Doctor of Statistics and Data Science

Mode of study
Hybrid (Online and In-person)

Duration
3 Years

Campus
East Legon

Local Fees / year
GH₵ 20,700.00

International Fees / year
GH₵

Entry year
2024-2025

Apply here

The Doctor of Statistics and Data Science (DSDS) programme at Dominion University College is primarily a course-based postgraduate programme designed for individuals seeking to engage in high-level research and application of statistical and data science methodologies.

This advanced academic degree blends theoretical and practical elements, preparing graduates for roles in industry and government agencies.

Students are expected to generate new knowledge from existing information and typically have a strong background in mathematics, carrying out research under the supervision of faculty.

Students will:

  • Exhibit a thorough knowledge and comprehensive understanding of statistical concepts and data science methods and techniques applicable to their research.
  • Be able to develop skills in testing hypotheses, developing or appreciating new theories, planning and conducting experiments, developing practical knowledge, and acquiring proficiency in the use of computer technologies relevant to statistics.
  • Be able to create the environment for the development of skills in written work, oral presentation, and publishing the results of their research in high-profile scientific journals.
  • Demonstrate proficiency in statistical software packages appropriate for statistical data analysis.
  • Apply knowledge in advanced scientific writing and oral presentation skills during the programme.

Capstone Project Supervision

Students will carry out a capstone project, integrating and applying knowledge and skills acquired throughout the study to a real-world or complex problem. This project is undertaken under the supervision of a primary supervisor and one or more co-supervisors, with regular documented meetings.

Proposal Review

An initial seminar will be held, typically at the end of the first year, where students present their project proposals for feedback and finalization. Faculty will provide inputs to fine-tune the proposal for acceptance and approval. If a proposal is deemed shallow, the student will undertake further research and present an improved proposal for approval.

Seminars and Workshops

Regular participation in seminars, workshops, and conferences is expected to keep you current with industry trends and research developments. Two mandatory seminars are required during the study period, providing opportunities for students to discuss research, receive feedback, and engage in intellectual dialogue with faculty and peers.

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Course Objectives

Technical Competence in Computer Science

One of the key benefits of pursuing a BSc Computer Science with Management degree is the solid foundation in computer science it provides. From programming languages to algorithms, database management to software development, you will gain a comprehensive understanding of the technical aspects of computer science. These skills will enable you to design and develop software systems, analyze complex data sets, and tackle real-world computational problems

Business Acumen and Management Skills

In addition to in-depth technical knowledge, this degree program equips you with essential business acumen and management skills. You will learn about organizational behavior, strategic management, project management, and entrepreneurship. This unique combination of computer science and management will make you well-rounded and better prepared to take on leadership roles in the tech industry.

Entry Requirements

This course creates a platform for an advanced financial education and you will explore a systematized flow and management of money and assets. Banking and Finance affords you an endless career options as you acquire expert knowledge, skill-set and requisite fundamentals of the financial world.

Candidates with a Master's degree in Statistics, Actuarial Science, Mathematics, or Data Science, or any related discipline, and a CGPA of 3.0 or better, with not more than one grade C+ or lower in Research Methods, can be admitted directly into the programme.

  • Two letters of recommendation from academic or professional referees who can attest to the applicant's capabilities and potential for success in a doctoral program.
     
  • A statement of purpose (500-1,000 words) that explains the candidate's motivation for pursuing the Doctor of Statistics and Data Science program, career goals, and how the program aligns with their professional aspirations.

Candidates with a Master's degree in Statistics, Actuarial Science, Mathematics, or Data Science, or any related discipline, and a CGPA lower than 3.0 with relevant working experience may be considered.

  • Two letters of recommendation from academic or professional referees who can attest to the applicant's capabilities and potential for success in a doctoral programme.
     
  • A statement of purpose (500-1,000 words) that explains the candidate's motivation for pursuing the Doctor of Statistics and Data Science program, career goals, and how the program aligns with their professional aspirations.

Academic Modules

  • DSDS 701: Advanced Probability Theory (3 Credits)
  • DSDS 703: Mathematical Foundation for Data Science (3 Credits)
  • DSDS 705: Data Management and Big Data Technologies (3 Credits)
  • DSDS 707: Machine Learning and Predictive Analytics (3 Credits)
  • DSDS 709: Computational Statistics and Data Analysis (Using R, Python and MATLAB) (3 Credits)
  • DDRS 701: Advanced Academic Writing (3 Credits)

  • DSDS 702: Bayesian Methods and Applications (3 Credits)
  • DSDS 704: Time Series Analysis and Forecasting (3 Credits)
  • DSDS 706: Advanced Experimental Designs (3 Credits)
  • DSDS 708: Leadership and Management (3 Credits)
  • DSDS 712: Advanced Statistical Inference (3 Credits)

  • DSDS 801: Linear Models and Applications (3 Credits)
  • DSDS 803: Financial Derivatives and Risk Management (3 Credits)
  • DSDS 805: Data Visualization and Interpretation (3 Credits)
  • DSDS 807: Data Management and Big Data Technologies (3 Credits)
  • DSDS 809: Research Methods and Project Design and Implementation (3 Credits)

  • DSDS 802: Advanced Topics in Statistics and Data Science (3 Credits)
  • DSDS 804: Advanced Stochastic Processes (3 Credits)
  • DSDS 806: Financial Modelling (3 Credits)
  • DSDS 808: Advanced Medical Statistics (3 Credits)
  • DSDS 812: Advanced Sampling Theory and Applications (3 Credits)

  • DSDS 900: Capstone Project (9 Credits)
  • DSDS 901: Professional Practice and Ethics (3 Credits)
  • DSDS 903: Statistical Consulting and Communication (3 Credits)
  • DSDS 905: Entrepreneurship in Statistics and Data Science (3 Credits)
  • DSDS 911: Seminar I (2 Credits)

  • DSDS 900: Capstone Project (9 Credits)
  • DSDS 912: Seminar II (2 Credits)

Career Prospects

Graduates of the Doctor of Statistics and Data Science programme can pursue various career paths, including:

Industry:
• Data Scientist
• Statistician
• Quantitative Analyst
• Research Scientist in sectors such as finance, healthcare, technology, and consulting.

Government: Positions in statistical agencies, research institutions, and policy analysis.

Non-Profit and Private Sector: Roles in organizations focusing on data-driven decision-making and research

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Career Prospects

Graduates of the Doctor of Statistics and Data Science programme can pursue various career paths, including:

Industry:
• Data Scientist
• Statistician
• Quantitative Analyst
• Research Scientist in sectors such as finance, healthcare, technology, and consulting.

Government: Positions in statistical agencies, research institutions, and policy analysis.

Non-Profit and Private Sector: Roles in organizations focusing on data-driven decision-making and research

Why choose Doctor of Statistics and Data Science

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Tuition costs

Explore detailed information about our tuition costs and payment options. We are committed to providing a transparent and affordable education for all our students.

Domestic fees

4-month semesters

Year 1 Semester Fees
20,700.00
(12 credit minimum)

Year 2 Semester Fees
None
(12 credit minimum)

Year 3 Semester Fees
None
(12 credit minimum)

Year 4 Semester Fees
None
(12 credit minimum)

  • Total
  • $21,490

International fees

4-month semesters

Year 1 Semester Fees
(12 credit minimum)

Year 2 Semester Fees
(12 credit minimum)

Year 3 Semester Fees
(12 credit minimum)

Year 4 Semester Fees
(12 credit minimum)

  • Total
  • $21,490
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