MSc Data Science and Analytics

Transform your future with advanced analytics and machine learning. Master the skills that drive innovation in the digital age.

Programme Overview

Aim

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

Objectives

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

Ghanaian Students
GH₵63,000
International Students
$3,500
Duration
2 Years (4 semesters)
Language
English

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 I
  • 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.

Top Industries

Key Pathways

Dive into data, develop algorithms, and shape data narratives for strategic decision-making.

Design and implement models, pioneering innovation in artificial intelligence.

Transform data into actionable insights, driving informed decisions for organizational success.

Architect and maintain data flow for seamless analysis and decision-making.

Provide strategic guidance, optimizing operations and achieving business objectives through data insights

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.

Why ACity

Our Unique Learning Pillars

Experiential Learning

Hands-on learning to prepare students to readily apply concepts, to easily integrate into the workspace.

Contextual Learning

Solving real grass-root problems to expose students to the local context and develop empathy towards the continent’s progress.

Unified
Learning

A project-based approach that combines concepts across courses to connect the dots and enable unified learning.

Extensional Learning

Arms students with a viable toolkit to help them confront real-life issues, they may not have encountered during their academic life, squarely.

Your Career Starts Here!

Take the first step.