Introduction to Business Analytics
Undergraduate course on data analysis and machine learning for business decision-making. Covers R programming fundamentals, data wrangling with the tidyverse, exploratory data analysis, clustering, classification and regression trees, and an introduction to AI tools, LLMs and prompt engineering for analytics work.
Instructor: Eduard F. Martínez-González
Institution: Universidad ICESI — Department of Economics
Course code: 06278-ECO
Term: 2026-01
Original title (in Spanish): Introducción al Business Analytics.
All weekly materials — slides (theory), in-class exercises, and datasets — are published on this site as they are released.
Course description
The course introduces students to the workflow of an analyst: how to turn raw data into evidence that supports business decisions. Students learn to program in R, manipulate and visualize data with the tidyverse, run exploratory data analysis, and apply foundational machine learning methods (clustering and decision trees) to real business datasets. The last unit covers the practical use of AI tools — large language models, agents, and prompt design — for analytics work.
Schedule
Unit 2 — Foundations of R and Programming
Week 3 — Fundamentos de R y Programación. Theory slides · Task
Unit 3 — Data Wrangling and Visualization
Week 4 — Transformación de Datos con dplyr. Theory slides · Task R script · Dataset (cafeteria.csv)
Week 5 — Visualización de Datos con ggplot2. Theory slides
Unit 4 — Data Sources, Quality and EDA
Week 6 — Fuentes, Calidad de Datos y Análisis Exploratorio. Theory slides
Unit 6 — Machine Learning Foundations
Week 9 — Fundamentos de Machine Learning. Theory slides
Unit 7 — Clustering
Week 10 — Clustering: Fundamentos y Métricas. Theory slides · Practice · Practice R script
Unit 8 — Classification Trees
Week 11 — Árboles de Clasificación. Theory slides · Practice · Dataset (credito_clasificacion.csv) · Data prep script
Unit 9 — Regression Trees
Week 12 — Árboles de Regresión. Theory slides · Practice · Dataset (notas_regresion.csv) · Data prep script
Unit 10 — AI, LLMs and Prompting
Week 15 — Special handouts on AI tools for analytics.
- Handout 1 — Inteligencia Artificial y Machine Learning
- Handout 2 — LLMs, Skills y Agentes
- Handout 3 — Prompts: cómo formular preguntas a una IA
Additional weeks and materials are added as the semester progresses.