AI Data Science and Business (992G5A)
AI Data Science and Business
Module 992G5A
Module details for 2025/26.
15 credits
FHEQ Level 7 (Masters)
Module Outline
In this module, apprentices will explore the roles and impact of AI, data science and data engineering in industry and society. They will understand the business needs and the needs of the customer. Apprentices will explore how data products can be delivered to engage the customer, organise information or solve a business problem using a range of methodologies, including iterative and incremental development and project management approaches. As well as the relationship between mathematical principles and core techniques in AI and data science within the organisational context and the scientific method and its application in research and business contexts, including experiment design and hypothesis testing.
As part of this learning, apprentices will interpret organisational policies, standards and guidelines in relation to AI and data, explore the current or future legal, ethical, professional and regulatory frameworks which affect the development, launch and ongoing delivery and iteration of data products and services. Apprentices will consider the associated regulatory, legal, ethical and governance issues when evaluating choices at each stage of the data process.
During the module, apprentices will explore how their own role fits with, and supports, organisational strategy and objectives through reflection on the on-the-job role. This includes the wider social context of AI, data science and related technologies, to assess business impact of current ethical issues such as workplace automation and misuse of data. The apprentice will identify the compromises and trade-offs which must be made when translating theory into practice in the workplace as well as how to identify current industry trends across AI and data science and how to apply these. Through undertaking independent, impartial decision-making respecting the opinions and views of others in complex, unpredictable and changing circumstances.
The apprentice will reflect on how AI and data science techniques support and enhance the work of other members of the team. This means coordinating, negotiating with and managing expectations of diverse stakeholders suppliers with conflicting priorities, interests and timescales.
Apprentices will demonstrate how to communicate concepts and present in a manner appropriate to diverse audiences, adapting communication techniques accordingly and the need for accessibility for all users and diversity of user needs. They will disseminate AI and data science practices across departments and in industry, promoting professional development and use of best practice
Module learning outcomes
Systematically understand and critique the basics of the national law on data protection and freedom of information.
Systematically understand the wider ethical context related to data science when data are relative to human or living beings.
Systematically and creatively deal with complex issues of the wider socio-economic context of data science related to business needs.
Demonstrate critical awareness of current problems through write a concise essay on wider aspects of data science, AI in specific business contexts.
| Type | Timing | Weighting |
|---|---|---|
| Coursework | 100.00% | |
| Coursework components. Weighted as shown below. | ||
| Essay | A3 Week 1 | 100.00% |
Timing
Submission deadlines may vary for different types of assignment/groups of students.
Weighting
Coursework components (if listed) total 100% of the overall coursework weighting value.
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