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Advanced Artificial Intelligence for Humanitarian Operations Training Course

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How to Register Click View Schedule for your preferred location, select your training dates, then register as an individual, group, or online participant. You will receive an invitation letter and invoice promptly after submission.
Training Locations Kenya (Nairobi, Mombasa, Malindi, Kisumu, Nakuru, Nanyuki) · Tanzania (Dodoma, Zanzibar, Dar es Salaam) · Dubai UAE · South Africa (Pretoria, Cape Town) · Istanbul · Accra · Banjul more ▾
Groups & Payment Groups of 5+ receive one complimentary place — see group rates. Payment due at least 1 month before (Europe & Asia) or 2 weeks before (Africa programs).
Virtual / Online
Live, instructor-led — join from anywhere
552 dates
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Aug 17, 2026 Aug 21, 2026 5 days Virtual Onsite
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Classroom / In-Person
Same course & certificate — face-to-face
14 locations
Nairobi, Kenya Aug 17, 2026 (99)
Mombasa, Kenya Aug 17, 2026 (51)
Kampala, Uganda Aug 17, 2026 (27)
Accra, Ghana Aug 17, 2026 (30)
Istanbul, Turkey Aug 17, 2026 (15)
Kigali, Rwanda Aug 24, 2026 (50)
Pretoria, South Africa Aug 24, 2026 (49)

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

Advanced Artificial Intelligence for Humanitarian Operations Training Course

Course Overview

The Advanced Artificial Intelligence for Humanitarian Operations Training Course is designed to equip humanitarian professionals, United Nations agencies, government institutions, non-governmental organizations (NGOs), disaster risk management specialists, emergency response coordinators, data scientists, information technology professionals, innovation managers, Monitoring, Evaluation, Accountability and Learning (MEAL) specialists, Geographic Information Systems (GIS) analysts, researchers, policy makers, and humanitarian leaders with advanced knowledge and practical skills in applying Artificial Intelligence (AI) to improve humanitarian preparedness, emergency response, disaster recovery, resilience building, and sustainable development. As humanitarian crises become increasingly complex due to climate change, armed conflicts, pandemics, forced displacement, food insecurity, environmental degradation, and urban emergencies, Artificial Intelligence has become a transformative technology for predictive analytics, humanitarian logistics, decision support, resource optimization, risk assessment, beneficiary targeting, and operational coordination. This course provides comprehensive knowledge of Artificial Intelligence, Machine Learning, Deep Learning, Natural Language Processing (NLP), Computer Vision, Generative AI, Large Language Models (LLMs), Geographic Information Systems (GIS), predictive analytics, cloud computing, robotics, digital humanitarian platforms, and AI governance 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 advanced competencies in AI strategy development, machine learning model implementation, humanitarian data science, predictive disaster modelling, satellite imagery analysis, remote sensing, computer vision, Natural Language Processing (NLP), chatbot development, humanitarian information management, Geographic Information Systems (GIS), cloud-based AI platforms, digital twins, Internet of Things (IoT), AI-powered logistics optimization, emergency communication systems, humanitarian financing analytics, monitoring, evaluation, accountability, and learning (MEAL), cybersecurity, responsible AI governance, innovation management, organizational resilience, stakeholder collaboration, and evidence-based humanitarian decision-making. The training emphasizes integrating Artificial Intelligence into disaster preparedness, humanitarian logistics, public health, disease surveillance, refugee management, food security, nutrition, water, sanitation and hygiene (WASH), education in emergencies, protection programming, cash and voucher assistance (CVA), climate adaptation, emergency operations centers, and humanitarian recovery programmes. Through AI laboratories, practical coding demonstrations, simulation exercises, collaborative workshops, digital innovation projects, and international humanitarian case studies, participants will strengthen their ability to develop and deploy AI-enabled humanitarian solutions that improve operational efficiency, accountability, and humanitarian impact.

The course further explores emerging technologies including Generative AI, autonomous AI agents, reinforcement learning, explainable AI (XAI), federated learning, edge AI, quantum computing, blockchain integration, predictive humanitarian analytics, climate intelligence, digital humanitarian ecosystems, anticipatory action, AI ethics, bias mitigation, responsible AI governance, digital transformation leadership, organizational innovation, localization, sustainability, cybersecurity, privacy protection, and future humanitarian technology trends. Participants will gain practical skills in designing AI roadmaps, evaluating AI systems, managing AI implementation projects, developing ethical governance frameworks, improving institutional readiness, supporting digital inclusion, strengthening partnerships, and fostering innovation across humanitarian organizations. Special emphasis is placed on accountability to affected populations, transparency, human-centered AI, data privacy, gender-responsive AI applications, disability inclusion, environmental sustainability, and responsible technology adoption.

Upon successful completion of the course, participants will possess the expertise to strategically design, implement, manage, and evaluate Artificial Intelligence solutions that strengthen humanitarian preparedness, improve emergency response, optimize humanitarian logistics, enhance organizational resilience, support data-driven decision-making, accelerate digital transformation, and build future-ready humanitarian organizations capable of responding effectively to evolving global crises. Organizations will benefit from enhanced operational efficiency, stronger predictive capabilities, improved programme quality, optimized resource allocation, strengthened digital governance, increased innovation capacity, improved donor confidence, enhanced collaboration, and sustainable humanitarian outcomes.

Course Objectives

  1. Understand advanced Artificial Intelligence concepts and their application in humanitarian operations.
  2. Apply Machine Learning, Deep Learning, Natural Language Processing (NLP), and Computer Vision to humanitarian challenges.
  3. Utilize AI-powered predictive analytics for disaster preparedness, risk assessment, and emergency response.
  4. Integrate Geographic Information Systems (GIS), remote sensing, and AI for humanitarian decision support.
  5. Strengthen humanitarian logistics, supply chain management, and resource optimization using Artificial Intelligence.
  6. Develop ethical AI governance, cybersecurity, data privacy, and responsible AI implementation strategies.
  7. Strengthen Monitoring, Evaluation, Accountability, and Learning (MEAL) systems using AI-driven analytics.
  8. Promote innovation, organizational resilience, and digital transformation through Artificial Intelligence.
  9. Build AI-enabled humanitarian programmes that improve efficiency, transparency, and accountability.
  10. Develop future-ready humanitarian organizations capable of leveraging emerging Artificial Intelligence technologies responsibly.

Organization Benefits

  1. Enhances organizational digital transformation and Artificial Intelligence capabilities.
  2. Improves disaster preparedness and emergency response through predictive analytics.
  3. Strengthens humanitarian logistics and operational efficiency.
  4. Enhances evidence-based decision-making using AI-powered insights.
  5. Improves monitoring, evaluation, accountability, and programme performance.
  6. Strengthens cybersecurity, digital governance, and responsible AI management.
  7. Optimizes humanitarian resource allocation and operational planning.
  8. Increases innovation capacity and organizational resilience.
  9. Enhances donor confidence through transparent, data-driven programme management.
  10. Builds future-ready humanitarian organizations capable of leveraging advanced Artificial Intelligence technologies.

Target Participants

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

Course Outline

Module 1: Foundations of Artificial Intelligence for Humanitarian Operations

  • Artificial Intelligence concepts and frameworks
  • Machine Learning and Deep Learning
  • AI strategy for humanitarian organizations
  • AI governance and ethics
  • Digital transformation for humanitarian operations
  • Case Study: Developing an AI strategy to improve humanitarian emergency preparedness and response

Module 2: AI Applications in Humanitarian Decision-Making

  • Predictive analytics and forecasting
  • Natural Language Processing (NLP)
  • Computer Vision and image recognition
  • Geographic Information Systems (GIS) integration
  • Remote sensing and satellite analytics
  • Case Study: Applying AI, GIS, and satellite imagery to predict floods and optimize humanitarian resource allocation

Module 3: AI-Enabled Humanitarian Operations

  • AI-powered humanitarian logistics
  • Smart emergency operations centers
  • Humanitarian chatbots and virtual assistants
  • Digital humanitarian platforms
  • Internet of Things (IoT) integration
  • Case Study: Using AI-driven logistics optimization to improve emergency supply chain management during disaster response

Module 4: AI Governance, Cybersecurity and Responsible Innovation

  • Responsible Artificial Intelligence
  • Explainable AI (XAI)
  • Cybersecurity and AI risk management
  • Data governance and privacy
  • AI policy development
  • Case Study: Designing an ethical AI governance framework for humanitarian organizations operating across multiple countries

Module 5: AI for Monitoring, Evaluation and Organizational Performance

  • AI-powered Monitoring, Evaluation, Accountability, and Learning (MEAL)
  • Business intelligence dashboards
  • Performance analytics
  • Organizational resilience
  • Innovation management
  • Case Study: Strengthening humanitarian programme monitoring and organizational performance using AI-powered analytics and decision-support systems

Module 6: Future Artificial Intelligence and Humanitarian Innovation

  • Generative AI and Large Language Models (LLMs)
  • Autonomous AI agents
  • Climate intelligence and predictive humanitarian systems
  • Future AI technologies
  • Strategic Artificial Intelligence transformation planning
  • Case Study: Developing a future-ready Artificial Intelligence roadmap integrating innovation, digital transformation, sustainability, responsible AI governance, and resilient humanitarian operations

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.

 

 

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