Costa Rica National High Technology Center
August 18 -22, 2025
The Costa Rica National Research and Education Network: RedCONARE and the Costa Rica National High Technology Center (CeNAT) are proud to host the next Costa Rica Big Data School 2025.
This school will be hands-on style. Working with live coding in conjunction with lectures discussing the art of scientific programming, algorithm design, and data science. Instructors will guide attendees through the Computational Research cycle. Students will participate in a coding challenge to develop a computational model writing code in Python, generate data to verify and validate information, applying machine learning techniques to the data set and find interesting outcomes and revalidate the data.
We hope you enjoy what we have prepared, and take full advantage of this exciting event.
M.Sc. Carlos Gamboa Venegas
RedCONARE Scientific Coordinator
Costa Rica Big Data School Chair
Instructors
Susan Lindsey
Technical Information Coordinator
Texas Advanced Computing Center
Biography: Susan is TACC’s Technical Information Coordinator. As such, she is responsible for gathering and presenting timely, consistent and accurate technical information to the supercomputing user community. She will also be evaluating and implementing emerging technologies related to the dissemination and presentation of technical content.
Susan comes to TACC after eight years at the San Diego Supercomputer Center where she researched and programmed on a variety of computational biology projects.
Charlie Dey. B.A.
Director, Training And Professional Development
User Services Texas Advanced Computing Center
Biography: Charlie is the Director of Training and Professional Development with the User Services group at TACC with a background in web development and scientific computing. Charlie’s responsibilities at TACC include organizing, developing content, and building curriculums for TACC’s academic course selection taught in conjunction with several departments at the University of Texas at Austin, as well as for TACC’s professional development and educational training. Prior to joining TACC, he worked as a Senior Application Developer for the Carle Foundation, and as a computer science instructor at Parkland College in Champaign, IL. He was also a member of a specialized application development team at the University of Illinois and has also been a contracted research consultant for NASA Ames Research Center, studying computational immunology and bioinformatics. Charlie holds a Bachelor’s Degree concentrating in Computer Science and Biology from Eastern Illinois University, and certifications in 3D programing and visualization.
Program
This 4–5 day hands-on AI Workshop is designed to introduce participants to foundational AI techniques using Python and guide them through the full data analysis pipeline—from exploration to forecasting. The workshop begins with a shared dataset and step-by-step demonstrations of how to apply AI methods such as classification, clustering, regression, and time series forecasting to gain insights. Participants will then use these techniques to model and project future data trends. In the final day and a half, attendees will work in teams to select their own datasets, analyze them using the techniques they’ve learned, and present their findings, including a discussion of the AI methods used and the insights gained.
| Date & Time | Monday 18 | Tuesday 19 | Wednesday 20 | Thursday 21 | Friday 22 |
|---|---|---|---|---|---|
| Foundations and Setup | AI Techniques – Classification and Clustering | AI Techniques – Regression and Forecasting | Team Projects – Dataset Exploration and Analysis | Team Projects – Final Presentation | |
| 08:30 – 10:30 | Introduction to the workshop goals and structure Setting up the Python environment | Introduction to supervised vs. unsupervised learning | Introduction to linear and non-linear regression models | Form teams and identify datasets of interest (sources: Kaggle, UCI, etc.) | Finalize analysis and visualizations |
| 10:30 – 11:00 | Break | ||||
| 11:00 – 13:00 | Introduction to the shared dataset Data cleaning and exploratory data analysis (EDA) techniques | Applying classification algorithms (e.g., Decision Trees, KNN, Logistic Regression) | Time series analysis and forecasting (e.g., ARIMA, LSTM basics) | Perform data cleaning and EDA Select and apply appropriate AI techniques | Teams present findings, methodology, and insights |
| 13:00 – 14:00 | Lunch | ||||
| 14:00 – 16:00 | Basic visualizations and feature engineering | Hands-on with clustering (e.g., K-Means, DBSCAN) Discussion on model evaluation and performance metrics | Applying models to project future trends in the dataset Error analysis and model tuning | Begin working on analysis and presentation prep | Group discussion on techniques used and key takeaways Wrap-up and feedback session |
| 16:00 – 16:20 | End of day | ||||
Registry
Tuition fee
Participation is free. There are no tuition costs associated with participating in this school for those affiliated to CONARE institutions.
Maximum quota
The maximum quota is 50 participants.
Inscription
The following form has to be fully filled before July 31th.
Important dates:
- The closing of the application process to the School: July 31th.
- Notification of acceptance/rejection in the participation of the School: August 6th.
Requirements
Being a student, teacher or researcher of any public university (UCR, TEC, UNA, UNED, UTN), from CONARE or any of its ascribed programs: CeNAT, PEN and SINAES.
Also, we are admitting functionaries of the Ministries and Public Entities of the Government of Costa Rica. (Limited spaces)
Have an intermediate English knowledge (reading and hearing). All of the presentations and exercises are going to be in this language.
Having basic programming skills with Python and basic Linux handling.
Organizers
The Advanced Computing Laboratory (CNCA) at Costa Rica High Technology Center (CeNAT) is a multidisciplinary space where scientific discovery is accelerated through an advanced computing infrastructure. This infrastructure includes not only specialized and updated hardware, but also a set of efficient applications and well-trained staff in order to take advantage of all the technology. This allows CNCA to work in the main dimensions of research, project development, training, and services provision.
