Course Introduction
Informal settlement upgrading programmes generate extensive data on households, population characteristics, housing conditions, land and tenure arrangements, infrastructure, basic services, mobility, livelihoods, environmental risks, and community priorities. Effective analysis of this information helps planners and programme teams understand settlement conditions, identify infrastructure and service gaps, prioritize interventions, monitor upgrading activities, and allocate resources more effectively while maintaining community dignity and protecting sensitive household information.
This course provides practical approaches for collecting, cleaning, integrating, analyzing, and interpreting data used in informal settlement upgrading. Participants examine household surveys, settlement profiles, infrastructure inventories, service-access assessments, land and spatial information, socioeconomic data, project records, community consultations, and environmental datasets. Particular emphasis is placed on data quality, spatial accuracy, consistent settlement classifications, participatory data collection, and the integration of administrative, household, geospatial, and project-monitoring information.
Participants will develop practical skills in spreadsheet analysis, databases, dashboards, GIS, spatial analysis, descriptive statistics, trend analysis, segmentation, and programme performance reporting. They will learn how to analyze housing conditions, service coverage, infrastructure deficits, population density, tenure characteristics, project progress, household vulnerability, and access to essential facilities. The course demonstrates how these analytical capabilities can support settlement prioritization, infrastructure planning, upgrading design, project monitoring, community engagement, and evidence-based resource allocation.
The programme also introduces advanced tools including GIS, satellite imagery, remote sensing, mobile data collection, predictive analytics, artificial intelligence, digital mapping, and urban monitoring technologies. Participants explore how these tools can help identify settlement growth, infrastructure gaps, environmental risks, accessibility constraints, and changing service needs. Attention is given to spatial uncertainty, data bias, digital exclusion, appropriate interpretation of remotely sensed information, and the importance of combining technological analysis with local knowledge and participatory planning.
Informal settlement data can contain highly sensitive information about households, income, tenure, vulnerability, location, and access to services. The course therefore places strong emphasis on privacy, data governance, confidentiality, cybersecurity, ethical mapping, informed participation, and responsible information sharing. Participants explore how to protect household identities, minimize unnecessary collection of personal information, manage sensitive spatial datasets, and communicate analytical findings without increasing risks of stigma, discrimination, displacement, or misuse of information.
By the end of the course, participants will be able to develop practical analytical workflows for informal settlement upgrading programmes and produce useful programme intelligence for planners and decision-makers. They will be equipped to build settlement profiles, analyze infrastructure and service gaps, develop spatial dashboards, monitor upgrading projects, assess resilience and environmental risks, and communicate evidence clearly. The course ultimately supports data-informed upgrading that is inclusive, participatory, practical, resilient, and responsive to the needs and priorities of settlement communities.
Duration
5 days
Who Should Attend
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Informal settlement upgrading programme managers responsible for planning, implementation, coordination, and performance management.
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Urban planners working on settlement upgrading, spatial planning, land use, infrastructure, and neighbourhood development.
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Municipal and local government officials responsible for informal settlements, housing, urban services, and community development.
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Monitoring and evaluation professionals supporting settlement upgrading indicators, results frameworks, and programme reporting.
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GIS specialists and spatial data analysts working with settlement mapping, infrastructure inventories, and geographic information systems.
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Community development professionals involved in participatory planning, community engagement, and settlement profiling.
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Housing and social development officers assessing household needs, housing conditions, and service accessibility.
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Infrastructure planners working on water, sanitation, roads, drainage, electricity, waste management, and public facilities.
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Land and tenure professionals managing settlement mapping, land information, occupancy patterns, and development planning.
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Development project managers overseeing upgrading projects, contractors, budgets, schedules, and implementation performance.
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NGO and development partner professionals implementing informal settlement upgrading and urban development initiatives.
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Resilience and climate professionals assessing environmental hazards and climate-related risks in informal settlements.
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Data and information management officers supporting settlement information systems and project databases.
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Researchers and policy professionals studying informal settlements, urban poverty, service access, and upgrading outcomes.
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Professionals seeking practical data analytics capabilities for evidence-based informal settlement upgrading and urban development.
Course Objectives
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Develop practical skills for collecting, cleaning, integrating, and analyzing household, infrastructure, service, spatial, socioeconomic, and project data for informal settlement upgrading.
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Analyze settlement population characteristics, housing conditions, service access, tenure patterns, vulnerability, and infrastructure deficits to support evidence-based prioritization.
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Apply spreadsheet, database, dashboard, and business intelligence techniques to transform complex settlement datasets into actionable programme intelligence.
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Develop indicators for upgrading coverage, infrastructure delivery, service access, housing improvements, project progress, community participation, and programme outcomes.
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Use GIS and spatial analytics to map settlement boundaries, infrastructure networks, service gaps, population concentrations, environmental risks, and accessibility challenges.
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Apply trend, comparative, diagnostic, and predictive analytics to monitor settlement change, upgrading progress, service demand, infrastructure requirements, and emerging risks.
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Explore remote sensing, satellite imagery, mobile mapping, artificial intelligence, and other emerging technologies while recognizing spatial, ethical, and data-quality limitations.
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Strengthen settlement data governance through privacy, confidentiality, informed participation, secure information management, access controls, cybersecurity, and responsible data sharing.
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Develop dashboards, maps, visualizations, and analytical reports that communicate upgrading priorities and programme performance clearly to technical teams, communities, and decision-makers.
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Integrate analytical evidence into settlement prioritization, infrastructure planning, resource allocation, community engagement, climate resilience, project management, and inclusive urban development.
Comprehensive Course Outline
Module 1: Foundations of Data Analytics for Informal Settlement Upgrading
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Understanding the role of data analytics in informal settlement profiling, upgrading, housing improvement, infrastructure planning, and urban service delivery.
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Mapping the upgrading data lifecycle from settlement assessment and community profiling through intervention design, implementation, monitoring, and evaluation.
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Identifying analytical questions concerning housing conditions, infrastructure deficits, service coverage, vulnerability, tenure, environmental risk, and upgrading priorities.
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Understanding descriptive, diagnostic, predictive, and prescriptive analytics and their applications in settlement upgrading decision-making.
Module 2: Settlement Data Collection, Quality, Integration, and Community Profiling
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Designing reliable household and settlement data collection processes covering housing, services, livelihoods, demographics, tenure, infrastructure, and community priorities.
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Identifying missing, duplicate, outdated, inconsistent, and geographically inaccurate records that can compromise settlement analysis and planning.
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Integrating household surveys, GIS layers, infrastructure inventories, administrative records, project databases, community assessments, and environmental information.
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Applying data dictionaries, validation rules, metadata, standard classifications, quality assurance, and participatory verification to improve analytical reliability.
Module 3: Spreadsheet, Database, GIS, and Business Intelligence Analytics
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Applying spreadsheet formulas, pivot tables, filters, lookups, charts, and data-cleaning techniques to analyze informal settlement datasets efficiently.
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Understanding relational and spatial databases, unique identifiers, geographic relationships, queries, and data structures for settlement information management.
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Developing dashboards that combine settlement profiles, service coverage, infrastructure conditions, project progress, and geographic indicators.
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Applying accessible maps, charts, tables, and visualization techniques to communicate settlement conditions, priorities, gaps, and upgrading progress.
Module 4: Household, Housing, Population, and Vulnerability Analytics
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Analyzing household characteristics, population density, age profiles, household composition, livelihoods, housing conditions, and socioeconomic indicators.
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Examining housing quality, occupancy, overcrowding, building conditions, tenure arrangements, and other indicators relevant to upgrading priorities.
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Developing vulnerability profiles using appropriate socioeconomic, service-access, environmental, and demographic indicators without creating harmful or stigmatizing classifications.
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Applying segmentation and comparative analysis to understand differences between neighbourhoods, zones, household groups, and upgrading areas.
Module 5: Infrastructure, Basic Services, and Accessibility Analytics
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Analyzing access to water, sanitation, drainage, electricity, roads, waste management, public lighting, health, education, and other essential services.
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Using GIS and network analysis to assess service coverage, facility accessibility, infrastructure connectivity, and underserved settlement areas.
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Developing infrastructure-gap indicators to compare existing service levels with programme targets, population needs, and planned upgrading interventions.
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Applying service-access analytics to support infrastructure prioritization, facility planning, maintenance strategies, and coordinated upgrading investments.
Module 6: Upgrading Projects, Finance, Procurement, and Performance Analytics
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Monitoring upgrading project schedules, construction progress, budgets, procurement activities, contractors, physical outputs, and implementation milestones.
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Analyzing programme expenditure, unit costs, resource utilization, financing requirements, and variations across upgrading projects and locations.
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Applying variance, trend, cost, schedule, and performance analysis to identify implementation delays, resource pressures, and delivery bottlenecks.
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Developing project dashboards that connect financial, physical, geographic, procurement, and community-related indicators for management decision-making.
Module 7: GIS, Environmental Risk, Climate Resilience, and Settlement Growth Analytics
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Applying GIS and spatial analysis to monitor settlement expansion, population concentration, infrastructure patterns, environmental exposure, and land-use changes.
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Using satellite imagery and remote sensing to identify changes in built-up areas, drainage patterns, vegetation, environmental conditions, and settlement development.
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Analyzing exposure to flooding, landslides, heat, pollution, fire, drainage failures, and other environmental hazards relevant to settlement resilience.
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Using spatial intelligence to support resilience planning, risk reduction, infrastructure design, emergency preparedness, and prioritization of upgrading interventions.
Module 8: AI, Remote Sensing, Predictive Analytics, and Emerging Urban Technologies
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Exploring artificial intelligence and machine learning applications for settlement classification, infrastructure monitoring, service-demand forecasting, and urban development intelligence.
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Applying satellite imagery, mobile mapping, drones, sensors, digital platforms, and automated geospatial processing to improve settlement monitoring.
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Developing predictive approaches for population growth, infrastructure demand, service pressures, settlement expansion, and environmental risk where appropriate.
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Evaluating model assumptions, spatial bias, data quality, privacy, accessibility, explainability, digital exclusion, and human oversight when applying emerging technologies.
Module 9: Settlement Data Governance, Privacy, Cybersecurity, and Ethical Analytics
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Establishing governance frameworks covering household and settlement data ownership, access, quality, retention, documentation, accountability, and responsible information sharing.
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Protecting household, location, socioeconomic, tenure, and vulnerability information through access controls, secure storage, authentication, encryption, and cybersecurity measures.
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Addressing ethical challenges involving community profiling, sensitive locations, displacement risks, stigma, consent, re-identification, and inappropriate use of settlement information.
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Developing responsible analytical practices that support transparency, participation, privacy, community trust, inclusion, accountability, and safe use of upgrading data.
Module 10: Integrated Informal Settlement Upgrading Analytics Project
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Designing an end-to-end analytical project using realistic settlement, household, infrastructure, service, spatial, and project-performance data to address an upgrading decision.
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Cleaning, integrating, analyzing, and visualizing settlement information using spreadsheets, databases, GIS, dashboards, and appropriate analytical techniques.
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Developing an integrated settlement intelligence dashboard and analytical report containing key indicators, maps, infrastructure gaps, risks, project findings, and priorities.
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Presenting analytical findings and demonstrating how data can support upgrading prioritization, infrastructure investment, community engagement, resilience planning, and project performance.
Training Approach
This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.
Tailor-Made Course
This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808
Training Venue
The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.
Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant
Certification
Participants will be issued with Upskill certificate upon completion of this course.
Airport Pickup and Accommodation
Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808
Terms of Payment:
Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.
