Students who want to develop skills in managing scientific data using the statistical software R and learn a basic understanding of data science.
Introduction: What is Data Science?
Statistical Inference
Exploratory Data Analysis and the Data Science Process
Three Basic Machine Learning Algorithms
One More Machine Learning Algorithm and Usage in Applications
Feature Generation and Feature Selection (Extracting Meaning From Data)
Recommendation Systems: Building a User-Facing Data Product
Mining Social-Network Graphs
Data Science and Ethical Issues
Data Science is the study of the generalizable extraction of knowledge from data. Being a data scientist requires an integrated skill set spanning mathematics, statistics, machine learning, databases and other branches of computer science along with a good understanding of the craft of problem formulation to engineer effective solutions.
This summer school will introduce students to this rapidly growing field and equip them with some of its basic principles and tools as well as its general mindset. Students will learn concepts, techniques and tools they need to deal with various facets of data science practice, including data collection and integration, exploratory data analysis, predictive modeling, descriptive modeling, data product creation, evaluation, and effective communication.
Registration opens on February 1, 2025!
Students who participate in a Badge are kindly asked to register via: