A 20-24 week program for leaders overseeing quant technology: research methodology, data strategy, AI adoption, systems architecture, controls and team building.
Duration20-24 weeks
LevelAdvanced
Phases8
Lessons32
The Executive Quant Technology Program helps leaders make sound decisions about quantitative research and financial technology. It covers how research moves from idea to production, how to read backtests critically, and how data, AI and architecture choices affect risk and cost. Guided exercises on historical data keep the material concrete, and the program ends with a technology strategy capstone presented for review.
8 phases · 32 lessons · 20-24 weeks. Curriculum preview; the final syllabus may change before enrollment opens.
Conduct a structured critical review of a historical backtest and write a findings memo
Assess a data and architecture plan for a research platform against risk and cost criteria
Present a technology strategy brief covering roadmap, controls and team structure
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.
4 weeks4 modulesLearn how algorithmic trading systems are structured, from market data and signals to orders, risk checks and evaluation, with a clear view of their limits.
5 weeks5 modulesLearn a structured process for designing trading strategies: forming hypotheses, defining rules, choosing data and evaluation criteria, and documenting research honestly.
5 weeks5 modulesLearn the foundations of financial data engineering: data types, schemas, SQL, ingestion, cleaning, corporate actions and reliable batch pipelines in Python.
7 weeks7 modulesApply supervised and unsupervised machine learning to financial datasets using feature engineering, purged cross-validation and disciplined, leakage-aware evaluation.
10 weeks10 modulesEngineer LLM-based research agents that retrieve documents, call analytical tools and produce traceable financial research outputs with evaluation and guardrails built in.
12 weeks12 modulesMaster end-to-end fintech architecture: ledgers, event sourcing, integrations, security, reliability, scalability, compliance-aware design and AI components.
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