← Introduction to Machine Learning

The Problem First

This lecture will emphasis on the importance of building ML-based systems with a purpose by focusing on the problem first. We will see the current status of ML applications, the adoption properties, and engineering mechanisms to ensure our ML projects align with the problems they are designed for.

Department: Centro de Estudios y Asesorías en Estadística (CEASE)

Institution: Universidad de Nariño

Date: May 24, 2025

Hours: 4

From: 10:00 am

To: 12:00 am

HTML slides | Notebook - Individual

Resources

Books

Haberfellner, R. and de Weck, O. and Fricke, E. and Vossner, S. (2019). Systems Engineering: Fundamentals and Applications. Springer Nature
Lawrence, N. D. (2024). The Atomic Human: Understanding Ourselves in the Age of AI. Penguin UK.

Papers and Reports
Bastidas V., Schooling J. (2025). Socio-Technical AI Design For Public Value
Kabi J., Maina C. (2021). Leveraging IoT and Machine Learning for Improved Monitoring of Water Resources - A Case Study of the Upper Ewaso Nyiro River
Lavin A. et al. (2022). Technology Readiness Levels for Machine Learning Systems
Hasterok C., Stompe J. (2022). PAISE® – Process Model for AI Systems Engineering
Hershey P. (2021). System of Systems Engineering Approach for Complex Deterministic and Nondeterministic Systems (ACDANS)
Cabrera C. et al. (2025). The Systems Engineering Approach in Times of Large Language Models

Web
The AIAAIC Repository
Data Science Africa (DSA)
Lawrence, N. D. (2025). AI that Serves Science, Citizens and Society