This 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 RThis course will give you an understanding of the git version control system, along with experience working both locally and in collaboration.
Learn more on Introduction to GitIn this course you will learn about a range of machine learning topic areas. You will also learn how to perform the modelling operations using the Python programming language and the package 'scikit-learn'.
Learn more on Introduction to machine learning in PythonThis 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.
Learn more on Introduction to NLP in PythonThis course is designed to introduce learners to object orientated programming in Python.
Learn more on Introduction to object orientated programming in PythonThis course will provide learners with the skills they need to act as an intelligent customer for evaluation.
Learn more on Introduction to policy evaluationThis course will give you an understanding of Pyspark, the Python interface to the distributed processing tool Spark.
Learn more on Introduction to PysparkThis course focuses on applying coding skills in Python and building confidence, independence and resilience so that you can continue your learning beyond the classroom.
Learn more on Introduction to Python