Programme Overview


Train students to apply data science techniques for problem-solving and decision-making in real-world scenarios.


  • Build expertise in widely used analytics tools and technologies for informed decision-making.
  • Develop independent problem-solving skills using analytics and data science.
  • Understand data science applications across industries, informing strategic development decisions.
  • Learn to extract and communicate strategic business insights from data.
  • Develop the ability to build predictive models for future trend analysis and strategic business planning.
  • Gain substantial knowledge in industry portfolios related to data science and analytics.


2 Years (4 semesters)


Ghanaian Students


International Students



August 30th, 2024

Curriculum Overview

Foundations of Data Science and Big Data Analytics
Big Data Management
Introduction to Data Science
Mathematical Foundations for Data Science
Deep Learning and Neural Networks
Statistical Methods for Data Science
Special Topics in Data Science
Graduate Qualifying Seminar
Data Warehousing and Information Retrieval
Financial Decision Making for Value Creation
MSc. Thesis Phase 1
MSc. Thesis Phase II

Career Prospects

At the intersection of data science and analytics, endless career opportunities await our graduates. The MSc programme opens doors to diverse roles across industries, equipping you with the skills and knowledge to thrive in the dynamic landscape of data-driven decision-making.

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Key Pathways

  • Data Scientist: Dive into data, develop algorithms, and shape data narratives for strategic decision-making.
  • Machine Learning Engineer: Design and implement models, pioneering innovation in artificial intelligence.
  • Business Intelligence Analyst: Transform data into actionable insights, driving informed decisions for organizational success.
  • Data Engineer: Architect and maintain data flow for seamless analysis and decision-making.
  • Analytics Consultant: Provide strategic guidance, optimizing operations and achieving business objectives through data insights
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Top Industries

  • Technology and IT Services
  • Finance and Banking
  • Healthcare
  • E-commerce and Retail
  • Telecommunications
  • Manufacturing and Supply Chain
  • Energy and Utilities
  • Government and Public Sector
  • Marketing and Advertising
  • Insurance
  • Consulting Services
  • Education

Entry Requirements


Each student is required to hold a BSc from an accredited university with a minimum of second class upper or second class lower from a recognised institution or a GPA of at least 2.0 on a scale of 4 or better and CWA greater than 50%.


Preference will be given to graduates with backgrounds in Statistics, Mathematics, Computer Science and Engineering


Graduates with other backgrounds will be considered on case-by-case basis.

Our Unique Learning Pillars

  • Experiential Learning

  • Contextual Learning

  • Unified Learning

  • Extensional Learning