Home Course Comprehensive Course on Monitoring and Evaluation About the Course Programmes and projects do not succeed by accident. They succeed because someone is paying attention, tracking progress, identifying problems early, measuring results, and using evidence to make better decisions. Monitoring and evaluation (M&E) is the discipline that makes this possible. It is not a bureaucratic requirement or an afterthought to programme design; it is a core management and accountability function that keeps interventions on track, supports course correction during implementation and generates the evidence needed to demonstrate impact. Without effective M&E, it is difficult to justify investment, demonstrate value for money, or make a convincing business case for a project or programme. Despite its importance, M&E is frequently misunderstood, poorly designed, or inadequately resourced. Many organisations collect data without a clear framework for what to measure or why. Others produce M&E reports that sit on shelves rather than informing decisions. The gap between data collection and data use remains one of the most persistent challenges in the development, public health and government sectors. This course closes that gap. This comprehensive M&E course provides participants with a rigorous grounding in M&E theory, frameworks, and practice — from the design of logical frameworks and indicator systems through to data collection, analysis, and the communication of findings to decision-makers and policymakers. Course Objectives This course is suitable for programme managers, M&E officers, development practitioners, government officials, and other professionals responsible for designing, implementing, or overseeing M&E systems. No prior M&E experience is required. The course equips participants with five core capabilities: Meaning of M&E: Participants will develop a clear understanding of the philosophy, principles, and purpose of M&E. They will distinguish between monitoring and evaluation, understand different types of evaluation, and appreciate the role of M&E across different programmatic and institutional contexts. M&E theory: Participants will understand the theory of change underpinning results-based management, construct logical frameworks that link programme inputs, activities, outputs, outcomes, and impact, and build comprehensive M&E frameworks that translate programme logic into a structured system for tracking performance. Indicators and target setting: Participants will design SMART performance indicators that are  appropriate to their programme context and understand the distinction between different types of indicators. They will also learn how indicator targets are set for programme interventions. Data collection for M&E: Participants will understand the types of data relevant to M&E. The session covers a wide range of data collection methods and tools, including quantitative and qualitative approaches, selecting and applying those most appropriate to their programme context and available resources. Data analysis, reporting and utilisation: Participants will analyse M&E data in Microsoft Excel, accurately interpret findings, and produce clear, well-structured reports. They will also develop the skills to communicate M&E results effectively to policymakers, funders, and other stakeholders, translating evidence into actionable recommendations that drive programme improvement and advocacy. Hence, the course will go beyond teaching M&E to MERLA. Course Outcomes After completing this course, participants will have a thorough grounding in the meaning, theory, and practice of M&E and the practical skills to design and implement M&E systems that generate credible, decision-relevant evidence. Participants will leave not only understanding what M&E is, but also knowing how to design and implement it effectively in their own organisational contexts. They will also learn to apply artificial intelligence tools to support key stages of the M&E. Course Content In-Person (5 Days) Virtual (5 Weeks) Day 1: Introduction to M&E Understand the philosophy, principles and purpose of M&E, distinguish between M&E, and appreciate the role of M&E across different programmatic and institutional contexts Explore different types of evaluation and develop a foundational understanding of logic models and results-based logical frameworks. Day 2: M&E Frameworks and Indicators Build a comprehensive M&E framework that translates programme logic into a structured system for tracking performance Design performance indicators appropriate to a programme context, understand different indicator types and develop the skills to set realistic, evidence-informed targets   Day 3: Data Collection for M&E Understand the types of data relevant to M&E, including quantitative and qualitative data collection methods and tools Select and apply data collection approaches appropriate to the programme context and available resources, and develop data collection instruments. Learn real-time electronic data collection for M&E Day 4: Data Analysis and Interpretation Analyse M&E data systematically using Microsoft Excel and apply appropriate analytical techniques to extract meaningful findings Interpret M&E findings accurately and understand what the evidence says and does not say about programme performance Day 5: Reporting, Utilisation and Synthesis Produce clear, well-structured M&E reports and develop the skills to communicate findings effectively to policymakers, funders and other stakeholders Go beyond M&E to MERLA. Translate M&E evidence into actionable recommendations, and consolidate learning through a final project and presentations Week 1: Introduction to M&E Understand the philosophy, principles and purpose of M&E, distinguish between M&E, and appreciate the role of M&E across different programmatic and institutional contexts Explore different types of evaluation and develop a foundational understanding of logic models and results-based logical frameworks. Week 2: M&E Frameworks and Indicators Build a comprehensive M&E framework that translates programme logic into a structured system for tracking performance Design performance indicators appropriate to a programme context, understand different indicator types and develop the skills to set realistic, evidence-informed targets   Week 3: Data Collection for M&E Understand the types of data relevant to M&E, including quantitative and qualitative data collection methods and tools Select and apply data collection approaches appropriate to the programme context and available resources, and develop data collection instruments. Learn real-time electronic data collection for M&E Week 4: Data Analysis and Interpretation Analyse M&E data systematically using Microsoft Excel and apply appropriate analytical techniques to extract meaningful findings Interpret M&E findings accurately and understand what the evidence says and does not say about programme performance Week 5: Reporting, Utilisation and Synthesis Produce clear, well-structured M&E reports and develop the skills to communicate findings effectively to policymakers, funders and other stakeholders Go beyond M&E to MERLA. Translate M&E evidence into actionable recommendations,