Generation STEM
Courses/Finance · Ages 13-18 · Intermediate
Algorithmic Trading (Finance) course artwork

Algorithmic Trading (Finance)

A Python-powered finance course where teens build an honest quantitative research lab with frozen market data, moving averages, signals, backtests, risk metrics, transaction costs, and out-of-sample testing.

▸16 lessons▸8-12 weeks▸Self-paced learning
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// learn by building

Here's what you build by Module 3 (Signals).

// course experience

Meet the workspace.

Students build through real coding environments while their personal AI mentor helps them through each challenge.

✓Approved market data
✓Backtests on teaching series
✓Risk and position sizing
✓No brokerage connection
// the quick version

What is Algorithmic Trading (Finance)?

Use code to understand markets, money, and the algorithms quietly moving modern finance.

🛠️

What you'll learn

  • ▸Analyze real market data with Python
  • ▸Build and backtest trading strategies
  • ▸Learn risk, returns, and position sizing
  • ▸Think about money quantitatively
🎯

Who it's for

Teens fascinated by markets, math, and how the financial world actually operates.

Ages 13-18 · intermediate
🚀

Where it leads

Quantitative finance and fintech are among the most competitive, highest-paid fields — and they run entirely on code. This is a rare early head start.

Quant FinanceFintechData ScienceEconomics
// curriculum

A clear path from first concept to final project.

8 modules designed for steady momentum and project-based practice.

Before any strategy, students learn to read the tape by turning a raw price series into the percentage moves a strategy actually sees.

Learning objective: Students practice price series and daily return concepts while adding pct_change and returns to their trading lab.

Lesson 1: Reading the TapeLesson 2: The Return Series
🎓
Students:
✓Learn quantitative finance through real Python programs instead of stock-market hype
✓Use authentic vocabulary like return, moving average, signal, position, equity curve, benchmark, drawdown, costs, and out-of-sample
✓Work with a frozen fictional APX dataset so every result is reproducible and every lesson is gradable
✓Practice Python, math, data analysis, systems thinking, and risk awareness in one course
✓Finish with a 16-program Quant Research Lab notebook and a complete strategy verdict
👪
Parents:
✓No brokerage setup, real trades, financial advice, or account credentials
✓A sober engineering-first approach to a high-interest finance topic, with clear disclaimers around backtests and risk
✓Deterministic sandbox data instead of arbitrary public internet access or volatile live-market grading
✓Practical Python, math, data literacy, and skeptical risk-thinking skills
✓A strong next step after Python for Teens for students interested in finance, analytics, AI, economics, or quantitative systems
✓Visible portfolio outcomes, Nova support, parent progress tracking, achievements, and certificates
// skills learned

Real technical vocabulary and practice.

Students learn the language of the field while building things that make each concept concrete.

Price SeriesPercent ChangeDaily ReturnsMoving AveragesCrossover SignalsPositionsBacktestingEquity CurvesDrawdownWin RateMomentumRSITransaction CostsTrain/Test SplitsOut-of-Sample Testing
// proof of work

Finish the course. Earn the certificate.

Every track ends in a verifiable Certificate of Completion - a real milestone your student can add to a portfolio, application, or resume. Proof they didn't just watch a video; they shipped real projects.

✓Awarded automatically when all lessons are complete
✓A shareable PDF plus a verifiable completion link
✓Lists the real skills practiced - not just attendance
✓A finish line students actually work toward
Start the course →
Generation STEM
Certificate of Completion
This certifies that
Your Name
has successfully completed all projects of
Algorithmic Trading (Finance)
Daniel Mondeu
Founder, Generation STEM
★CERTIFIED
January 1, 2026
Date issued
// parent questions

Clear answers before you enroll.

No. Students do not connect brokerage accounts, place real trades, collect credentials, or receive financial advice. They work in a safe educational sandbox with simulated positions and a frozen fictional APX price series.

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