{
  "title": "Big Data for Macroeconomic Statistics",
  "sourceUrl": "https://www.imf.org/en/capacity-development/training/icdtc/schedule/at/2026/bdmsat26-27",
  "canonical": "https://www.imf.org/en/capacity-development/training/icdtc/schedule/at/2026/bdmsat26-27",
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  "summary": "Big Data for Macroeconomic Statistics Training Program Qualifications Participants are expected to have a degree in economics, statistics, data science or equivalent experience.",
  "publishDate": "2026-02-26",
  "sections": [
    {
      "heading": "Overview and logistics",
      "content": "- Session No.: AT 26.27\n- Location: Ebene, Mauritius\n- Date: October 26-30, 2026 (1 week)\n- Delivery Method: In-person Training\n- Primary Language: English\n- Interpretation Language: French Portuguese\n- Deadline: Deadline passed"
    },
    {
      "heading": "Target audience and qualifications",
      "content": "- Intended participants:\n  - Technical staff and managers from national statistics offices and central banks involved in macroeconomic statistics, nowcasting, and data science projects.\n  - Economists, statisticians, data scientists, and decision-makers overseeing related projects or teams.\n- Qualifications:\n  - Expected to have a degree in economics, statistics, data science or equivalent experience.\n  - Working knowledge of advanced programming languages such as Python and R is strongly recommended."
    },
    {
      "heading": "Course description",
      "content": "- Audience: Country officials from national statistics offices (NSOs) and central banks seeking skills to leverage Big Data and advanced technologies for high-frequency and detailed statistics.\n- Delivery: Lectures and hands-on workshops delivered by data scientists of the IMF Big Data Center.\n- Emphases:\n  - Big Data applications pertinent to macroeconomic statistics from both producer and user standpoints.\n  - Participant presentations and discussion of use cases, peer learning, and experience sharing."
    },
    {
      "heading": "Course objectives and learning outcomes",
      "content": "- Technical architecture and workflows:\n  - Provide support in setting up Big Data architecture, encompassing data extraction, preprocessing, and visualization in their various organizations.\n- Machine learning and nowcasting:\n  - Demonstrate a practical knowledge of machine learning modeling, variable selection, performance analysis as well as model selection, for GDP nowcasting and trade monitoring (based on the IMF's \"PortWatch\" platform).\n- Geospatial analysis:\n  - Demonstrate practical skills in the use of Google Earth Engine (GEE), Dynamic World, Jupyter Notebook and other geospatial and data science packages to analyze satellite data and generate high-frequency macroeconomic statistics.\n- Textual analysis and NLP:\n  - Carry out textual analysis with natural language processing (NLP) technologies to support macroeconomic analysis.\n- Statistical production improvements:\n  - Demonstrate the application of these Big Data technologies and resources to improve timelines and granularity of their official statistics.\n- Institutional capacity and collaboration:\n  - Facilitate peer-learning on Big Data applications and explore collaborations between agencies working on projects of mutual interest.\n  - Gain insights into setting up effective data science teams and developing institutional Big Data strategies to support innovation for macroeconomic statistics."
    }
  ],
  "bullets": [
    "Session No.: AT 26.27",
    "Location: Ebene, Mauritius",
    "Date: October 26-30, 2026 (1 week)",
    "Delivery Method: In-person Training",
    "Primary Language: English",
    "Interpretation Language: French Portuguese",
    "Deadline: Deadline passed",
    "Intended participants:",
    "Qualifications:",
    "Audience: Country officials from national statistics offices (NSOs) and central banks seeking skills to leverage Big Data and advanced technologies for high-frequency and detailed statistics.",
    "Delivery: Lectures and hands-on workshops delivered by data scientists of the IMF Big Data Center.",
    "Emphases:",
    "Technical architecture and workflows:",
    "Machine learning and nowcasting:",
    "Geospatial analysis:",
    "Textual analysis and NLP:",
    "Statistical production improvements:",
    "Institutional capacity and collaboration:"
  ],
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    "bundleManifest": "/en/capacity-development/training/icdtc/schedule/at/2026/bdmsat26-27/bundle-manifest.json"
  },
  "generatedAtUtc": "2026-09-29T16:51:22.905Z"
}