About this course
Step into the future of business with the MSc AI for Business. This programme is designed for ambitious professionals and graduates ready to harness the power of AI and data science to drive real-world impact. You’ll gain a rare combination of cutting-edge technical skills and strategic business insight, learning how to apply AI across marketing, sales, finance, operations and customer analytics.
Delivered through our state-of-the-art London Campus IT suite, you’ll master programming, machine learning, big data, predictive analytics, recommendation engines, customer segmentation and time series analysis. You’ll also explore the ethical, legal and sustainability challenges of AI in business, preparing you to make responsible, informed decisions that shape the future.
This course is accessible to students from a wide range of backgrounds, including those without prior computational experience. Through a research project – independently, with academic staff, or in collaboration with industry – you’ll tackle real business challenges and turn data into actionable solutions.
Choose your modules
For a full Masters degree, you’ll study 180 credits over the duration of your course. Some programmes offer a Postgraduate Diploma (PGDip) qualification or a Postgraduate Certificate (PGCert) qualification. For a PGDip, you’ll study 120 credits, and for a PGCert, you’ll study 60 credits.
Introduction to Programming
Learn the fundamentals of Python coding so you can progress onto the rest of the course.
This module is assessed with programming coursework (80% of the final mark) and an open-book computer-based examination (20% of the final mark).
Type: Compulsory
Credits: 20 credits
Fundamentals of Data Science
An introduction to the principles of data science and data analysis. Topics include:
- Data Science Context: Datafication of society and the history of data science.
- Properties and types of data (e.g., quantitative and categorical data)
- Classification and regression, introduction to Kaggle and other sources of data
- Data Management: Data collection and techniques; Cleaning of data and processing; Data errors and artefacts; missing data
- Introductory statistical approaches to data: Basic mathematical concepts; Introduction to probabilities; Descriptive statistics (e.g., centrality measures) and characterizing distributions; Correlations; Statistical hypothesis testing
- Data analysis and visualization: Types of visualization and interpretation; Identifying outliers; Regression models
- Applications: Real-world data applications, including examples
This module is assessed by a presentation and project report.
Type: Compulsory
Credits: 20 credits
Understanding Artificial Intelligence
This module offers an introduction to the fundamental concepts in Artificial Intelligence, and their application. You will study topics such as:
- Origins of AI: What is AI? From early history to the Dartmouth conference and the present day; Intelligent agents, and performance measures
- Learning, Frameworks and Packages: Introduction to supervised learning; Regression; Classification; Clustering; Artificial Neural Networks; Convolutional Neural Networks; Keras; Tensorflow
- Implications for Society: Legalities; Ethics and professional implications; Social consequences
This module is assessed by a portfolio of work, in the form of a programmed code and a corresponding technical report.
Type: Compulsory
Credits: 20 credits
AI for Marketing and Sales
Deepen your AI and programming skillset and learn about common marketing applications, including
- Chatbots and conversational AI for customer engagement
- Dynamic pricing and predictive analytics for sales forecasting
- Customer segmentation
- Recommendation engines
- Sentiment analysis and natural language processing
Type: Compulsory
Credits: 20 credits
Big Data for Business
Delve deeply into major components of using Big Data for business, including
- Introduction to Big Data (velocity, veracity, volume, value, variety)
- Exploratory and causal analytics
- Business data storage platforms
- Data mining and web scraping
- Applications of Big Data in business
- Time series analysis for business
Type: Compulsory
Credits: 20 credits
Research Project
Put what you have learnt into practice by solving a real-world problem in research or industry. Conduct a novel research project under the supervision of a member of staff.
Type: Compulsory
Credits: 60 credits
Research and Application in Artificial Intelligence and Data Science
This module teaches you the necessary research skills to undertake project-based work in AI and data science with a scientific approach. You will also explore real-world applications of AI and data science, for example in healthcare, the environment, social responsibility, and engineering.
The specific topics may vary, but the DAIM team will aim to present content that reflects current and relevant developments in this fast-evolving field.
Assessment will be a mixture of coursework, a group presentation and a computer-based exam.
Type: Core
Credits: 20 credits
