This is a 3.5 hour module. It will introduce you to multilateral methods. You must have completed the 'Intermediate Index Numbers' course to enrol on this course.
Learn more on Introduction to multilateral methodsThis 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 PythonThis course focuses on applying coding skills and building confidence, independence and resilience so that you can continue your learning beyond the classroom.
Learn more on Introduction to RThis course introduces the concepts, motivation, and techniques for creating a Reproducible Analytical Pipeline (RAP). It explains the benefits of RAP and gives guidance to help you overcome common problems with it.
Learn more on Introduction to Reproducible Analytical Pipelines (RAP)This course will give an overview of the benefits and main features of RMarkdown.
Learn more on Introduction to RMarkdownThis course will give you an understanding of Sparklyr, the R interface to the distributed processing tool Spark.
Learn more on Introduction to SparklyrThis course will give you an understanding of unit testing: the practice of designing, creating and executing tests for your code in both R and Python.
Learn more on Introduction to unit testing