This course is for producers of index numbers or people who want to understand how they are produced.
Learn more on Intermediate index numbersLearners will learn important components used for modelling text. This includes feature representation and language modelling.
Learn more on Intermediate NLP in PythonThis is an introductory session aimed at statistical producers to show how the Code of Practice for Statistics works in practice in the context of the UK statistical system, along with case studies to show how the code has been applied in the past.
Learn more on Introducing the Code of Practice for StatisticsThis course will develop your understanding of artificial intelligence, machine learning and Data Privacy. It will help you understand the data privacy issues present in machine learning. The course will: Introduce what artificial intelligence (AI) and machine learning (ML) are give a basic understanding of what the data privacy risks with AI and ML are […]
Learn more on Introduction to artificial intelligence, machine learning and data privacyThis short course is designed to introduce learners to Bayesian analysis and how it can be applied within both the R and Python programming languages.
Learn more on Introduction to Bayesian data analysisThis short course is designed to introduce learners to modern software development approaches.
Learn more on Introduction to Continuous IntegrationData linkage provides insight, informs policy change and helps answer society’s most important questions by increasing the utility of data. This self-study course will introduce you to the principles, theory and practice of data linkage.
Learn more on Introduction to data linkageThis course aims to introduce participants to the processes of editing and imputing in surveys.
Learn more on Introduction to editing and imputationSee also our Introduction to QGIS and Introduction to GIS in Rshort courses.
Learn more on Introduction to GIS in PythonThis course provides an introduction to working with geospatial data in R. Learning outcomes By the end of the course you will: Know how to load spatial data into R using the sf library Be familiar with using Government Statistical Service (GSS) codes to join statistics to geographies Understand how spatial objects can be manipulated using tidyverse Understand […]
Learn more on Introduction to GIS in R