1 Summary of available resources

1.1 Analytical IT Tools Strategy

The MoJ Analytical IT Tools Strategy describes the analytical IT tools analysts are recommended to use along with the ways of working to be followed.

1.2 Analytical Platform

The Analytical Platform is a data analysis environment, enabling the use of modern open source tools such as R and Python, and holding key datasets for MoJ analysts.

To learn more about the Analytical Platform and to get up and running, go to the Analytical Platform chapter.

1.3 Coding Mentoring Scheme

If you are new to coding (in any language or in a new coding language), or if you are new to MoJ and your role involves coding, then it is recommended that you request a coding mentor. The purpose of the scheme is to provide a better on-the-job coding learning experience and raise awareness of the preferred ways of working that will for instance enable people to get up to speed more quickly with others’ code. The scheme is also open to non-coders who need to use the Analytical Platform to advise them through the learning process, and for those needing help with developing the reproducibility of a coding product and/or pipeline or commencing a more complex coding project.

To request a coding mentor please complete the Coding Mentoring Scheme mentee form. If you would like to become a coding mentor please complete the Coding Mentoring Scheme mentor form. For more information please contact Jose Vieira or Helen Williams.

1.4 Coding Training Groups

To benefit from learning while using the MoJ Analytical Platform, MoJ analysts are recommended to take the internal training courses in R, SQL, Python and Git/GitHub. The main introductory R, SQL and Git/GitHub sessions are usually run live in February/March, June/July and October/November each year while you can also work through R, SQL, Git/GitHub and Python sessions yourself using the training material and/or recordings. To learn more about the sessions currently available and how to access the material and recordings, go to the Coding Training Groups chapter.

1.5 Coffee and Coding

The internal training (see above) is complemented by Coffee and Coding presentations. These presentations usually take the form of a demonstration of a tool or technique and/or a show and tell of work done within the department using particular coding methods. For more information go to the Coffee and Coding chapter.

1.6 Bite-sized sessions

The bite-sized sessions are short sessions (generally talks of up to 15mins followed by Q/A) on a variety of topics including specialist as well as softer skills. Past topics have included:

  • Introduction to Explainable Boosting Machines
  • Introduction to Analytical Platform and related tools training
  • What is and isn’t meant by AI?
  • Using MS Power Automate to reduce office tasks
  • An introduction to the D&A Coding Mentoring Scheme
  • Introduction to nDelius derived tables
  • New statistical methods guidance for MoJ analysts
  • How to use the Evidence Library to support your work
  • Prototyping - why, how and when?
  • Key components of RAP in MoJ coding projects
  • ChatGPT for coding - Know your Frenemy
  • Hints and tips on public speaking
  • What are faith and belief?

You can find recordings of bite-sized sessions in the bite-sized session video library. For more information including if you are interested in presenting a session or joining the bite-sized session facilitation team please contact Aidan Mews or Edward Adams.

1.7 Learning Pathways

Learning Pathways are a structured series of learning activities and resources designed to help individuals acquire specific skills and knowledge. You can access the MoJ learning pathways via the DataCamp website (see the DataCamp section for more information about DataCamp).

The Introduction to Data Science Learning Pathway has been developed to equip staff with the foundational knowledge and skills they need to make a successful start as a Data Scientist.

Who is it for?

  • Everyone with an interest in upskilling in Data Science! The Pathway was developed with new HEOs in mind but would also suit other grades seeking a refresher or those transitioning from another profession.
  • Python users. (A version for R users is under development.)

1.8 Analytical Function training

There are many Analytical Function training opportunities for analysts including about specialist topics not presently covered internally. Examples useful for Reproducible Analytical Pipeline practitioners include Best practice in programming – clean code and a more lengthy Introduction to unit testing than currently available internally. You can learn more about such opportunities via:

1.9 DataCamp

DataCamp licenses are beneficial to cover gaps in current training provision that are not currently picked up by either internal or Analytical Function training e.g. training in Power BI and more advanced or niche R, SQL, and Python skills.

1.10 Microsoft Learn

Microsoft Learn provides free training including in Power BI and the Power Apps that you can work through yourself.

1.11 Slack

Technical help can be requested via the following Data and Analysis Directorates (and other MoJ analysts) slack channels:

  • ask-operations-engineering - this provides support to those with Analytical Platform issues
  • intro_R - this provides support to those starting out in the world of R
  • R - this is for beginners and experts alike
  • sql
  • git
  • python
  • RAP

More information about Slack including how to get set up is available via the Analytical Platform User Guidance and the Hive (for Data and Analysis Directorates (and other MoJ analysts)).

1.12 Use of AI

You may find use of Copilot or ChatGPT (see the Approved AI tools MoJ Intranet article) to be very helpful in writing, editing and making your coding more reproducible. Datacamp courses (see the DataCamp section above) are available to enable you to make the most of these AI tools.

1.13 Other assistance

You may also find useful:

There are also many useful free R and Python books on the web, for instance for Python: