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Market Intelligence & Financial Data EngineeringEnrollment opening soon

Macroeconomic Intelligence Platform Development

Build a macroeconomic data platform that ingests public economic series, tracks vintages and releases, computes indicators and serves dashboards and APIs.

  • Duration8 weeks
  • LevelAdvanced
  • Modules8
  • Lessons32
Enroll nowView curriculum
Macroeconomic Intelligence Platform Development
Proposed fee$1,199USD · 8 weeks

Course overview

This advanced course guides you through building a platform for macroeconomic research. You will ingest public economic series from official statistical sources, model release calendars and data vintages so revisions are tracked correctly, and transform raw series into seasonally adjusted, comparable indicators. The platform is exposed through a FastAPI service and dashboards, with careful attention to methodology, provenance and the limits of macro data.

  • Macroeconomic data sources
  • Vintages and revisions
  • Release calendars
  • Indicator construction
  • Platform APIs
  • Macro dashboards

What you will learn

  • Ingest public macroeconomic series and normalize frequencies, units and metadata
  • Model data vintages and release calendars to support real-time, as-of queries
  • Construct indicators such as growth rates, diffusion indexes and composite measures
  • Apply seasonal adjustment and nowcasting concepts with statsmodels
  • Deliver a FastAPI service and dashboards with provenance and methodology notes

Curriculum

8 modules · 32 lessons · 8 weeks. Curriculum preview; the final syllabus may change before enrollment opens.

  • Key economic indicators and what they measure
  • Official statistical sources and formats
  • Frequencies, units and base periods
  • Platform requirements and users

  • Connecting to public data APIs
  • Series identifiers and metadata catalogs
  • Normalizing frequencies and units
  • Scheduling and failure handling

  • Why macro data gets revised
  • Bitemporal data modeling
  • As-of queries in PostgreSQL
  • Release calendar tracking

  • Growth rates and annualization
  • Seasonal adjustment concepts
  • Using statsmodels for decomposition
  • Rebasing and chain-linking

  • Diffusion indexes
  • Composite and standardized indicators
  • Surprise measures against prior releases
  • Documenting indicator methodology

  • Mixed-frequency data challenges
  • Bridge equations and simple factor models
  • Real-time evaluation with vintages
  • Communicating uncertainty

  • FastAPI endpoints for series and vintages
  • Caching and pagination
  • Dashboard layouts for macro research
  • Provenance and methodology notes in the UI

  • Data quality monitoring
  • Testing transformations and as-of logic
  • Deployment with Docker
  • Capstone: a macro intelligence platform demo

Practical projects

01

Build a vintage-aware macro data store that answers what was known on a given date

02

Construct a composite activity indicator from multiple public series with documented methodology

03

Ship a macro dashboard and API with release calendar views and series provenance

Skills you will practice

  • Python
  • PostgreSQL
  • statsmodels
  • FastAPI
  • Time-series transformations
  • Dashboard design

Requirements

Who it's for

  • Data engineers building research platforms for economists and analysts
  • Quant and macro researchers who need reproducible economic datasets
  • Developers who completed the data engineering courses and want a platform-scale project

Prerequisites

  • Building Market Data Pipelines or equivalent pipeline engineering experience
  • Financial Time-Series Modeling or familiarity with time-series transformations
  • Basic knowledge of macroeconomic concepts such as inflation, employment and GDP

Learning format

  • Self-paced lessons with platform architecture walkthroughs
  • Weekly build milestones on a shared reference platform
  • Design and code reviews
  • Live demo days and capstone reviews in cohort runs

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

Self-paced lessons with platform architecture walkthroughs Weekly build milestones on a shared reference platform Design and code reviews

Building Market Data Pipelines or equivalent pipeline engineering experience. 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 $1,199 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.
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