Course Details

AI and Machine Learning in Development Evaluation Training Course

INTRODUCTION

This essential training course provides comprehensive knowledge and practical skills for leveraging Artificial Intelligence (AI) and Machine Learning (ML) in Development Evaluation. Recognizing the immense potential of these advanced technologies to enhance the efficiency, depth, and scale of evaluation efforts, this program equips participants with a systematic understanding of AI/ML concepts, their ethical implications, and practical applications in analyzing complex development data. Participants will gain deep insights into predictive analytics, natural language processing for qualitative data, image recognition for remote sensing, and responsible AI deployment, all crucial for generating more robust evidence, improving program design, and accelerating progress towards sustainable development goals. This course is ideal for M&E specialists, data scientists, researchers, policymakers, and anyone seeking to innovate their evaluation approaches for greater impact.

DURATION

10 days

TARGET AUDIENCE

This course is specifically designed for professionals involved in monitoring, evaluation, research, and data analysis in the development sector, as well as data scientists interested in social impact, including:

• Monitoring and Evaluation (M&E) Specialists.
• Data Scientists and Analysts working in development.
• Researchers and Academics focused on social impact.
• Policymakers and Program Designers.
• Funders and Grant Managers interested in innovative evaluation.

OBJECTIVES

Upon completion of this course, participants will be able to:

• Understand the fundamental concepts of AI and Machine Learning relevant to evaluation.
• Identify appropriate AI/ML techniques for various development evaluation challenges.
• Apply basic AI/ML tools for data analysis, prediction, and insight generation.
• Recognize the ethical considerations and risks associated with AI/ML in evaluation.
• Critically assess the potential and limitations of AI/ML for improving development outcomes.

MODULES

Module 1: Foundations of AI and Machine Learning for Evaluation

• Define Artificial Intelligence (AI) and Machine Learning (ML) and their sub-fields.
• Explore the relevance of AI/ML to addressing complex challenges in development evaluation.
• Understand the core concepts: data, algorithms, models, training, prediction.
• Discuss the difference between supervised, unsupervised, and reinforcement learning.
• Examine real-world examples of AI/ML applications in various development sectors.

Module 2: Data Preparation and Feature Engineering for AI/ML

• Understand the critical importance of data quality for AI/ML models.
• Discuss techniques for cleaning, transforming, and structuring diverse evaluation datasets.
• Explore feature engineering: creating new variables from existing data for model improvement.
• Examine strategies for handling missing data, outliers, and imbalanced datasets.
• Learn about ethical data sourcing and bias considerations in data preparation.

Module 3: Predictive Analytics for Outcome Forecasting

• Understand the concept of predictive modeling in evaluation (e.g., forecasting program outcomes).
• Explore common supervised learning algorithms (e.g., Linear Regression, Logistic Regression, Decision Trees).
• Discuss how to train, validate, and test predictive models.
• Examine metrics for evaluating model performance (e.g., accuracy, precision, recall).
• Learn about interpreting model outputs and their implications for M&E.

Module 4: Natural Language Processing (NLP) for Qualitative Data

• Understand the basics of Natural Language Processing (NLP) for text analysis.
• Discuss how NLP can extract insights from qualitative M&E data (e.g., interview transcripts, reports).
• Explore techniques like sentiment analysis, topic modeling, and keyword extraction.
• Examine challenges of NLP in diverse languages and low-resource settings.
• Learn about tools and libraries for performing basic NLP tasks.

Module 5: Computer Vision and Geospatial AI for Evaluation

• Understand the application of computer vision for analyzing images and video data.
• Discuss how satellite imagery and drones combined with AI can monitor changes in infrastructure, land use, or crop health.
• Explore object detection and classification for counting assets or identifying phenomena.
• Examine the integration of geospatial data with AI for spatial targeting and impact assessment.
• Learn about tools for image processing and basic computer vision tasks.

Module 6: Ethical AI in Development Evaluation

• Understand the critical ethical considerations of deploying AI/ML in sensitive development contexts.
• Discuss issues of bias, fairness, transparency, and accountability in AI algorithms.
• Explore responsible AI principles and frameworks for M&E professionals.
• Examine the potential for AI to exacerbate existing inequalities or create new harms.
• Learn about strategies for mitigating ethical risks and fostering trust in AI-driven evaluations.

Module 7: Implementing AI/ML in M&E Workflows

• Discuss practical considerations for integrating AI/ML into existing M&E cycles.
• Explore the tools and platforms available for AI/ML development (e.g., cloud platforms, open-source libraries).
• Understand the importance of interdisciplinary teams for successful AI/ML implementation.
• Examine strategies for piloting AI/ML solutions and iterating based on results.
• Learn about communicating complex AI/ML findings to non-technical stakeholders.

Module 8: Advanced Topics and Future Trends in AI for Evaluation

• Explore an introduction to unsupervised learning for pattern discovery (e.g., clustering).
• Discuss the potential of AI for automating aspects of data collection or quality assurance.
• Examine the role of AI in real-time monitoring and adaptive management.
• Learn about emerging trends in AI ethics, explainable AI (XAI), and AI governance.
• Understand the continuous learning required to stay updated with rapid advancements in AI/ML.

CERTIFICATION

• Upon successful completion of this training, participants will be issued with Macskills Training and Development Institute Certificate

TRAINING VENUE

• Training will be held at Macskills Training Centre. We also tailor make the training upon request at different locations across the world.

AIRPORT PICK UP AND ACCOMMODATION

• Airport pick up and accommodation is arranged upon request

TERMS OF PAYMENT

Payment should be made to Macskills Development Institute bank account before the start of the training and receipts sent to info@macskillsdevelopment.com