Doctor of Statistics and Data Science (DSDS)
The Doctor of Statistics and Data Science (DSDS) at Southshore University College is the institution’s premier quantitative research degree, designed to produce "Data Architects" and "Sovereign Analysts." Grounded in our TEASEvalues (Trustworthiness, Experience, Authority, Success, Expertise), the programme integrates advanced mathematical theory with the technical Expertise required to architect AI solutions and manage massive datasets. Representing the Nova Lux philosophy, this degree signifies a safe harbor for elite researchers transitioning to peak technical authority in the global data economy, backed by the prestigious award of the University of Cape Coast.
Key Information
Academic Division
School of Computing & Information Technology
Duration
3 Years
Awarding Institution
University of Cape Coast (UCC)
Accreditation
Ghana Tertiary Education Commission (GTEC)
Strategic Focus
Advanced Algorithmic Logic & Predictive Intelligence
Institutions
Teaching Institution
SouthShore University College
Awarding Institution
University of Cape Coast (UCC)
Our programme is benchmarked against International Standards for data science research to ensure your mathematical contributions carry global weight.
Original Research Mandate
60% of the programme focus is dedicated to Original Algorithmic Theory Building and Field Research. Under the supervision of the RIC (Research and Innovation Committee), candidates engage in inquiry within the African Digital Sovereignty (ADS) cluster.
Doctoral Skills Pipeline
A mandatory 100-hour track for researchers focusing on High-Impact Publishing (RJA), Advanced Machine Learning Theory, Big Data Ethics, and Data Governance (Phase I-IV).
Applied Learning Infrastructure
Candidates have 24/7 priority access to the ADS Cybersecurity & Data Lab, featuring high-performance computing (HPC) nodes and specialized environments (R-Studio, PyTorch, TensorFlow).
Integrity & Trust
Defined by institutional Reliability and Adaptability—the curriculum includes mandatory certifications in Algorithmic Transparency, Data Sovereignty Law, and Research Ethics.
Expertise Engine
PhD candidates drive output for the African Digital Sovereignty (ADS) Research Cluster, ensuring regional technical independence.
Quality & Accreditation
Fully accredited by GTEC and monitored by the DOEQA. As an affiliate of the University of Cape Coast, Southshore ensures that the DSDS thesis undergoes rigorous external examination by globally ranked statisticians. All research output must achieve ethical clearance from the RIC and aims for publication in top-quartile (Q1) journals to ensure absolute institutional Trustworthiness and Expertise. Apply via the Registrar's portal to join the source of the New Light in African Quantitative Research.
Admission Requirements
- Academic Qualification
A research-focused Master’s degree (MPhil or MSc with Thesis) in Statistics, Data Science, Computer Science, or Mathematics from a recognized institution with a minimum CGPA of 3.5.
- Research Aptitude
Submission of a comprehensive Research Proposal (minimum 3,000 words) detailing an original quantitative problem to be solved, aligned with the ADS Research Cluster.
- Equitable Admissions
STEM-focused research fellowships are available via the Widening Participation pillar for high-potential scholars from underrepresented demographics.
Curriculum Overview
Year 1
Semester 1
DSDS 701: Advanced Probability Theory
DSDS 703: Mathematical Foundation for Data Science
DSDS 705: Data Management and Big Data Technologies
DSDS 707: Machine Learning and Predictive Analytics
DSDS 709: Computational Statistics and Data Analysis (Using R, Python and MATLAB)
DDRS 701: Advanced Academic Writing
Semester 2
DSDS 702: Bayesian Methods and Applications
DSDS 704: Time Series Analysis and Forecasting
DSDS 706: Advanced Experimental Designs
DSDS 712: Advanced Statistical Inference
Year 2
Semester 1
DSDS 801: Linear Models and Applications
DSDS 803: Financial Derivatives and Risk Management
DSDS 805: Data Visualization and Interpretation
DSDS 807: Data Management and Big Data Technologies
DSDS 809: Research Methods and Project Design and Implementation
Semester 2
DSDS 708: Leadership and Management
DSDS 802: Advanced Topics in Statistics and Data Science
DSDS 804: Advanced Stochastic Processes
DSDS 806: Financial Modelling
DSDS 808: Advanced Medical Statistics
DSDS 812: Advanced Sampling Theory and Applications
Year 3
Semester 1
DSDS 900: Capstone Project
DSDS 901: Professional Practice and Ethics
DSDS 903: Statistical Consulting and Communication
DSDS 905: Entrepreneurship in Statistics and Data Science
Semester 2
Capstone Project (DSDS 900)
DSDS 911: Seminar I
DSDS 900: Capstone Project
DSDS 912: Seminar II
Career Prospects
We target a 90% Success Rate for graduates entering elite analytical or research roles. Graduates are prepared for:
University Professors & Tenure-Track Faculty
Lead Data Scientists (FAANG/Fintech Sector)
Chief Data Officers (CDO)
Senior Quantitative Policy Architects
AI/ML Research Leads
