | Whenever you stop watching |
| How you learn | Writing code, tested instantly | Lectures & problem sets | Lectures & exams | Watching someone else code |
| Feedback loop | Seconds, every exercise | Weeks per assignment | Exam results | None |
| What you leave with | 7 working systems + interview prep | Degree & alumni network | Industry-known certificate | Certificate of completion |
| If it’s not for you | 30-day money-back | Tuition is committed | Fees are committed | Depends on platform |
Typical advertised prices, 2026. An MSc is a genuinely good route — if you have two years and the tuition to spare.
FAQ
Questions, answered.
Primarily Python — the industry standard for quantitative research — plus C++ fundamentals for high-frequency systems and an introduction to Rust. All coding happens in our browser-based editor, with no local setup required.
No. You should know basic Python (variables, loops, functions), but each stream starts with foundational refreshers and builds progressively. Quantt is ideal for CS graduates, career changers, and junior professionals breaking into quant finance.
Three streams: Finance (portfolio theory, derivatives, market microstructure, risk), Mathematics (stochastic calculus, linear algebra, statistics, Monte Carlo), and Technology (Python, C++, distributed systems, databases) — from foundations to professional level.
A complete trading engine (order book, execution, backtesting), an options pricing model (Black-Scholes, Heston), a portfolio optimiser, an ML prediction model, a volatility forecaster, and a factor model — production-quality systems you can show in interviews.
Generic platforms teach programming without financial context; video platforms are passive. Every Quantt course, exercise and project is built around real financial problems — you write and run code in the platform and get instant feedback.
Yes. Monthly (£39.95) and Annual (£249.95, 47% cheaper) plans can be cancelled at any time, and every plan has a 30-day money-back guarantee — no questions asked.
