Price: $399

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Instructors: Dr Rob Mastrodomenico and Dr Phillip Brooker, University of Bath

This course will help you build up the skills needed to perform data analysis using Python.

It will teach you to:
•  Perform tasks using elements of the core Python language and some commonly used Python packages
• Make the right decisions when approaching programmatic tasks, including dealing with and manipulating data
• Understand a data analysis problem, develop a strategy to tackle the problem, and devise a solution using Python.

Price: $399

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Instructors:  Martin John Hadley, University of Oxford and Professor Richard Traunmüller, Goethe University Frankfurt

This course will introduce to the tools and techniques needed to produce effective visualizations in R.

By the end of the course you will:
• Understand the need for interactive visualisations and reports, and the associated workflow
• Be able to produce a range of visualizations relevant to the available data
• Produce and publish a report that contains appropriate interactive visualizations to tell a story about the data.

Price: $399

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Instructor: Professor Jonathan Slapin, University of Essex

This course looks at methods for extracting quantitative information from texts for social scientific purposes.

It uses a practical, hands-on approach, so you can learn to apply these methods to your own research, and will teach you:
• The theoretical basis for quantitative text analysis
• Survey methods for systematically extracting quantitative information from texts
• How to identify texts and units of texts for analysis, and convert these texts into matrices for quantitative analysis
• How to analyse these matrices in order to generate inferences using quantitative or statistical methods.

Price: $399

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Instructor: Matthew Denny, Pennsylvania State University

This course will provide you with the foundation to tackle a wide range of practical data management tasks using the R programming language.

It will teach you:
• Basic R commands and data structures for manipulating data
• The ability to read data from multiple formats in and out of R
• Proficiency using loops, conditional statements, and functions to automate common tasks
• Familiarity with R’s package system for extending its functionality
• The skills to clean and manage multiple complex datasets, and textual data
• An understanding of basic web scraping techniques, for web pages and the Twitter API
• An overview of techniques and hardware for managing large datasets efficiently