Qualitative data—rich narratives from interviews, focus groups, and open-ended surveys—is crucial for understanding the why and how of program impact, but its analysis is traditionally time-consuming and resource-intensive. This training course is designed to empower M&E professionals to leverage the power of AI-driven qualitative analysis. By using advanced tools, participants will learn how to automate tasks like transcription, thematic coding, and sentiment analysis, enabling them to process vast amounts of unstructured data with unprecedented speed and accuracy. This shift frees up valuable time for higher-level strategic interpretation and decision-making.

This comprehensive program provides a practical, hands-on roadmap for ethically and effectively integrating AI into qualitative M&E. Participants will gain skills in everything from selecting the right AI tools and auditing for algorithmic bias to ensuring data privacy and presenting complex findings in a compelling way. The course is a strategic investment for organizations seeking to enhance the depth and speed of their learning cycles, ensuring their work is a force for positive change in a world that needs it most.

Duration: 10 days

Target Audience:

• M&E Specialists
• Researchers
• Program and Project Managers
• Data Analysts
• Social Scientists
• Civil Society Leaders
• Humanitarian Aid Workers
• Consultants
• Public Health Practitioners
• Strategic Planners

Objectives:

• Understand the core principles of AI-driven qualitative analysis.
• Master the process of designing a framework for AI-assisted qualitative M&E.
• Learn how to select and use a variety of AI tools for qualitative analysis.
• Develop a data collection and analysis plan for unstructured data.
• Integrate ethical considerations and safety protocols.
• Build a more participatory and inclusive approach to AI-driven analysis.
• Communicate findings from AI-driven analysis to different audiences.
• Ensure ethical considerations and safety protocols in data collection.
• Foster a culture of continuous learning and adaptive management.
• Apply AI-driven techniques to a wide range of sectors.

Course Modules:

Module 1: Foundations of Qualitative M&E

• The importance of qualitative data in M&E
• Defining qualitative analysis and its purpose
• The limitations of traditional qualitative analysis
• An overview of the M&E workflow
• The difference between qualitative and quantitative data

Module 2: Introduction to AI for Qualitative Analysis

• The rise of AI and its potential in M&E
• Defining AI, machine learning, and their relevance
• The business case for AI in qualitative analysis
• An overview of the AI-driven workflow
• Key challenges and opportunities

Module 3: AI-Powered Data Collection

• The importance of a clear and secure data collection plan
• The use of AI for automatic transcription of interviews and focus groups
• The role of an AI-powered survey platform
• The importance of a clear and consistent reporting style
• Practical labs on a basic data collection tool

Module 4: AI-Driven Thematic Analysis

• The concept of a "codebook" and its purpose
• The use of AI for automatic coding and theme identification
• The role of a human in the loop for quality control
• The difference between a simple and a comprehensive analysis
• Practical labs on a basic thematic analysis tool

Module 5: Sentiment and Emotion Analysis

• The concept of sentiment and its purpose
• The use of AI for sentiment analysis of a text
• The role of a "sentiment score" and a "sentiment map"
• The importance of a clear and consistent reporting style
• Case studies on effective sentiment analysis

Module 6: Data Visualization and Storytelling

• The importance of a clear and compelling narrative
• Using dashboards and visualizations to communicate insights
• The role of a "data story map"
• The use of an AI-powered visualization tool
• Practical labs on building a data story

Module 7: Ethical Considerations and Safety

• The importance of a "do no harm" approach
• Ensuring the safety and privacy of participants
• The role of informed consent in a crisis
• The importance of a community-led ethical review process
• Protocols for handling sensitive and potentially harmful data

Module 8: M&E for a Diverse Audience

• The importance of knowing your audience
• The role of a "stakeholder analysis"
• Designing reports and dashboards for non-technical audiences
• The importance of accessibility and inclusivity
• Case studies on communicating with different audiences

Module 9: Mainstreaming AI in M&E

• How to integrate AI into the project cycle
• The importance of a phased implementation strategy
• The role of AI in the project cycle
• Building a culture of adaptive management
• Case studies on successful integration

Module 10: The Role of the M&E Professional

• Shifting from a technician to a facilitator
• The skills required for an AI-driven M&E professional
• Managing power dynamics and group conflicts
• The importance of a non-judgmental and empathetic approach
• The ethical responsibilities of the M&E professional

Module 11: M&E for a Diverse AI Sector

• M&E for AI in public health
• M&E for AI in humanitarian response
• M&E for AI in governance and social protection
• M&E for AI in climate change and environment
• M&E for AI in education and livelihoods

Module 12: The Future of AI in M&E

• The role of AI and machine learning in automated analysis
• The potential of blockchain for data integrity
• The use of new data sources (e.g., IoT sensors)
• The rise of complexity-aware M&E
• The long-term implications for the sector

Module 13: CBM and AI

• The potential of community-based monitoring with AI
• Training community members as monitors
• The importance of a participatory approach
• The role of a feedback mechanism for continuous learning
• The long-term benefits of a community-led system

Module 14: Practical Application and Simulation

• A hands-on simulation of a real-world project
• Participants work in teams to design an AI-driven framework
• Troubleshooting common challenges in data collection
• Analyzing and interpreting a set of data
• Peer review and feedback sessions on framework design

Module 15: Building Your AI-Driven Roadmap

• Creating a customized plan for a new project
• Identifying key stakeholders and securing buy-in
• Developing a phased implementation strategy
• Measuring the ROI and business impact of the investment
• Final Q&A and course wrap-up

Module 16: The Role of a Responsible AI Team

• The importance of a cross-functional team
• The role of a data scientist, a data analyst, and an M&E specialist
• The importance of a clear and consistent reporting style
• The long-term implications for the organization
• The importance of a "responsible AI" framework

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: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute 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: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 10 working days before commencement of the training.