EvalCommunity Academy · Certificate Course
Put AI to work in your evaluation practice. Keep your judgment in charge.
A practical course for M&E professionals who want AI workflows for evaluation design, data, qualitative and quantitative analysis, and reporting, without losing the rigor that makes findings credible.
6
modules
50
lessons, bonuses & appendices
22–28 h
self-paced learning
4.9/5
from 2,300+ learners
No coding required · Certificate included · Lifetime access · 10-day money-back guarantee
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AI as an assistant. Your judgment stays in charge.
Faster transcript coding, cleaner datasets and clearer reports are real gains, but only if the evidence underneath is sound. You will learn to use AI in ways you can explain to donors, defend in peer review and trust in your own practice. The curriculum was field-tested with evaluators from government agencies, consultancies, universities and non-profits.
From pressure to practice
The pressure most M&E teams feel
- Hours lost coding transcripts and open-ended responses by hand
- Messy datasets that slow analysis and complicate reporting
- Stakeholders expecting faster findings and sharper recommendations
- Uncertainty about using AI responsibly with sensitive program data
What you will be able to do
- Run AI-assisted qualitative coding you can audit and explain
- Clean and prepare datasets faster, with human verification
- Turn evidence into clear findings, briefs and presentations
- Apply privacy safeguards, bias checks and human review at every stage
Curriculum
Six modules, one clear pathway
36 lessons · 6 module quizzes · course review · 13 bonuses and appendices. Tap a module to see its lessons.
Module I3–4 hours · 6 lessons + quizAI Foundations for M&E, Prompt Engineering, Tools, Ethics, Responsible Use & Governance FrameworksHow AI works, where bias enters, the governance frameworks that apply, and how to keep humans in the loop.View lessons +
- AI Essentials & How AI Transforms Traditional M&E Practice
- AI Prompts for Evaluation
- Ethics, Bias & Responsible AI in M&E
- Managing AI Risks, Human-in-the-Loop QA & Adoption Barriers
- AI Governance & Institutional Frameworks for M&E and International Development
- AI Observability & Monitoring in M&E Systems
- Quiz: AI Foundations, Ethics & M&E Practice
Module II3–4 hours · 6 lessons + quizAI for Evaluation Design, Frameworks & Decision LogicMethodology selection, theories of change, logframes, rubrics, TORs, inception reports and adaptive management.View lessons +
- AI for Evaluation Design & Methodology Selection
- AI-Driven Theories of Change, Logframes & Indicator Design
- AI for Rubric Development & Evaluative Reasoning
- AI for Evaluation Products: TORs, Inception Reports & Evaluation Matrices
- Embedding AI into M&E Systems & Framework Architecture
- AI for Decision-Making & Adaptive Management Systems
- Quiz: AI for Evaluation Design, Frameworks & Decision Logic
Module III4–5 hours · 6 lessons + quizAI for Data Collection, Management & MonitoringSurveys, chatbots and multilingual methods, geospatial evidence, data cleaning, real-time monitoring and dashboards.View lessons +
- AI-Driven Data Collection: Surveys, Chatbots, Voice & Multilingual Methods
- Big Data & Geospatial Evidence for Evaluation
- AI for Data Processing, Cleaning & Quality Assurance
- AI-Powered Real-Time Monitoring Systems
- AI-Powered Dashboards & Automated Reporting
- Debugging & Validating AI Systems in M&E
- Quiz: AI for Data Collection & Management in M&E
Module IV3–4 hours · 6 lessons + quizAI for Qualitative & Mixed-Methods Sense-MakingText and sentiment analysis, qualitative coding, evidence synthesis, and participatory and developmental evaluation.View lessons +
- Text & Sentiment Analysis with NLP for Qualitative Evidence
- AI-Assisted Qualitative Coding & Thematic Analysis
- AI for Evidence Synthesis & Systematic Reviews
- AI for Participatory & Utilization-Focused Evaluation
- AI for Developmental Evaluation
- AI for Evidence-Informed Policy
- Quiz: AI for Qualitative & Mixed-Methods Sense-Making
Module V4–5 hours · 6 lessons + quizAI for Quantitative Analysis, Impact & Evaluation QualityQuantitative analytics, predictive modeling, causal inference, contribution analysis and meta-evaluation standards.View lessons +
- AI-Enhanced Data Analysis for M&E (Quantitative Analytics)
- Predictive Modeling with AI for M&E
- AI for Causal Inference & Impact Evaluation
- AI for Contribution Analysis & Process Tracing
- AI for Social Impact Measurement
- AI for Meta-Evaluation & Evaluation Quality Standards (OECD-DAC, AEA, EES)
- Quiz: AI for Quantitative Analysis, Impact & Evaluation Quality
Module VI5–6 hours · 6 lessons + review + quizAI for Communication, Implementation & Intelligent SystemsEvaluation writing, data storytelling, AI-ready teams, AI agents, and a capstone lab designing an AI-powered M&E system.View lessons +
- AI for Evaluation Writing & Knowledge Products
- AI for Data Storytelling & Visualization
- AI-Ready Teams & Smart Budgeting for M&E
- The AI Tools Ecosystem for M&E
- AI Agents for M&E: Automating Evaluation Workflows
- Capstone Lab: Designing an AI-Powered M&E System
- Course Review & Your AI-M&E Professional Toolkit
- Quiz: AI for Communication, Implementation & Intelligent Systems
Included13 itemsBonuses & AppendicesCase studies, tutorials, 100 FAQs, a tool finder, prompt examples, checklists and governance tools.View all 13 +
- Bonus 1: Case Studies
- Bonus 2: Tutorials
- Bonus 3: AI in M&E 100 FAQs
- Bonus 4: Find the Right AI Tool for Each M&E Task
- Bonus 5: AI Families for M&E & Development
- Bonus 6: Human-First AI Manifesto
- Appendix A: Glossary of Key Terms
- Appendix B: AI Tools & Platforms
- Appendix C: AI Prompts & Examples for M&E
- Appendix D: Ethical & Risk Checklist
- Appendix E: AI Governance Tools
- Appendix F: AI in M&E Workflow
- Appendix G: Why Source Documents Matter
What you leave with
Reusable tools, not just concepts. Every module produces something you can use on your next assignment.
Prompt library
Tested prompts for planning, coding, analysis, reporting and learning tasks.
Ethics & risk checklist
Guardrails for privacy, bias, sensitive data, transparency and human review.
Tool comparison matrix
Choose the right AI tool for the task, the data type and the risk level.
Workflow examples
Applied workflows for design, coding, data quality, synthesis and reporting.
Capstone artifact
A portfolio piece designing an AI-powered M&E system, ready to show clients or employers.
Certificate
An EvalCommunity Academy certificate when you complete the course.
Free preview
Download the AI in M&E Course Guide
Study roadmap, module checklists, the risk traffic-light test, ethical AI principles, prompt workflow guidance and capstone support.
Learn at a pace that fits your workload
Most learners finish in 4–6 weeks at 3–5 hours per week. One module a week works well, but you set the pace.
WEEK 1
Foundations
WEEK 2
Design
WEEK 3
Data
WEEK 4
Qualitative
WEEK 5
Quantitative
WEEK 6
Communication
2,300+ learners · rated 4.9/5
What M&E professionals are saying
★★★★★
“This course is a game-changer! It’s the perfect blend of practical tools, engaging lessons, and real-world applications. I now feel equipped to incorporate AI into every stage of my M&E workflow.”
David C.
M&E Professional
★★★★★
“Practical, clear, and genuinely useful. This course delivers exactly what it promises: practical, hands-on ways to use AI in real Monitoring & Evaluation work.”
Mike R.
Evaluation Consultant
★★★★★
“I came into this course curious about AI but unsure how it fit into M&E. By the end, I was confidently using AI tools for survey analysis and reporting.”
Ibrahim A.
M&E Specialist
Choose your option
One-time payment. Lifetime access. No subscription. 10-day money-back guarantee.
Individual course
AI in Monitoring & Evaluation
$245
One-time payment · self-paced
- ✓ 6 modules, 36 lessons, 6 quizzes
- ✓ 13 bonuses and appendices
- ✓ Prompt library, checklists and templates
- ✓ Course guide and capstone support
- ✓ EvalCommunity Academy certificate
Best value
The Professional Bundle
AI in M&E + AI Agents for Evaluators
$349
Two certificate courses · save $141 vs. buying separately
- ✓ Everything in the individual course
- ✓ AI Agents for Evaluators course
- ✓ No-code agent workflows for reporting, coding and indicator tracking
- ✓ Two certificates, one purchase
Training a team? Save up to 30%.
For NGOs, agencies, universities and consulting firms enrolling 5 or more people. Individual accounts and certificates, no shared logins.
Common questions
Do I need coding or AI experience?
No. The course is designed for M&E professionals with no coding background. If you are comfortable with Excel and email, you are ready.
How long does it take to complete?
The six modules take about 22–28 hours in total. Most learners finish in 4–6 weeks at 3–5 hours per week, and you keep lifetime access.
Is sensitive M&E data safe when I use AI tools?
The course teaches data minimization, anonymization, privacy safeguards, bias checks and human review, so you can decide what should and should not go into an AI tool.
Does it cover qualitative and quantitative work?
Yes. Module IV covers qualitative and mixed-methods sense-making. Module V covers quantitative analysis, impact evaluation and evaluation quality.
Can my organization enroll a team?
Yes. Teams of 5 or more save up to 30%, with individual accounts and certificates. View group pricing.
What is the refund policy?
The course includes a 10-day money-back guarantee. If it is not the right fit, contact EvalCommunity within 10 days of purchase.
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Build AI skills your next evaluation will use
Practical workflows for design, analysis and reporting, with professional judgment, ethics and evidence quality at the center.
Self-paced · Certificate included · 10-day money-back guarantee
Course Features
- Lectures 50
- Quizzes 6
- Duration Lifetime access
- Skill level Intermediate
- Language English
- Students 2396
- Certificate Yes
- Assessments Yes
- 7 Sections
- 50 Lessons
- Lifetime
Expand all sectionsCollapse all sections
- Module I: AI Foundations for M&E, Prompt Engineering, Tools, Ethics, Responsible Use & Governance Frameworks (3–4 hours)7 Items
- 1.1Module I – Lesson 1: AI Essentials & How AI Transforms Traditional M&E Practice
- 1.2Module I – Lesson 2: AI Prompts for Evaluation
- 1.3Module I – Lesson 3: Ethics, Bias & Responsible AI in M&E
- 1.4Module I – Lesson 4: Managing AI Risks, Human-in-the-Loop QA & Adoption Barriers
- 1.5Module I – Lesson 5: AI Governance & Institutional Frameworks for M&E and International Development
- 1.6Module I – Lesson 6: AI Observability & Monitoring in M&E Systems
- 1.7Module I Quiz: AI Foundations, Ethics & M&E Practice10 Questions
- Module II: AI for Evaluation Design, Frameworks & Decision Logic (3–4 hours)7 Items
- 2.1Module II – Lesson 1: AI for Evaluation Design & Methodology Selection
- 2.2Module II – Lesson 2: AI-Driven Theories of Change, Logframes & Indicator Design
- 2.3Module II – Lesson 3: AI for Rubric Development & Evaluative Reasoning
- 2.4Module II – Lesson 4: AI for Evaluation Products: TORs, Inception Reports & Evaluation Matrices
- 2.5Module II – Lesson 5: Embedding AI into M&E Systems & Framework Architecture
- 2.6Module II – Lesson 6: AI for Decision-Making & Adaptive Management Systems
- 2.7Module II Quiz: AI for Evaluation Design, Frameworks & Decision Logic10 Questions
- Module III: AI for Data Collection, Management & Monitoring (4–5 hours)7 Items
- 3.1Module III – Lesson 1: AI-Driven Data Collection: Surveys, Chatbots, Voice & Multilingual Methods
- 3.2Module III – Lesson 2: Big Data & Geospatial Evidence for Evaluation
- 3.3Module III – Lesson 3: AI for Data Processing, Cleaning & Quality Assurance
- 3.4Module III – Lesson 4: AI-Powered Real-Time Monitoring Systems
- 3.5Module III – Lesson 5: AI-Powered Dashboards & Automated Reporting
- 3.6Module III – Lesson 6: Debugging & Validating AI Systems in M&E
- 3.7Module III Quiz: AI for Data Collection & Management in M&E15 Questions
- Module IV: AI for Qualitative & Mixed-Methods Sense-Making (3–4 hours)7 Items
- 4.1Module IV – Lesson 1: Text & Sentiment Analysis with NLP for Qualitative Evidence
- 4.2Module IV – Lesson 2: AI-Assisted Qualitative Coding & Thematic Analysis
- 4.3Module IV – Lesson 3: AI for Evidence Synthesis & Systematic Reviews
- 4.4Module IV – Lesson 4: AI for Participatory & Utilization-Focused Evaluation
- 4.5Module IV – Lesson 5: AI for Developmental Evaluation
- 4.6Module IV – Lesson 6: AI for Evidence-Informed Policy
- 4.7Module IV Quiz: AI for Qualitative & Mixed-Methods Sense-Making10 Questions
- Module V: AI for Quantitative Analysis, Impact & Evaluation Quality (4–5 hours)7 Items
- 5.1Module V – Lesson 1: AI-Enhanced Data Analysis for M&E (Quantitative Analytics)
- 5.2Module V – Lesson 2: Predictive Modeling with AI for M&E
- 5.3Module V – Lesson 3: AI for Causal Inference & Impact Evaluation
- 5.4Module V – Lesson 4: AI for Contribution Analysis & Process Tracing
- 5.5Module V – Lesson 5: AI for Social Impact Measurement
- 5.6Module V – Lesson 6: AI for Meta-Evaluation & Evaluation Quality Standards (OECD-DAC, AEA, EES)
- 5.7Module V – Quiz: AI for Quantitative Analysis, Impact & Evaluation Quality10 Questions
- Module VI: AI for Communication, Implementation & Intelligent Systems (5–6 hours)8 Items
- 6.1Module VI – Lesson 1: AI for Evaluation Writing & Knowledge Products
- 6.2Module VI – Lesson 2: AI for Data Storytelling & Visualization
- 6.3Module VI – Lesson 3: AI-Ready Teams & Smart Budgeting for M&E
- 6.4Module VI – Lesson 4: The AI Tools Ecosystem for M&E
- 6.5Module VI – Lesson 5: AI Agents for M&E – Automating Evaluation Workflows
- 6.6Module VI – Lesson 6: Capstone Lab – Designing an AI-Powered M&E System
- 6.7Course Review & Your AI-M&E Professional Toolkit
- 6.8Module VI – Quiz: AI for Communication, Implementation & Intelligent Systems10 Questions
- Bonuses and Appendices13 Items
- 7.1Bonus 1 – Case Studies
- 7.2Bonus 2 – Tutorials
- 7.3Bonus 3 – AI in M&E 100 FAQs
- 7.4Bonus 4 – Find the Right AI Tool for Each M&E Task
- 7.5Bonus 5 – AI Families for M&E & Development
- 7.6Bonus 6 – Human-First AI Manifesto
- 7.7Appendix A – Glossary of Key Terms
- 7.8Appendix B – AI Tools & Platforms
- 7.9Appendix C – AI Prompts & Examples for M&E
- 7.10Appendix D – Ethical & Risk Checklist
- 7.11Appendix E – AI Governance Tools
- 7.12Appendix F – AI in M&E Workflow
- 7.13Appendix H – Why Source Documents Matter
Target audiences
- Monitoring & Evaluation professionals across NGOs, government, and donor agencies
- Data analysts, researchers, and program managers seeking AI proficiency
- Development practitioners advancing their digital capabilities
- Professionals transitioning from AI curiosity to practical implementation
