Tânia Sousa
E-mail: tania.sousa@ucp.pt
Phone: (+351) 217 227 801
Curriculum
Contacts
More Information
5th edition (in-class format): to be confirmed
Schedule: available soon
Classes: Thursdays and Fridays, from 5 p.m. to 9 p.m. and Saturdays, from 9:30 a.m. to 1:30 p.m.
Duration: 70 hours
This program will be taught in english
Miguel Godinho Matos, Program Director, details the contents of the program:
INTRODUCTION
| 1h | Program Opening | |
| 2h | Overview of Big Data, Data Science and Business Analytics | |
| 1h | Environment Setup and Configuration |
CORE ANALYTICS SKILLS
| 1h | Basic concepts of Data Mining, Machine Learning, Supervised and Unsupervised Learning | |
| 3h | Supervised Learning for Predictive Analytics in Business Applications | |
| 4h | Causality, Correlation and Unobserved Effects | |
| 4h | Introduction to R Statistical Programming | |
| 2h | Review of Statistical Analysis with Applications in R | |
| 2h | Descriptive Statistics and Visualization of Large Datasets | |
| 4h | Model Fit, Over Fit and Performance Evaluation | |
| 4h | Advanced Topics | |
| 8h | Causality in Observational Data | |
| 3h | Randomized Experiments |
SOFTWARE
| 3h | Big Data Tools Ecosystem | |
| 4h | Big Data Tools Hands-on | |
| 8h | R for Business Analytics Hands-On |
CASE STUDIES
| 6h | Case Studies | |
| 3h | Data Science Team Work | |
| 4h | Building our First Predictive Model |
Contacts
More Information
5th edition (in-class format): to be confirmed
Schedule: available soon
Classes: Thursdays and Fridays, from 5 p.m. to 9 p.m. and Saturdays, from 9:30 a.m. to 1:30 p.m.
Duration: 70 hours
This program will be taught in english
