This course provides an introduction to the fundamentals of the R language and its applications to data analysis. In this course, you will learn how to program in R and how to effectively use R for data analysis. The course covers an introduction to data/object types in R, reading data, creating data visualizations, accessing and […]
The Data Science Initiative is sponsoring a short symposium highlighting recent advances in data science. The event will consist of talks on a variety of topics related to data science followed by a reception and graduate student poster session, including posters from the 2016 Data Science Summer Fellows. Date: October 7, 2016 Time: 3:00 - 6:30 […]
Information Session on the Insight Data Science Fellows Program Speaker: Emily Thompson, Insight Data Science, insightdatascience.com Target audience: Graduate students and Postdoctoral researchers Date: Friday, October 14 Time: 4:00 to 5:00 p.m. Location: Calit2 Auditorium, UCI (directions) RSVP Today About Emily Thompson Emily Thompson, Product Manager at Insight Data Science, will be talking about her transition from […]
This course provides an introduction to the basics of using open source software tools to analyze large scale genomics data, specifically Next Generation Sequencing data. In this course, you will learn general NGS workflow, data analysis pipeline, data formats, short read mapping and alignment software, general workflow for DNA-seq, RNA-seq and ChIP-seq. Data visualization tools […]
This workshop aims to introduce both users of scripting languages and advanced programmers to the Julia ecosystem and explore details about the Julia language which can help produce efficient and readable code. The goal of the workshop is for students to understand where Julia can be applied and be well-equipped to start using Julia in […]
Learn about the use of predictive models in Python through scikit-learn. Python is a popular language for scientific processing and machine learning. This course will introduce general modeling concepts in addition to concrete examples based on the scikit-learn library. Example usage of scikit-learn will illustrate how to fit and evaluate predictive models. Regression and classification […]
This course provides an introduction to the fundamentals of the R language and its applications to data analysis. In this course, you will learn how to program in R and how to effectively use R for data analysis. The course covers an introduction to data/object types in R, reading data, creating data visualizations, accessing and […]
This course builds on our Introduction to R by teaching advanced visualization and performance code. In this course, you will cover advanced visualization including ggplot and R Shiny. In addition to visualizations, the latter half of the course will include methods for speeding up R code. If time permits, data wrangling and version control will […]
This course provides an introduction to the fundamentals of the R language and its applications to data analysis. In this course, you will learn how to program in R and how to effectively use R for data analysis. The course covers an introduction to data/object types in R, reading data, creating data visualizations, accessing and […]
Learn about the use of predictive models in Python through scikit-learn. Python is a popular language for scientific processing and machine learning. This course will introduce general modeling concepts in addition to concrete examples based on the scikit-learn library. Example usage of scikit-learn will illustrate how to fit and evaluate predictive models. Regression and classification […]