Costa Rica Big Data School 2024

Costa Rica National High Technology Center

August 05 to 09

The National Research and Education Network of Costa Rica (RedCONARE) and the Advanced Computing Laboratory (CNCA) of the National High Technology Center of Costa Rica (CeNAT) are proud to host the eighth edition of the Costa Rica Big Data School.

The main objective of this event is to train students, teachers and researchers from the Costa Rican public education system in R and Python. The training will cover basic topics of data manipulation, exploratory data analysis and the fundamentals of machine learning.

We hope you enjoy the program that we have meticulously prepared over the past few months and that you make the most of this valuable opportunity.

 

MSc. Carlos Gamboa Venegas
Scientific Coordinator RedCONARE
Organizer Costa Rica Big Data School

Instructors

Raphael Cóbe

Raphael Mendes de Oliveira Cobe holds a Ph.D. in Computer Science from the Institute of Mathematics and Statistics at the University of São Paulo, with an emphasis on Artificial Intelligence. With over 15 years of experience in software development, he has been working as a Research Computing Specialist at the São Paulo State University's Center for Scientific Computing since 2015. His work focuses on projects related to Machine Learning, High-Performance Computing, and Big Data, as well as building and maintaining Research Computing infrastructures. He is also a member of the São Paulo Research and Analysis Center (SPRACE), which is part of the CMS LHC collaboration. More recently, he co-founded the Advanced Institute for Artificial Intelligence (AI2), a non-profit organization dedicated to bridging the gap between academia and the private sector by fostering projects with positive socio-economic impact.

Obed Ramírez Sánchez

Engineer in Agroecology, he has a Master's degree in Applied Computing and a PhD in Science from the Center for Research and Advanced Studies of the National Polytechnic Institute (CINVESTAV), Irapuato Unit, Mexico. His areas of expertise are Bioinformatics and Machine Learning. Since 2022 he has been working in private industry as head of the Data Science area at Solena Ag. (https://solena.ag/home/us). His focus is the development of personalized agriculture through the intersection of genomics, metagenomics, molecular biology and Machine Learning. His flagship project “Prometheus” is based on the use of different ML algorithms to identify and develop low-cost biomarkers to monitor soil health in terms of productivity, sustainability and pathogen control.

Agenda

  • Module 1: Introductory topics on data: nature of variables, importance and applications of data analysis, basic software structures, dataframe management.
  • Module 2: Data analysis and exploration techniques: data cleaning, replacement of missing values, exploration of extreme values, identification of patterns and correlations, among others.
  • Module 3: Introduction to statistical and machine learning models: model concept, supervised analysis, unsupervised analysis, statistical and machine learning models on regression and classification, among others.
TimeMondayTuesdayWednesdayThursdayFriday
8:30 am - 10:30 amPython Module 1R Module 2R Module 4Python Module 5R Module 6
10:30 am - 11:00 amDescanso
11:00 am - 1:00 pmMódulo 2 de PythonPython Module 3R Module 5Python Module 6Challenge
1:00 pm - 2:00 pmAlmuerzo
2:00 pm - 4:00 pmR Module 1Python Module 3Python Module 4SCALAC Conference: Convergence of HPC, AI and Big DataChallenge

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.

Important dates

  • School application deadline: July 21, 2024
  • Notification of acceptance/refusal to participate in the School: July 26, 2024

Requirements

To be a student, professor, or researcher at any public university (UCR, TEC, UNA, UNED, UTN), from CONARE or any of its ascribed programs: CeNAT, PEN and SINAES.

Have an intermediate English level (reading and listening). Some presentations and exercises may be in English.

Having basic programming skills (knowledge in R and Python are desired) and basic Linux handling.

Organizers

RedCONARE is the Costa Rica National Research and Education Network (NREN). It provides technical infrastructure and communication services like eduroam, Mconf, LA Referencia, and the Colaboratorio, among others. The NRENs or Advanced Networks are common spaces that the universities research community has among the world to enhance their knowledge and contributions to humanity. In Costa Rica, RedCONARE has been positioning as a research space and join collaboration among its members.

The Advanced Computing Laboratory (CNCA) 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 a well-trained staff in order to take advantage all of this technology. This allows the CNCA to work in the main dimensions of research project development, training and service provision.