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This is a short self-study course on hypothesis testing.
Learn more on Hypothesis testing in RThis is a short self-study course on hypothesis testing.
Learn more on Hypothesis testing in PythonIn this introductory course, we will cover the basics of Natural Language Processing (NLP) topics.
Learn more on Natural Language Processing (NLP) in RThis is a short course and aims to covers the practical application of editing and imputation in R.
Learn more on Editing and imputation in RThe course is a series of modules exploring quality issues related to predictive modelling.
Learn more on Quality assurance of predictive modellingData 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 cover the practical application of linking data in Python.
Learn more on Data linkage in PythonIn 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 PythonDealing 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.
Learn more on Dates and times in RDealing 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.
Learn more on Dates and times in Python