Summary of available resources
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-[["CTG.html", "3 Coding Training Groups 3.1 R Training 3.2 Git/GitHub Training 3.3 SQL Training 3.4 Python Training 3.5 Get involved!", " 3 Coding Training Groups Those working in Data and Analysis are recommended to take the internal training courses as they are run using the MoJ Analytical Platform and focus on topics of relevance to MoJ analysts. 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. There is also Python training you can work through yourself. 3.1 R Training The following sessions are available; click on the links to view the latest recordings and GitHub repositories respectively. The first three are particularly recommended for new starters. Introduction to using R on the Analytical Platform: Link to recording and Link to GitHub repository Introduction to R: Link to recording of part 1, Link to recording of part 2 and Link to GitHub repository R Charting: Link to recording and Link to GitHub repository Introduction to R +: Link to recording and Link to GitHub repository R Markdown: Link to recording and Link to GitHub repository Interfacing Excel with R: Link to recording and Link to GitHub repository Writing Functions in R: Link to recording and Link to GitHub repository Developing R packages: Link to recording of part 1, Link to recording of part 2 and Link to GitHub repository You can view these and other less recent recordings (for instance of the old Developing R packages and RAP ways of working: Link to recording of part 1 and Link to recording of part 2) in the R/SQL/Git Training Video Library. 3.2 Git/GitHub Training Whether seeking to use R, SQL or Python, it is recommended that all newcomers attend or work through themselves the Introduction to Git/GitHub: see the Link to GitHub repository and most recent Link to recording. You may also want to watch the Intro to Git/GitHub - Merge conflict resolution: see Link to recording. You can view this and other less recent recordings in the R/SQL/Git Training Video Library. 3.3 SQL Training All newcomers who are to use SQL should attend or work through themselves the Introduction to SQL: see Link to GitHub repository and most recent Link to recording. You can view this and other less recent recordings in the R/SQL/Git Training Video Library. 3.4 Python Training These have not yet been run as live sessions, but you can work through the material at your own pace. Introduction to Python Iterables in Python Unit Testing and GitHub Actions AWS Tooling demos Pyspark in AP Prisoid Academy - Python Training (if you have access to NOMIS) Plotly Dash Coffee and Coding Session 3.5 Get involved! One great way of learning is by teaching. If you would be interested in playing an active role, whether delivering, updating or designing training, or co-ordinating the courses, please contact Aidan Mews (R), Georgina Eaton (SQL), or Mike Ratford (Python). If you have any questions please contact Aidan Mews, Georgina Eaton or Mike Ratford. "],["404.html", "Page not found", " Page not found The page you requested cannot be found (perhaps it was moved or renamed). You may want to try searching to find the page's new location, or use the table of contents to find the page you are looking for. "]]
+[["index.html", "Analytical Platform and related tools training 1 Summary of available resources 1.1 Analytical IT Tools Strategy 1.2 Analytical Platform 1.3 Coding Mentoring Scheme 1.4 Coding Training Groups 1.5 Coffee and Coding 1.6 Bite-sized sessions 1.7 Analytical Function training 1.8 DataCamp 1.9 Microsoft Learn 1.10 Slack 1.11 Other assistance", " Analytical Platform and related tools training MoJ coding training leads (the Analytical Platform team is not responsible for the content on this page) 2025-01-29 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. You can view a recent recording of the Introduction to the Analytical Platform, which was given as part of the Analysis Directorate Induction Academy. Otherwise, to learn more about the Analytical Platform and to get up and running, go to the Analytical Platform chapter. More extensive information is provided by the Analytical Platform user guidance. 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 Data and Analysis 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 D&A 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 Those working in Data and Analysis are recommended to take the internal training courses in R, SQL, Python and Git/GitHub as they are run using the MoJ Analytical Platform. 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 Data and Analysis 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. Recent topics have included: 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 Analytical Function training There are many Analytical Function training opportunities for analysts including about specialist topics not presently covered internally. Examples useful for RAP 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: The Analytical Function Learning Curriculam The Analytical Function Training Courses 1.8 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. Read more about DataCamp and signup for a license paid for by MoJ View this March 2024 DataCamp Licence: Onboarding and Q&A session recording and associated onboarding slides Access DataCamp on your mobile View the DataCamp courses currently in development - Trello board Reach out to the DataCamp support team for any technical requests 1.9 Microsoft Learn Microsoft Learn provides free training including in Power BI and the Power Apps that you can work through yourself. 1.10 Slack Technical help can be requested via the following Data and Analysis 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 Data and Analysis Hive. 1.11 Other assistance You may also find useful: Statistical Methods Guidance on key topics for MoJ analysts with many of the signposted sources including R or Python code. links to further analytical training including in R or Python via the Free online analytical training Trello Board and R cheatsheets. There are also many useful free R and Python books on the web, for instance for Python: Automate The Boring Stuff with Python (Good for Python Fundamentals) Python Data Science Handbook "],["AP.html", "2 Analytical Platform 2.1 Introduction 2.2 Summary of key terms 2.3 Getting set up 2.4 Managing data", " 2 Analytical Platform 2.1 Introduction To gain an overview of the Analytical Platform (AP) watch this 2-3 min introductory video, although please be aware that given it’s a few years old some things have changed. In addition to the information in this chapter, you can: Attend or work through yourself the Introduction: Using R on the Analytical Platform - see the internal R training section. Read the Analytical Platform User Guidance which provides more technical details. 2.2 Summary of key terms It will help you to be familiar with the following key terms: Analytical Platform (AP): A data analysis environment providing modern tools and key datasets for MoJ analysts. AP contains training documents, resources, and access to various analytical software such as Rstudio and Jupyter. Control Panel: A place to navigate to Rstudio, Jupyter, S3 Buckets etc RStudio: Development environment for writing R code and R Shiny apps JupyterLab: Development environment for writing Python code including Python notebooks Git: Version control software that enables multiple people to make separate changes at the same time. GitHub: A web-based interface that uses Git and on which you publish and share your version-controlled code. You use Git locally (e.g. using RStudio) to track versions of your code, and then submit those changes to Github. GitHub Repositories (Repo): Broadly similar to setting up a project folder on DOM1 shared drive to save work and share with others. Files on Github Repos represent the definitive version of the project. Everyone who works on the project makes contributions from their own personal versions. Amazon S3: A web-based cloud storage platform for storing data. Access to amazon S3 buckets can be managed. Slack: Collaboration tool where you can get technical support for Analytical Platform tools such as R, Python, Git. You can share knowledge, submit admin requests and communicate quickly with other AP users. 2.3 Getting set up Follow the steps in the Getting Started section of the Analytical Platform User Guide. You need to: Set up a Slack account. Set up a GitHub account with two-factor authentication. Set up a Analytical Platform account. Set up RStudio to use R and/or JupyterLab to use Python. You can learn more about GitHub by attending or working through yourself the Introduction to Git/GitHub - see the internal Git/GitHub training section. For those that need to get set up to use Athena databases for SQL (in R or Athena) on the Analytical Platform, please follow the additional instructions in the “Training Requirements” section of the Introduction to SQL training repository. 2.4 Managing data Once you have got set up on the Analytical Platform, do read about the following data management/handling topics: How data are held on the Analytical Platform and finding the data you need. You can read about the three different data storage options (Amazon S3, Curated databases and home directories). Working with Amazon S3, data FAQ, the Data Uploader tool and interacting with Amazon S3 via the Analytical Platform. Information governance procedures to be followed. Data retention policies including when deleting data means they are permanently deleted. "],["CTG.html", "3 Coding Training Groups 3.1 R Training 3.2 Git/GitHub Training 3.3 SQL Training 3.4 Python Training 3.5 Get involved!", " 3 Coding Training Groups Those working in Data and Analysis are recommended to take the internal training courses as they are run using the MoJ Analytical Platform and focus on topics of relevance to MoJ analysts. 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. There is also Python training you can work through yourself. 3.1 R Training The following sessions are available; click on the links to view the latest recordings and GitHub repositories respectively. The first three are particularly recommended for new starters. Introduction to using R on the Analytical Platform: Link to recording and Link to GitHub repository Introduction to R: Link to recording of part 1, Link to recording of part 2 and Link to GitHub repository R Charting: Link to recording and Link to GitHub repository Introduction to R +: Link to recording and Link to GitHub repository R Markdown: Link to recording and Link to GitHub repository Interfacing Excel with R: Link to recording and Link to GitHub repository Writing Functions in R: Link to recording and Link to GitHub repository Developing R packages: Link to recording of part 1, Link to recording of part 2 and Link to GitHub repository Coding testing in R: No recording yet, Link to GitHub repository You can view these and other less recent recordings (for instance of the old Developing R packages and RAP ways of working: Link to recording of part 1 and Link to recording of part 2) in the R/SQL/Git Training Video Library. 3.2 Git/GitHub Training Whether seeking to use R, SQL or Python, it is recommended that all newcomers attend or work through themselves the Introduction to Git/GitHub: see the Link to GitHub repository and most recent Link to recording. You may also want to watch the Intro to Git/GitHub - Merge conflict resolution: see Link to recording. You can view this and other less recent recordings in the R/SQL/Git Training Video Library. 3.3 SQL Training All newcomers who are to use SQL should attend or work through themselves the Introduction to SQL: see Link to GitHub repository and most recent Link to recording. You can view this and other less recent recordings in the R/SQL/Git Training Video Library. 3.4 Python Training These have not yet been run as live sessions, but you can work through the material at your own pace. Introduction to Python Iterables in Python Unit Testing and GitHub Actions AWS Tooling demos Pyspark in AP Prisoid Academy - Python Training (if you have access to NOMIS) Plotly Dash Coffee and Coding Session 3.5 Get involved! One great way of learning is by teaching. If you would be interested in playing an active role, whether delivering, updating or designing training, or co-ordinating the courses, please contact Aidan Mews (R), Georgina Eaton or Craig Medhurst (SQL), or Mike Ratford (Python). If you have any questions please contact Aidan Mews, Georgina Eaton, Craig Medhurst or Mike Ratford. "],["CC.html", "4 Coffee and Coding 4.1 About Coffee and Coding 4.2 Recorded presentations 4.3 Code repositories 4.4 Get involved!", " 4 Coffee and Coding 4.1 About Coffee and Coding The aim of the MoJ Coffee and Coding presentations is to nurture, enable and encourage a vibrant, supportive and inclusive coding community at MoJ. Coffee & Coding provides a regular opportunity for people within MoJ who are interested in coding to: Share skills and knowledge Showcase their work and projects Provide advice and guidance to each other Network and get to know each other Code can be shared from any language — whether R, Python, SQL, or other more specialised languages. The format is generally 30–40 minutes for a presentation, followed by time for questions. The 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 these methods. 4.2 Recorded presentations Where possible, Coffee and Coding presentations are recorded to allow people to catch up on talks they may have missed and to provide a useful training resource for colleagues. These recordings are available on the Coffee and Coding Sharepoint page. We regularly update the access list, but if you cannot access the videos please contact the Coffee and Coding mailbox. 4.2.1 Some useful talks If you are new to coding in MoJ, you might find the following recorded talks useful:- Ten top tips for data presentation Package management in renv Developing an Accessible and gov.uk styled dashboard The full archive of recorded talks can be found here. 4.3 Code repositories You can find code examples to go along with past Coffee and Coding presentations in our private repo (only accessible by members of the MoJ Analytical Services GitHub organisation). 4.4 Get involved! We are always looking for new presentations. If you have an idea for a talk you would like to give, or if you want to showcase a coding project you have been working on, please contact the Coffee and Coding mailbox. If you have feedback or suggestions for the Coffee and Coding team, we would love to hear from you. You can respond to our open feedback form here. "],["404.html", "Page not found", " Page not found The page you requested cannot be found (perhaps it was moved or renamed). You may want to try searching to find the page's new location, or use the table of contents to find the page you are looking for. "]]