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 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 […]
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: February 21, 2017 Time:9 a.m. to 5 p.m. with lunch provided Location: Donald Bren […]
Learn more about the practice of predictive modeling using Python. Description: Learn more about the practice of predictive modeling using Python. To find out about future one-day courses, please join our mailing list. This course builds upon Predictive Modeling with Python, covering best practices for building predictive models that perform well in noisy, real-world domains. […]