5K7V0024 Level 7 AI and Machine Learning: Business Application Assignment Brief 2023/24

Assignment Task and word count

For this assignment, you need to prepare several 10 up to 12 slides and make an individual oral presentation recording, which should include the following:

- A summary of the main categories of machine learning and AI techniques 

- An exploration of their business applications, and

- Analytical details about the implementation of relevant machine learning techniques to address a business analytics case.

Unit Learning Outcomes 

• Explain what AI is, distinguishing between the main categories of machine learning, and giving examples of practical applications in each category.

• Implement a simple classification machine learning algorithm.

• Evaluate the possible benefits of potential machine learning approaches to solving a range of business problems, considering risk and ethics.

Assignment Brief

This is an individual assignment to be completed in the format of pre-recorded “oral presentation”. Students are required to prepare a number of 10 up to 12 PPT slides and make an individual oral presentation recording, to

- summarise the main categories of machine learning and AI techniques (1 to 2 slides) 

- explore their typical business applications (1 to 2 slides), and

- describe in detail the implementation of relevant machine learning techniques to address a self-selected business case study (6 to 8 slides).

In the business case study, you, as a Business Analyst, should aim to develop a data analytics solution for a chosen opportunity to use machine learning and AI techniques to support business decision making. The presentation slides should cover the following main areas:

• Define the scope and objective of the business case,

• Describe the key data sources and data elements needed for the business case,

• Describe in detail how appropriate machine learning and AI techniques can be applied to achieve the business objective,

• Discuss the possible ways in which the machine learning models can be evaluated against the business objective,

• Explain how the analytical results can be used to inform business decision making, and

• Explore any ethical and legal considerations that may be relevant when considering the implementation of the data analytics solution.