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Introduction to NLP in Python

This is an Introduction to Natural Language Processing, and covers the main concepts around text cleaning, processing, exploring datasets, and becoming familiar with working with text based data in Python.

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Introducing the Code of Practice for Statistics

This 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.

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Data visualisation in R and Python

This course explains how to take the GSS guidelines and practically apply them using the programming language of R. The course will take you from first principles through to producing production ready visualisation.

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Data linkage in R

This course aims to cover the practical application of linking data in R.

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Editing and imputation in Python

This is a short course and aims to covers the practical application of editing and imputation in Python.

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Introduction to Continuous Integration

This short course is designed to introduce learners to modern software development approaches.

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Python control flow loops and functions

Loops, Control Flow and the ability to write your own functions are valuable programming tools. This short course covers and introduction to these topics and demonstrates areas for additional learning.

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Dates and times in R

Dealing with dates and times is something any data analyst will need to do at some point. This course provides an introduction on how to deal with this kind of data.

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Intermediate index numbers

This course is for producers of index numbers or people who want to understand how they are produced.

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Introduction to data linkage

Data 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.

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