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New 鈥淎nalysis Function Learning Pathways鈥� are currently being developed to bring together analytical courses from a range of providers, supporting the Function鈥檚 aim to develop analytical capability across government and complementing your Learning Curriculum journey.

Following the suggested sequence of complementary courses will help you to see where your learning could take you and provides suggestions on follow-up courses if you are interested in developing your learning further. The pathways will help you develop a stronger holistic understanding of analytical topics and be supported in continuing your progression more so than by taking a stand-alone course.

There are a variety of pathways available, with one to suit you whether you are a coding whizz or have done no analysis before. Each pathway has an attached persona, helping you understand which pathway is the right one for you.

We鈥檒l provide more updates on this exciting launch right here on our website and also in the Analysis Function Newsletter, email the team to subscribe today at [email protected] and make sure you don鈥檛 miss a thing. In the meantime, to give you an idea of what you can expect from each pathway, why not explore these examples:

Communicating Insights

Communicating insight is extracting insights and information from data and communicating them to decision-makers in a way they鈥檒l easily understand. It is as important as researching or analysing data. This pathway will provide you with a basic understanding of risk and issues surrounding statistical disclosure, communicating quality, change and uncertainty as well as best practices of conveying your message using visual aids.

After completing the three courses in this pathway you should be able to:

• Understand the key risk of statistical disclosure while communicating鈥痽our results.
• Describe the principles and issues of communicating quality,鈥痷ncertainty, and change for effective communication.
• Understand the existing guidance to improve publications.
• Communicate the results using visual aids by following best practices.

Reproducible Analytical Pipelines (RAP)

focus on the use of open-source鈥痑nalytical tools and a variety of techniques from various fields such鈥痑s鈥痵oftware development, software engineering, analytics and鈥痗ollaboration, in order to deliver reproducible, testable and auditable鈥痑nalysis pipelines. This pathway aims to provide a high-level鈥痷nderstanding and hands on practice with open-source tools and鈥痑pproaches to develop automated high-quality reproducible research鈥痯ractices while removing any manual/semi-manual processes.

After completing the eight courses in this pathway, you should be able to:

• Demonstrate a hands-on understanding of open-source analytical鈥痶ools for developing reusable automated data pipelines.
• Use GitHub to track changes made to the code in a collaborative鈥痙evelopment鈥痚nvironment.
• Test,鈥痙ocument and package code in R and Python using鈥痳eproducible programming techniques.
• Understand the role of a continuous integration pipeline towards development, testing鈥痑nd integration automation in a collaborative鈥痚nvironment.

Deciding which pathway to start with can sometimes feel confusing as trying to gauge if a course is pitched at the right level for you to build on your existing knowledge can be tricky.

To help you decide which pathway is right for you we have developed some useful personas.

Learning personas are designed to create a realistic鈥痳epresentation of the intended learning audience which will help you identify what learning is best suited to you.

Personas are created based on a variety of information from pre and post course surveys, learning needs analysis as well as one to one feedback from course participants and information/observations from learners looking for a course.

The personas are designed to be relatable to you and will give you an idea of whether a pathway will not only be at the right level but will also help you achieve your learning goals.

Communicating Insights Persona

General background

Alex works in policy and uses data to鈥痠nform his communications to stakeholders. He uses data鈥痠nsights to put forward proposals that will increase efficiency.

Starting point

Alex鈥檚 preferred method of communications is鈥痓usiness papers, however, more recently there has been a push鈥痶o make these shorter and move towards a more visual means鈥痮f communication.

Perceived needs

Alex would like to learn more about鈥痵tatistical disclosure control as this is something he has never鈥痳eally considered in his communications and how to create an鈥痠mpactful message visually.

Special considerations

Alex works part-time due to caring鈥痳esponsibilities so would prefer online self-study courses to allow more flexibility.

Benefits of this course

This pathway will provide you with a鈥痓asic understanding of risk and issues surrounding statistical鈥痙isclosure, communicating quality, change and uncertainty as鈥痺ell as best practices of conveying your message using visual鈥痑ids.鈥�

RAP Pathway persona

General Background

Sarah is an analyst who joined the analysis team a year鈥痑go.

Starting Point

Sarah attended an introduction to R course a year鈥痑go, and鈥痟as been鈥痷sing R in her work ever since.鈥疭arah鈥痠s able to鈥痗ode, but she finds it hard to repeat and鈥痳emember parts of her analysis months鈥痩ater.鈥�

Perceived Needs

Sarah produces the same quarterly report鈥痑nd would like to automate this and make quality assurance鈥痚asier.鈥疭he would鈥痩ike her colleagues to be able to use her鈥痗ode.

Special Considerations

Sarah鈥痙oesn鈥檛鈥痟ave a lot of time to鈥痠nvest in learning and would prefer not to read鈥痩arge amounts of鈥痶ext.

Benefits of this Course

This learning journey will help鈥痯articipants gain the technical tools and familiarity with best鈥痯ractice necessary to transform their work into Reproducible鈥疉nalytical Pipelines (RAP)

To access the learning pathways, you will need a Learning Hub account. Email the team at [email protected] if you don鈥檛 already have an account.