1. Início
  2. NOVA Information Management School
  3. Mestrado em Ciência de Dados e Métodos Analíticos Avançados
  4. Especialização em Business Analytics
  5. Casos de Negócio com a Ciência de Dados

Casos de Negócio com a Ciência de Dados

Objetivos

In business cases, data scientists work with business stakeholders to define the problem, gather data, apply appropriate data analysis methods, and communicate the results to stakeholders. These tasks require combining technical skills and an understanding of the business context.

The general objective of this course is to demonstrate the value of data-driven decision-making by solving specific problems businesses face. Students will be involved in all phases of a business case, including collecting and cleaning data, applying data analysis techniques, and presenting the results and insights in a meaningful and impactful way.

Caracterização geral

Código

200208

Créditos

7.5

Professor responsável

João Carlos Palmela Pinheiro Caldeira

Horas

Semanais - A disponibilizar brevemente

Totais - A disponibilizar brevemente

Idioma de ensino

Português. No caso de existirem alunos de Erasmus, as aulas serão leccionadas em Inglês

Pré-requisitos

Students should know Statistics, Machine Learning, Data Mining, and Python and have good computer user skills.

Bibliografia

Método de ensino

Initially, the course is based on theoretical classes (introduction to business cases and the CRISP-DM process model). After that, an example of a case study will be presented, including the demonstration of its source code, interpretation of the results, and examples of decisions to be made based on the results. After that, a case is introduced to students. Students will have two to three weeks to work on the case. During those weeks, students will have Q&A practical and theoretical classes. Then, students will have to make a presentation about the case, submit a report, and all the code developed. The process will be repeated for the four business cases under study.

The work on the case will be done in groups of 5 students each.

Applications used: Microsoft Excel, Python, Jupyter notebook, Microsoft visual code.

Método de avaliação

Due to the application-based design of the course, evaluation is continuous and based only on the projects. There is no exam in the course.

All evaluation grades are on a scale of 0-20.

  • Group projects:
    • The minimum grade is 8.0
    • Each project weights 25%

All submissions should be made via Moodle. Submissions after the deadline will be rejected.

Conteúdo

LU1. Introduction to business cases

LU2. Introduction to CRoss-Industry Standard Process for Data Mining (CRISP-DM) methodology

LU3. Communication and Data visualization

LU4. Customer segmentation case

LU5. Market basket analysis case

LU6. Demand estimate case

LU7. Customer “churn” forecast case