Business Analytics and AI (Taught)

Why study this course with LJMU?

• No prior coding experience required

• Learn high‑demand skills: Python, Tableau, machine learning, data modelling, visualisation

• Real business case studies, simulations and employer projects

• Dedicated specialist facilities, digital tools and 24/7 support

• Develop both technical and professional skills, including communication and leadership

• Opportunities for work-based or work‑related learning

About this course
The MSc Business Analytics and Artificial Intelligence programme at Liverpool Business School prepares you to become a confident, industry-ready professional capable of using data, digital tools, and AI to shape organisational decision‑making.

This future‑focused master's degree in Business Analytics and Artificial Intelligence is designed for students from all academic backgrounds and does not require prior programming experience.

Throughout your studies, you’ll build practical skills in analytics, problem‑solving, programming, machine learning, and digital business strategy. You’ll learn how to collect, analyse, and visualise data, work effectively with stakeholders, and apply AI responsibly in real‑world contexts.

Teaching combines hands‑on workshops, interactive learning, and employer‑informed case studies to ensure you graduate ready for a career in the fast‑growing digital economy.

What You’ll Learn
Our programme is built from the ground up to gradually develop your confidence and capability. You will explore:

• How businesses use data to make strategic decisions

• Foundations of analytics, coding, and digital tools

• Ethical and responsible uses of AI

• Predictive analytics and machine learning techniques

• Problem‑solving and research skills

• Visualising and communicating insights to diverse audiences

You will also develop soft skills essential for the modern workplace, including teamwork, presentation skills, stakeholder management, and critical thinking.

To cater for the wide-ranging content of our courses and the varied learning preferences of our students, we offer a range of assessment methods on each programme.

Assessment is authentic and varied, including:

Portfolios and practical tasks
Presentations and visual dashboards
Case studies and reports
Coding exercises and data projects
Exams in selected analytical modules
A large final-year research project

Formative feedback is embedded throughout to support your development.