This group project is for the Bank of England as part of the Data Science and AI Career Accelerator Programme, delivered in partnership with Cambridge Institute of Continuing Education (ICE) and FourthRev.

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Project Overview

This employer project is a multidisciplinary group effort designed to apply the skills and knowledge gained throughout the programme to a real-world scenario. You will collaborate with peers to research, analyze, and respond to a business problem by analyzing provided data, conducting your own research, and making data-informed recommendations.

Key aspects of the project include:

• Solving a real-life scenario provided by the Bank of England that requires data analysis.
• Working in groups of 4-6 team members.
• Utilizing tools such as Google Colab and Python.
• Developing and presenting a data-informed plan to optimize business performance.

Required Skills & Tools

To successfully complete this project, you are expected to leverage skills in:

• Data preprocessing and analysis: Preparing and processing complex data sets, ensuring quality and consistency.
• Advanced statistical thinking: Investigating and interpreting key trends and relationships across diverse data sets using supervised and unsupervised techniques.
• Model design, validation, and optimization: Developing, testing, and deploying advanced models.
• Python for data science: Building innovative solutions to complex data problems.
• AI applications and ethical awareness: Evaluating AI potential within business contexts and addressing ethical challenges.
• Business context and decision-making: Synthesizing data science insights with organizational strategies.

Project Requirements

Your team will need to:

• Write a project plan: Outline the timeline, objectives, tasks, and milestones. This includes defining the problem statement and conducting relevant research.
• Identify model selection criteria: Justify the choice of models appropriate for the domain.
• Employ relevant metrics: Evaluate LLM performance and present comparative results.
• Explain fine-tuning process: Highlight why the chosen approach was effective in enhancing model performance.
• Verify result accuracy: Ensure the results are logical and make sense.
• Prepare data-informed recommendations: Include intended outcomes and justification for focusing on critical areas.
• Present insights: Deliver recommendations and justifications in a written report and a group presentation to the employer partner.

Employer Partner Engagement

The Bank of England will provide live virtual sessions, including:

• Initial kick-off and team briefing.
• Final presentation day.

Project Assignments

There are four assignments, with three being group-based. Details are available under the "Assignments" heading in the sidebar of your course platform.

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Assignment Summary

Assignment	Description	Due
Assignment 1: Project Scope and Plan	Prepare a project plan and roadmap for team self-management. Provide a problem statement and draft the project scope.	Week 3
Submission: PDF document Word limit (report): 1,000 words (+/- 10%)
Assignment 2: Preliminary Solution Pitch	Prepare and present your preliminary solution.	Week 5
Submission: Presentation deck (PDF) and presentation recording (MP4) Time limit (presentation): 15 minutes per group
Assignment 3: Final Report and Presentation	Submit a comprehensive report and give a live presentation summarizing the technical overview of the project.	Week 7
Submission: PDF report, code (file or link), presentation deck (PDF), and live presentation (schedule TBD) Word limit (report): 1,500 words (+/- 10%) Time limit (presentation): 15 minutes (+/- 10%) per group
Assignment 4: Individual Reflection	Prepare a written reflection on the experience of working with your group.	Week 7
Submission: PDF document Word limit (report): 500 words (+/- 10%)

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Accessing Notebook

From Colab

1. Open Colab
2. File > Open Notebook > Github
3. Select appropriate repo, branch, and notebook to open
4. EDIT SETUP CONFIGS noted with "TODO" (these are included as default in notebooks/notebook_boilerplate.ipynb)
5. On the left sidebar, go to Github Secrets and add the following: github_token, github_email, github_user. For github_token, please see the video tutorial on how to retrieve it.
6. If you've added any new packages, please add them in the notebook (if notebook-specific only) or within the requirements.txt file.
7. To Save: File > Save. Please make sure you are saving to the correct repo, branch, and path (the file path should include the filename and path to the notebook where it originally sat).

From Local

1. Clone Repo
2. Open Target Notebook
3. EDIT SETUP CONFIGS noted with "TODO" (these are included as default in notebooks/notebook_boilerplate.ipynb)
4. If you've added any new packages, please add them in the notebook (if notebook-specific only) or within the requirements.txt file.
5. To Save: File > Save. Please make sure you are saving to the correct repo, branch, and path (the file path should include the filename and path to the notebook where it originally sat).

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Plagiarism Policy

All learners must abide by the Code of Conduct concerning academic misconduct, including plagiarism. For more information, please refer to the Code of Conduct under Programme Policies from your Career Accelerator Knowledge Base and the Policies and procedures for more details on plagiarism.