An applied Swiss-inspired curriculum combining algorithmic rigour, systems architecture, digital trust and practical engineering capability for modern technology leaders.
The DBA in Generative AI Business Transformation at Brookfield School of Computing is engineered to provide deep competency across core computer science, systems design, and targeted domain applications. Students develop fluency in software craftsmanship, distributed architectures, algorithm optimization, and data governance.
Instruction balances rigorous theoretical foundations with practical code repositories, laboratory simulations, and ethical technology review aligned with modern international computing standards.
| Code | Module Title | Type | Discipline & Learning Outcome |
|---|---|---|---|
| DBA101 | Epistemology & Philosophy of Applied Business Research in Generative AI Business Transformation | Theory | Examine positivism, constructivism, critical realism and pragmatic epistemology in executive business research in Generative AI Business Transformation. |
| DBA102 | Strategic Leadership, Governance & Corporate Direction in Generative AI Business Transformation | Theory | Formulate executive governance models, boardroom strategic alignment and C-suite technology oversight in Generative AI Business Transformation. |
| DBA103 | Advanced Qualitative Research Design & Executive Interview Lab in Generative AI Business Transformation | Practical | Design semi-structured executive interview protocols, ethical consent mechanisms and qualitative sampling matrices in Generative AI Business Transformation. |
| DBA104 | Quantitative Methodologies & Econometrics in Generative AI Business Transformation | Theory | Derive multiple linear regression, panel data estimators, structural equation modeling (SEM) and factor analysis in Generative AI Business Transformation. |
| DBA105 | Applied Statistical Modeling & Corporate Decision Analytics in Generative AI Business Transformation | Practical | Analyze corporate survey and financial data using SPSS, R or SmartPLS to validate measurement models in Generative AI Business Transformation. |
| DBA106 | Systematic Literature Review & Conceptual Frameworks in Generative AI Business Transformation | Theory | Execute rigorous PRISMA systematic literature reviews and synthesize conceptual frameworks in Generative AI Business Transformation. |
| DBA107 | Economics of Digital Innovation & Platform Disruption in Generative AI Business Transformation | Theory | Analyze platform economics, multi-sided markets, switching costs, competitive moats and technological disruption in Generative AI Business Transformation. |
| DBA108 | Executive Data Analytics & Decision Support Systems in Generative AI Business Transformation | Practical | Build executive decision analytics models and corporate scenario simulations to inform strategic resource allocation in Generative AI Business Transformation. |
| DBA109 | Ethical Governance & Boardroom Accountability in Generative AI Business Transformation | Theory | Evaluate fiduciary responsibilities, stakeholder capitalism, corporate ESG metrics and executive research ethics in Generative AI Business Transformation. |
| Code | Module Title | Type | Discipline & Learning Outcome |
|---|---|---|---|
| DBA201 | Applied Doctoral Research Proposal Defense in Generative AI Business Transformation | Theory | Formally defend the doctoral research proposal, problem statement, methodology and contributions before faculty in Generative AI Business Transformation. |
| DBA202 | Corporate Fieldwork Pilot Study & Executive Methodology in Generative AI Business Transformation | Practical | Conduct preliminary pilot fieldwork, test survey instruments and refine qualitative interview protocols in Generative AI Business Transformation. |
| DBA203 | Strategic Risk Management, Compliance & Cyber Resilience in Generative AI Business Transformation | Theory | Evaluate enterprise risk management (COSO ERM), operational cyber resilience and corporate liability in Generative AI Business Transformation. |
| DBA204 | Survey Instrument Engineering & Psychometric Validation in Generative AI Business Transformation | Practical | Validate psychometric survey scales, Cronbach's alpha reliability, convergent validity and discriminant validity in Generative AI Business Transformation. |
| DBA205 | Organizational Change, Agility & Technology Adoption in Generative AI Business Transformation | Theory | Analyze Technology Acceptance Model (TAM/UTAUT), dynamic capabilities theory and organizational agility in Generative AI Business Transformation. |
| DBA206 | Corporate Case Study Development & Qualitative Coding in Generative AI Business Transformation | Practical | Execute thematic coding, grounded theory analysis and cross-case synthesis using NVivo / ATLAS.ti software in Generative AI Business Transformation. |
| DBA207 | Swiss & International Corporate Governance Regulations in Generative AI Business Transformation | Theory | Audit corporate compliance against Swiss Code of Best Practice for Corporate Governance and international standards in Generative AI Business Transformation. |
| DBA208 | Mid-Candidature Doctoral Review & Progress Defense in Generative AI Business Transformation | Theory | Defend mid-candidature empirical milestones and demonstrate significant primary data collection progress in Generative AI Business Transformation. |
| DBA209 | Executive Seminar: Business Impact of Research in Generative AI Business Transformation | Practical | Synthesize academic findings into actionable C-suite executive transformation playbooks and board presentations in Generative AI Business Transformation. |
| Code | Module Title | Type | Discipline & Learning Outcome |
|---|---|---|---|
| DBA301 | Applied Doctoral Field Investigation & Data Collection in Generative AI Business Transformation | Practical | Execute multi-organization primary data collection gathering quantitative survey metrics and executive interviews in Generative AI Business Transformation. |
| DBA302 | Empirical Data Triangulation & Cross-Case Synthesis in Generative AI Business Transformation | Practical | Triangulate qualitative findings with quantitative survey data and secondary financial corporate metrics in Generative AI Business Transformation. |
| DBA303 | Organizational Intervention & Transformation Analysis in Generative AI Business Transformation | Theory | Measure business impact, ROI realization, organizational productivity shifts and strategic performance metrics in Generative AI Business Transformation. |
| DBA304 | Doctoral Dissertation Drafting: Methodological Synthesis in Generative AI Business Transformation | Practical | Author dissertation chapters detailing research design, data collection rigor and analytical procedures in Generative AI Business Transformation. |
| DBA305 | Doctoral Dissertation Drafting: Strategic Implications in Generative AI Business Transformation | Theory | Synthesize theoretical implications for business scholarship and actionable strategic guidance for executives in Generative AI Business Transformation. |
| DBA306 | Peer Review Workshop & Executive Working Paper Series in Generative AI Business Transformation | Practical | Present findings at executive doctoral colloquia, collect peer reviews and prepare executive working papers in Generative AI Business Transformation. |
| DBA307 | Final Executive Dissertation Submission & Quality Review in Generative AI Business Transformation | Practical | Finalize the complete executive doctoral dissertation manuscript and pass institutional originality review in Generative AI Business Transformation. |
| DBA308 | Preparation for Doctoral Viva Voce & Oral Defense in Generative AI Business Transformation | Theory | Rehearse doctoral dissertation defense, defend methodological choices and articulate executive contributions in Generative AI Business Transformation. |
| DBA309 | Final DBA Dissertation Defense & Executive Dissemination in Generative AI Business Transformation | Practical | Successfully defend the DBA dissertation in oral viva voce examination and disseminate executive findings in Generative AI Business Transformation. |
Master’s degree in management or technology with senior executive leadership experience. Applied research concept required.
Brookfield School of Computing is an independent private education institution in formation. Academic programmes, entry requirements, fees and awards are subject to institutional review and applicable Swiss legal regulations.