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 settings will be considered. The course will be taught mostly through the medium of iPython notebooks. This course is targeted primarily at graduate students who…

This course provides an introduction to fundamentals of data analysis using the R language. In this course, you will learn how to effectively use R for data analysis. This course provides a brief introduction to the fundamentals of the R language and focuses on its use for data analysis–including exploratory data analysis, linear and logistic regression, variable selection, model diagnostics, and prediction. Practical examples will be provided during the course. Date: October 20, 2017 Time: 9 a.m. to 5 p.m.…

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 settings will be considered. The course will be taught mostly through the medium of iPython notebooks. This course is targeted primarily at graduate students who…

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 their own research. Students will learn about the current state of Julia development (IDEs, documentation, where to get help), how to write efficient code by…

This course is for researchers who have never used Linux and/or a computer cluster and introduces concepts and best practices for both. Description: This course covers how to best exploit the bash shell for both interactive work and batch jobs, moving & simple manipulation of data, as well very short introductions to programming in bash, Perl, and R. This is not computer science; this is a driver's license. Date: May 16, 2017 Time: 9 a.m. to 5 p.m. with lunch…

This course builds on our Introduction to R by teaching advanced visualization and data tidying. In this course, you will cover advanced visualization including ggplot and R Shiny. In addition to visualizations, principles of tidy data and reporting will be discussed. Date: May 12, 2017 Time:9 a.m. to 5 p.m. with lunch provided Location: Donald Bren Hall, Room 4011 Instructor:  Colleen Nell, Dustin Pluta, UC Irvine Pre-requisites: 1) familiarity with basic statistical concepts, and 2) intermediate R programming knowledge. For the tutorial,…

Data collected in time and/or space exhibit unique properties that require attention to draw proper conclusions from statistical analyses. In this workshop, students are introduced to statistical concepts that are particularly useful for analyzing spatial-temporal data. Using R and Python, students will learn the basic mathematics of spatial-temporal analysis via hands-on exercises, and will put the concepts to practice analyzing real datasets from the environmental sciences. Key R packages will be used in the workshop, while Python functionality to call…

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 settings will be considered. The course will be taught mostly through the medium of iPython notebooks. This course is targeted primarily at graduate students who…