Format: Live instructor-led online training via Zoom / Microsoft Teams

Humanitarian Data Science and Analytics Training Course

Course Overview

The Humanitarian Data Science and Analytics Training Course is designed to equip humanitarian professionals, government agencies, United Nations personnel, non-governmental organizations (NGOs), disaster risk management specialists, Monitoring, Evaluation, Accountability and Learning (MEAL) professionals, researchers, statisticians, data scientists, Geographic Information Systems (GIS) specialists, information management officers, programme managers, policy makers, and humanitarian leaders with advanced knowledge and practical skills in applying data science, advanced analytics, and evidence-based decision-making to humanitarian operations. As humanitarian crises continue to increase in complexity due to climate change, armed conflict, forced displacement, pandemics, food insecurity, and environmental disasters, humanitarian organizations require robust data-driven approaches to improve preparedness, response, recovery, resilience, and sustainable development outcomes. This course provides comprehensive knowledge of humanitarian data science, statistical analysis, predictive analytics, machine learning, artificial intelligence, Geographic Information Systems (GIS), business intelligence, data visualization, humanitarian information management, cloud analytics, and digital transformation while aligning with international humanitarian principles, the Sustainable Development Goals (SDGs), the Sendai Framework for Disaster Risk Reduction, the Core Humanitarian Standard (CHS), and the Humanitarian-Development-Peace Nexus.

Participants will develop practical competencies in humanitarian data collection, data cleaning, database management, statistical modelling, predictive analytics, machine learning applications, Python programming, R programming, SQL databases, Power BI, Tableau, Excel analytics, Geographic Information Systems (GIS), remote sensing, humanitarian dashboards, cloud-based analytics platforms, artificial intelligence, humanitarian information management systems, monitoring, evaluation, accountability, and learning (MEAL), impact evaluation, humanitarian logistics analytics, risk modelling, needs assessment, beneficiary targeting, resource optimization, and evidence-based programme management. The training emphasizes integrating data science into emergency preparedness, humanitarian coordination, disaster risk reduction, food security, nutrition, public health, water, sanitation and hygiene (WASH), refugee management, protection programming, humanitarian financing, climate adaptation, recovery programming, and strategic humanitarian planning. Through practical data laboratories, analytics workshops, real-world datasets, simulation exercises, collaborative projects, and international humanitarian case studies, participants will strengthen their ability to transform humanitarian data into actionable intelligence that improves operational efficiency and humanitarian impact.

The course further explores advanced topics including artificial intelligence, deep learning, Natural Language Processing (NLP), predictive humanitarian analytics, big data ecosystems, cloud computing, data governance, cybersecurity, geospatial intelligence, digital twins, humanitarian forecasting, anticipatory action, business intelligence, innovation management, digital transformation, organizational resilience, responsible data management, climate intelligence, localization, ethical analytics, and future humanitarian data ecosystems. Participants will gain practical skills in developing predictive models, designing interactive dashboards, performing geospatial analysis, automating data pipelines, strengthening organizational data governance, improving institutional decision-making, and promoting responsible use of humanitarian data. Special emphasis is placed on data ethics, privacy protection, accountability to affected populations, gender-responsive analytics, disability inclusion, transparency, environmental sustainability, responsible artificial intelligence, and evidence-based humanitarian leadership.

Upon successful completion of the course, participants will possess the expertise to design, implement, manage, and evaluate humanitarian data science and analytics systems that improve preparedness, optimize emergency response, strengthen organizational resilience, support strategic decision-making, enhance programme quality, and build future-ready humanitarian organizations. Organizations will benefit from enhanced analytical capabilities, improved operational efficiency, stronger monitoring and evaluation systems, increased transparency, optimized resource utilization, enhanced donor confidence, improved collaboration, better forecasting, and sustainable humanitarian outcomes.

Course Objectives

1. Understand advanced humanitarian data science concepts, methodologies, and analytical frameworks.
2. Apply statistical analysis, machine learning, and predictive analytics to humanitarian operations.
3. Strengthen humanitarian data management, quality assurance, and governance systems.
4. Utilize Python, R, SQL, Power BI, Tableau, and Excel for humanitarian analytics.
5. Apply Geographic Information Systems (GIS) and geospatial analytics for humanitarian decision-making.
6. Develop interactive dashboards and business intelligence solutions for humanitarian programmes.
7. Strengthen Monitoring, Evaluation, Accountability, and Learning (MEAL) through advanced analytics.
8. Promote evidence-based planning, forecasting, and humanitarian resource optimization.
9. Enhance organizational resilience through digital transformation and data-driven innovation.
10. Build future-ready humanitarian organizations capable of leveraging advanced data science and analytics technologies.

Organization Benefits

1. Strengthens evidence-based humanitarian planning and strategic decision-making.
2. Improves programme monitoring, evaluation, accountability, and organizational learning.
3. Enhances humanitarian needs assessments and predictive risk analysis.
4. Improves operational efficiency through advanced data analytics and automation.
5. Strengthens humanitarian information management and data governance.
6. Enhances donor reporting, transparency, and accountability.
7. Optimizes humanitarian logistics and resource allocation.
8. Increases organizational innovation and digital transformation capacity.
9. Strengthens organizational resilience through predictive analytics and business intelligence.
10. Builds sustainable data-driven humanitarian organizations capable of responding effectively to future crises.

Target Participants

• Humanitarian Programme Managers
• Monitoring, Evaluation, Accountability, and Learning (MEAL) Specialists
• Data Scientists
• Statisticians
• Information Management Officers
• Geographic Information Systems (GIS) Specialists
• United Nations Agency Personnel
• NGO and INGO Professionals
• Government Disaster Management Officials
• Public Health Analysts
• Humanitarian Logistics Officers
• Business Intelligence Analysts
• Information Technology Professionals
• Researchers and Consultants
• Policy Makers
• Development Practitioners
• Digital Transformation Managers
• Artificial Intelligence Specialists
• Emergency Response Coordinators
• Organizational Development Specialists

Course Outline

Module 1: Foundations of Humanitarian Data Science

• Humanitarian data ecosystems
• Data science methodologies
• Humanitarian information management
• Data governance and quality assurance
• Ethical data management
• Case Study: Developing a humanitarian data management framework for multi-country emergency operations

Module 2: Statistical Analysis and Predictive Analytics

• Statistical modelling
• Predictive analytics
• Machine learning fundamentals
• Python and R programming
• SQL database management
• Case Study: Predicting humanitarian needs using machine learning and statistical forecasting models

Module 3: Geospatial Analytics and Humanitarian Intelligence

• Geographic Information Systems (GIS)
• Remote sensing
• Spatial analysis
• Humanitarian mapping
• Climate and disaster analytics
• Case Study: Applying GIS and satellite imagery to optimize humanitarian response and resource allocation

Module 4: Business Intelligence and Data Visualization

• Power BI dashboards
• Tableau analytics
• Excel for advanced analytics
• Interactive reporting
• Humanitarian performance dashboards
• Case Study: Building executive dashboards to monitor humanitarian programme performance and emergency operations

Module 5: Artificial Intelligence and Humanitarian Innovation

• Artificial Intelligence applications
• Natural Language Processing (NLP)
• Big data analytics
• Cloud computing
• Monitoring, Evaluation, Accountability, and Learning (MEAL)
• Case Study: Integrating Artificial Intelligence and business intelligence tools to strengthen humanitarian programme monitoring and decision-making

Module 6: Future Humanitarian Analytics and Digital Transformation

• Predictive humanitarian intelligence
• Digital transformation strategies
• Responsible Artificial Intelligence
• Organizational resilience through analytics
• Future trends in humanitarian data science
• Case Study: Designing a future-ready humanitarian data science strategy integrating predictive analytics, digital transformation, Artificial Intelligence, GIS, business intelligence, and evidence-based humanitarian leadership

General Information

1. Customized Training: All our courses can be tailored to meet the specific needs of participants.
2. Language Proficiency: Participants should have a good command of the English language.
3. Comprehensive Learning: Our training includes well-structured presentations, practical exercises, web-based tutorials, and collaborative group work. Our facilitators are seasoned experts with over a decade of experience.
4. Certification: Upon successful completion of training, participants will receive a certificate from Foscore Development Center (FDC-K).
5. Training Locations: Training sessions are conducted at Foscore Development Center (FDC-K) centers. We also offer options for in-house and online training, customized to the client's schedule.
6. Flexible Duration: Course durations are adaptable, and content can be adjusted to fit the required number of days.
7. Onsite Training Inclusions: The course fee for onsite training covers facilitation, training materials, two coffee breaks, a buffet lunch, and a Certificate of Successful Completion. Participants are responsible for their travel expenses, airport transfers, visa applications, dinners, health/accident insurance, and personal expenses.
8. Additional Services: Accommodation, pickup services, freight booking, and visa processing arrangements are available upon request at discounted rates.
9. Equipment: Tablets and laptops can be provided to participants at an additional cost.
10. Post-Training Support: We offer one year of free consultation and coaching after the course.
11. Group Discounts: Register as a group of more than two and enjoy a discount ranging from 10% to 50%.
12. Payment Terms: Payment should be made before the commencement of the training or as mutually agreed upon, to the Foscore Development Center account. This ensures better preparation for your training.
13. Contact Us: For any inquiries, please reach out to us at training@fdc-k.org or call us at +254712260031.
14. Website: Visit our website at www.fdc-k.org for more information.