Bridge analytics and AI through hands on programming, predictive modelling, and real world application across domains. This academically accredited Postgraduate Diploma develops job ready capability across the full analytics workflow, from data preparation and statistical inference through to machine learning, natural language processing and forecasting. You will build confidence writing code in Python, R and SQL, interpreting results, and communicating insights clearly, with a strong emphasis on practical case studies and project work. Graduates and current students work across a wide range of multinational organisations and sectors, and the programme is designed as a clear pathway to masters study.
• Build foundations in Python, R and SQL for data analysis and modelling
• Clean, transform and visualise data, then communicate insights clearly
• Apply statistical inference for evidence based decision making
• Develop and evaluate predictive models, including advanced regression methods
• Build practical machine learning capability across key techniques
• Learn forecasting with time series methods, including ARIMA family approaches
• Apply natural language processing concepts in practical contexts
• Complete an applied project and progress on a clear pathway to masters study
| Course Category | Data Analytics, Business |
| Course Type | Online Learning |
| Course Qualification | Postgraduate Diploma |
| Awarding Body | Woolf |
| Course Start Date | 23rd March 2026 |
| Course End Date | 23rd March 2027 |
| Course Duration | 12 months, part-time |
| Course Time | Live online sessions 2x per week, supported by self paced materials and access to recordings. |
| Course Fee | 2725 |
| Entry Requirements | The programme welcomes applicants from diverse backgrounds with two routes, an Academic Entry Route and a Non Academic Entry Route for candidates with relevant professional experience. Academic Entry Route: A 2.1 honours degree (or international equivalent) in a numerate or analytical discipline. Applicants with alternative qualifications demonstrating sufficient quantitative or analytical skills may also be considered. Language Proficiency: English language skills equivalent to IELTS 6.5 or higher for non native speakers |
| Career Path | Graduates progress into data roles across diverse sectors, including data analyst and data science pathways depending on prior experience. The programme also supports progression to masters study |
| Course Code | PGD DS |
Course Details Bridge analytics and AI through hands on programming, predictive modelling, and real world application across domains.
Course Details Develop advanced capability in applied analytics and AI through practical learning, real world case studies and project based assessment.
Course Details Build practical capability in AI development and deployment through hands on coding, applied projects and real world problem solving.
Course Details Develop deep technical expertise in AI and machine learning through rigorous theory and hands on practice, from concept through to real world deployment.
