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https://github.com/simonespa/apprenticeship-project-assessment

Contains the report and presentation of the work-based project I built during my L7 AI and Data Science apprenticeship.
https://github.com/simonespa/apprenticeship-project-assessment

ai apprenticeship artificial-intelligence data-science machine-learning ml presentation project report

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Contains the report and presentation of the work-based project I built during my L7 AI and Data Science apprenticeship.

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README 

        
- [Apprenticeship Project Assessment](#apprenticeship-project-assessment)

  * [Report](#report)

  * [Presentation](#presentation)

  * [Dates](#dates)

  * [References](#references)



# Apprenticeship Project Assessment



Contains the report and presentation of the work-based project I built during my L7 AI and Data Science apprenticeship at the BBC.



I built a machine learning pipeline that generates metadata item embeddings for the calculation of item similarity in the context

of Content-To-Content similarity recommendations for BBC iPlayer.



## Report



- The project report should be in the form of a paper based or electronic report.

- All work relating to the project report must be started and completed during the EPA period.

- The project report will comprise of a written report with a word count of 5,000 words plus/minus

a tolerance of 10% [4500, 5500] is allowed. Appendices, references, diagrams and tables will not be included in

this total.



Word Count:

- 5265 (title page, section headings and figure captions)

- 5183 (title page, section headings, no figure captions)

- 5163 (section headings only)



"\usepackage[none]{hyphenat}"



The format of the project report should be:



- Introduction and background

- Outline of the issue or opportunity and the business problem to be solved

- Methods used & justification

- The scope of the project (including key performance indicators)

- Data selection, collection & pre-processing

- Survey of potential alternatives

- Implementation - performance metrics

- Results

- Discussion & conclusions/recommendations

- Summary of findings

- Implications

- Caveats & limitations

- Appendices

  - Code & documentation used for the project e.g. coding developed

  - Statistical rigour - To include uncertainty/bias/error estimates as appropriate

  - Figures/tables/visualisation as appropriate to project

  - Mapping of the project report to the KSB’s mapped to this method

  - Verification by the apprentice's employer that the project report is a true reflection of

the apprentice's involvement, and the report is their own work.



## Presentation



Apprentices will prepare and deliver a presentation that appropriately covers the KSBs assigned to

this method of assessment.



The presentation will be based on the project report and will cover:

- a high-level summary of the main aspects of the project report

- context/implications/recommendations from the project report

- research undertaken

- practical application of knowledge, skills and behaviours to complete the project report

- business recommendations

- any follow-on outcomes

- actions and next steps.



The presentation with supplementary questions will last for 75 minutes (the typical length of the

presentation will be 30 minutes and the typical length of the questioning will be 45 minutes). The

independent assessor has the discretion to increase the time of the presentation by up to 10% to

allow the apprentice to answer their last question.



To deliver the presentation, the apprentice will have access to:

- flip chart

- work products

- notes

- interactive boards

- PowerPoint

- videos

- computer

- interactive demonstrations.



A minimum of 10 questions will be asked at the end of the presentation; follow-up questions are

allowed and do not form part of the question number count. Questions can be generated by the

assessor based on the presentation, however an EPAO question bank must be provided for the

assessor to use as a guide.



## Dates

- Start date: 23/09/2024

- Completion date: 04/11/2024

- Submission date: 18/11/2024



## References

- [AI Apprenticeship Standard](https://www.instituteforapprenticeships.org/media/3685/st0763_artificial-intelligence-ai-data-specialist_l7_ap-for-publication_qm.pdf)

- [Report Guidelines](https://app.edukate.ai/modules/9516/markdown_page/2421)

- [LaTeX Document Structure](https://en.wikibooks.org/wiki/LaTeX/Document_Structure)