Core Module Information
Module title: Machine Learning, AI and Ethics

SCQF level: 11:
SCQF credit value: 20.00
ECTS credit value: 10

Module code: SOE11448
Module leader: Sujoy Bhattacharya
School The Business School
Subject area group: Management
Prerequisites

There are no pre-requisites for this module to be added

Description of module content:

Artificial intelligence (AI), machine learning, and ethics are crucial to changing business models and decision-making. AI is changing businesses and the way they work. Businesses are facing new technological solutions connected with big data and advanced analytics. This module aims to introduce you to how we can use AI in different businesses connected with analytics. You will be exposed to different areas of AI and analytics, like business intelligence, concepts, drivers, and major technologies of AI, including machine learning techniques, deep learning, robotics, the internet of things, etc. You will learn about the different types and methods of machine learning and how businesses have applied machine learning successfully. In addition, you will be able to understand the role of risk and ethics within AI, and how AI, machine learning and ethics have an impact on the performance of organisations. You will understand the different types of models, what kind of business questions they help answer, or what kind of opportunities they can uncover. By the end of this module, you will have a foundational understanding of AI in business and be able to apply these technological solutions to your business environment.

Learning Outcomes for module:

Upon completion of this module you will be able to

LO1: Critically evaluate the key concepts in AI, machine learning, and business ethics.

LO2: Apply a broad range of essential professional skills, practices, and techniques in AI related to business analytics.

LO3: Apply critical analysis and methods to a business problem to find AI solutions, and identify the relationship between AI and the performance of the organisation.

LO4: Apply machine learning with R/Python to develop business solutions and present the same in an interpretable format.

Full Details of Teaching and Assessment
2025/6, Trimester 1, ONLINE,
VIEW FULL DETAILS
Occurrence: 001
Primary mode of delivery: ONLINE
Location of delivery: ONLINE
Partner:
Member of staff responsible for delivering module: Sujoy Bhattacharya
Module Organiser:


Student Activity (Notional Equivalent Study Hours (NESH))
Mode of activityLearning & Teaching ActivityNESH (Study Hours)NESH Description
Independent Learning Practical classes and workshops 12 In weekly online live academic sessions, you will apply techniques to explore how machine learning and AI can be used in various businesses. You will use analytical software in an online environment, focusing on real-world business scenarios.
Independent Learning Guided independent study 188 Independent reading: You will engage with materials on specific topics at your own pace. A variety of online resources (e.g., code samples, articles, textbooks, videos, etc.) will be provided to help you develop a deep understanding of the module content.
Total Study Hours200
Expected Total Study Hours for Module200


Assessment
Type of Assessment Weighting % LOs covered Week due Length in Hours/Words Description
Practical Skills Assessment 30 3~4 Week 10 HOURS= 10 Minutes You will complete one practical task related to applying machine learning with R/Python to develop practical skills and find answers to business problems. You will create a presentation using the results obtained from the practical task.
Essay 70 1~2~3 Week 13 , WORDS= 2000 words You will write a 2,000-word essay exploring how AI and machine learning enhance business analytics and organisational performance, while also addressing the ethical considerations and potential risks involved.
Component 1 subtotal: 30
Component 2 subtotal: 70
Module subtotal: 100
2025/6, Trimester 2, Online (fully o,
VIEW FULL DETAILS
Occurrence: 001
Primary mode of delivery: Online (fully o
Location of delivery: ONLINE
Partner:
Member of staff responsible for delivering module: Sujoy Bhattacharya
Module Organiser:


Student Activity (Notional Equivalent Study Hours (NESH))
Mode of activityLearning & Teaching ActivityNESH (Study Hours)NESH Description
Independent Learning Practical classes and workshops 12 In weekly online live academic sessions, you will apply techniques to explore how machine learning and AI can be used in various businesses. You will use analytical software in an online environment, focusing on real-world business scenarios.
Independent Learning Guided independent study 188 Independent reading: You will engage with materials on specific topics at your own pace. A variety of online resources (e.g., code samples, articles, textbooks, videos, etc.) will be provided to help you develop a deep understanding of the module content.
Total Study Hours200
Expected Total Study Hours for Module200


Assessment
Type of Assessment Weighting % LOs covered Week due Length in Hours/Words Description
Practical Skills Assessment 30 3~4 Week 10 HOURS= 10 Minutes You will complete one practical task related to applying machine learning with R/Python to develop practical skills and find answers to business problems. You will create a presentation using the results obtained from the practical task.
Essay 70 1~2~3 Week 13 , WORDS= 2000 words You will write a 2,000-word essay exploring how AI and machine learning enhance business analytics and organisational performance, while also addressing the ethical considerations and potential risks involved.
Component 1 subtotal: 30
Component 2 subtotal: 70
Module subtotal: 100

Indicative References and Reading List - URL:
Contact your module leader