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Quantzivo Professional Algo Developer

A 12-week program that takes you from Python market data work to building, backtesting, validating and engineering algorithmic strategies as tested software.

  • Duration12 weeks
  • LevelIntermediate
  • Phases7
  • Lessons28
Enroll nowView curriculum
Quantzivo Professional Algo Developer
Proposed fee$2,499USD · 12 weeks

Program overview

The Professional Algo Developer program combines Quantzivo courses into one guided path for building algorithmic strategy software. You progress from Python and historical market data through strategy logic, backtesting methodology and robustness validation to event-driven system design. The focus is on engineering quality and honest evaluation, ending with a reviewed capstone system that runs on historical and simulated data.

  • Python for market data
  • Strategy logic
  • Backtesting methodology
  • Robustness validation
  • Event-driven systems
  • Engineering practice

What you receive

  • Practical coding labs in Python
  • Structured weekly assignments
  • Strategy backtesting on historical data
  • Code reviews on submitted work
  • Live technical mentoring in cohort runs
  • Capstone assessment

What you will learn

  • Clean and analyze historical market data with Python and pandas
  • Translate a written strategy specification into tested, modular code
  • Backtest strategies with explicit cost assumptions and bias controls
  • Validate results with walk-forward analysis and parameter sensitivity checks
  • Build an event-driven system with simulated execution, logging and replay

Curriculum

7 phases · 28 lessons · 12 weeks. Curriculum preview; the final syllabus may change before enrollment opens.

  • Python for financial data
  • Working with pandas time series
  • Market structure essentials
  • Cleaning historical price data

  • Rules-based strategy logic
  • Signals, entries and exits
  • Position sizing basics
  • Writing strategy specifications

  • Vectorized backtests
  • Transaction costs and slippage
  • Look-ahead and survivorship bias
  • Performance and risk metrics

  • Walk-forward analysis
  • Parameter sensitivity
  • Overfitting risks
  • Out-of-sample evaluation

  • Event loops and handlers
  • Order and portfolio components
  • Simulated execution
  • Logging and replay

  • Testing strategy code
  • Code review habits
  • Packaging and configuration
  • Monitoring paper trading

  • Capstone specification
  • Build and backtest
  • Code review and revisions
  • Capstone assessment

Practical projects

01

Implement and backtest a rules-based strategy with transaction costs and a written specification

02

Produce a validation report with walk-forward results and parameter sensitivity charts

03

Build an event-driven paper-trading system on a simulated feed with full decision logs

Skills you will practice

  • Python
  • pandas
  • Backtesting
  • Walk-forward analysis
  • Event-driven design
  • pytest

Requirements

Who it's for

  • Developers who want a structured path into algorithmic strategy engineering
  • Analysts and traders who want to build and test their own research tools
  • Learners who completed Algorithmic Trading Fundamentals and want to go further

Prerequisites

  • Basic Python programming, or Python Programming for Financial Markets
  • Familiarity with market basics, such as Algorithmic Trading Fundamentals

Learning format

  • Phased curriculum over 12 weeks combining self-paced lessons and labs
  • Weekly assignments with code reviews
  • Live technical mentoring sessions in cohort runs
  • Quantzivo certificate of completion after passing the capstone assessment (not an accredited qualification)

Quantzivo certificates are completion credentials issued by Quantzivo, not accredited qualifications. Courses teach technical and research skills; they do not promise investment returns or provide investment advice.

Frequently asked questions

Phased curriculum over 12 weeks combining self-paced lessons and labs Weekly assignments with code reviews Live technical mentoring sessions in cohort runs

Basic Python programming, or Python Programming for Financial Markets. See the full list under Requirements.

Yes. Completing the lessons and assessed projects earns a Quantzivo certificate of completion. It is a completion credential issued by Quantzivo, not an accredited qualification.

The $2,499 USD fee is a proposed launch price. Final fees, schedules, refund terms and any regional options are confirmed before any payment is taken.

Quantzivo teaches technical, data and research skills. It does not provide investment advice, trading signals or any promise of returns. Trading involves risk, including loss of capital.
Keep learning

Courses in this program

Algorithmic Trading with Python - Algorithmic Trading Engineering course thumbnail
Intermediate6 weeks6 modules

Algorithmic Trading with Python

Build a modular algorithmic trading research stack in Python, covering data handling, signal libraries, vectorized and event-based backtests, and paper-trading workflows.

Proposed fee$799
View details
Python Backtesting Masterclass - Strategy Development & Backtesting course thumbnail
Intermediate6 weeks6 modules

Python Backtesting Masterclass

Build accurate, bias-aware backtesting engines in Python, from vectorized prototypes to event-driven simulators with realistic costs, fills and portfolio accounting.

Proposed fee$799
View details
Advanced Strategy Validation & Optimization - Strategy Development & Backtesting course thumbnail
Intermediate7 weeks7 modules

Advanced Strategy Validation & Optimization

Apply rigorous validation methods to trading strategies: walk-forward and cross-validation, overfitting diagnostics, multiple testing control and robust parameter optimization.

Proposed fee$999
View details
Event-Driven Trading System Architecture - Algorithmic Trading Engineering course thumbnail
Advanced8 weeks8 modules

Event-Driven Trading System Architecture

Design and build an event-driven trading system architecture with message queues, state management, risk services and replayable simulations shared between research and paper trading.

Proposed fee$1,199
View details
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