MBA (Top-Up) in Tourism and Hospitality Management

Key Information:

Programme Summary:

This MBA (Top-Up) is designed for professionals and graduates who have already completed a Level 7 Postgraduate Diploma in Business, Management, or a related field. The program offers an intensive specialisation in Tourism and Hospitality Management, equipping learners with strategic insight, operational excellence, and leadership skills specific to global tourism and hospitality industries.

Award Titles Qualifications:

MBA in Tourism and Hospitality Management

Length of Programme:

06 Months

Exit Awards:

Master's Degree

Study Mode	Delivery Mode	Language	Credits	ECTS
Full Time / Part Time	Live (Online) Delivery	English	120	60

Modules:
Specialisation Modules in Tourism & Hospitality (30 ECTS)
- Hotel Management Fundamentals – 5 ECTS - Marketing Hotels – 5 ECTS - Event Management – 5 ECTS - Tourism Marketing – 5 ECTS - Tourism and Hospitality Operations Management – 5 ECTS - Practical Pricing & Revenue Management – 5 ECTS
Capstone Project (30 ECTS)
A comprehensive and research-driven project that allows learners to apply academic theories to a real-world challenge in tourism or hospitality. The project fosters advanced analytical, strategic, and leadership competencies required at senior executive levels.
MBA in Tourism and Hospitality Management

Learning Outcomes

Graduates of this programme will be able to:
Analyse and apply sustainable strategies in tourism and hospitality contexts.
Manage complex operational tasks in resorts and hospitality venues.
Design and implement effective visitor experience strategies.
Demonstrate key transferable skills for employment and leadership.
Apply destination and cultural tourism management techniques.
Launch and manage tourism/hospitality enterprises.
Conduct academic and industry-based research.

Entry Requirements

- A recognised Level 7 Postgraduate Diploma in Business, Management, or a related discipline
- Proficiency in English (IELTS 6.0 or equivalent)
- Relevant professional experience in hospitality or tourism (preferred but not mandatory)

Career Pathways

Graduates are equipped for senior roles such as:
- Hotel or Resort General Manager
- Director of Tourism Operations
- Global Event Manager
- Tourism Policy Advisor
- Hospitality Revenue Manager
- Travel and Leisure Consultant
- Entrepreneurship in Hospitality and Tourism

Disclaimer:

Every effort has been made to ensure the accuracy of our published course information. However, our programmes are subject to ongoing review and development. Changing circumstances may cause alteration to, or the cancellation of, courses. Changes may be necessary to comply with the requirements of accrediting bodies or revisions to subject benchmarks statements. We may also make changes to keep courses updated and contemporary, or as a result of student feedback. We reserve the right to make variations if we consider such action to be necessary or in the best interests of students.

Level 3 Diploma in Data Science

Progression routes

Level 4 Diploma in IT-related rectors
Level 4 Diploma in DS
Level 5 Extended Diploma in DS
Year 1 of Bachelor's Degree
Directly into employment in an associated profession

Qualification Overview

The aim of the Level 3 Diploma in Data Science is to provide learners with an introduction and understanding of the field of data science.
The Level 3 Diploma provides a contemporary and holistic overview of data science, artificial intelligence, and machine learning, from the birth of artificial intelligence and machine learning in the late 1950s, to the dawn of the “big data” era in the early 2000s, to the current applications of AI and machine learning and the various challenges associated with them. In addition to the standard machine learning models of linear and logistic regression, decision trees and k-means clustering, the diploma introduces learners to two new exciting and emerging areas of data science: synthetic data and graph data science.
The Diploma also introduces learners to the data analytical landscape and associated analytical tools, teaching introductory Python so that Learners can analyse, explore, and visualise data, as well as implement a number of basic data science models.
Successful completion of the Level 3 Diploma in Data Science provides learners with the opportunity to progress to further study or employment.

Mandatory Units

- The Field of Data Science
- Python for Data Science
- Creating and Interpreting Visualisations in Data Science
- Data and Descriptive Statistics in Data Science
- Fundamentals of Data Analytics
- Data Analytics with Python
- Machine Learning Methods and Models in Data Science
- The Machine Learning Process
- Linear Regression in Data Science
- Logistic Regression in Data Science
- K-means Clustering in Data Science
- Decision Trees in Data Science
- Synthetic Data for Privacy and Security in Data Science
- Graphs and Graph Data Science

Credits:

Duration: