Executive Master in Strategic Finance and Business Leadership

Organizational Strategy Executive Master - Strategy Models

Course ID:   2610050104381LuEMT

Course Dates :          05/10/26             Course Duration :   5   Studying Day/s   Course Location: London,   UK

Language:  Bilingual


Course Category:          Executive Masters


Course Subcategories:   


Course Certified By:  LondonUni - Executive Management Training


* Executive Masters Certificate


Certification Will Be Issued From :  From London, United Kingdom


Course Fees:      £0.00

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https://www.educationandserviceshub.net/2026-training-outlines-short/2610050104381LuEMT
Executive Master in Strategic Finance and Business Leadership

Course Information

Introduction

Objectives

Who Should Attend?

Training Method

• Pre-assessment
• Live group instruction
• Use of real-world examples, case studies and exercises
• Interactive participation and discussion
• Power point presentation, LCD and flip chart
• Group activities and tests
• Each participant receives a 7” Tablet containing a copy of the presentation, slides and handouts
• Post-assessment

Program Support

This program is supported by:
* Interactive discussions
* Role-play
* Case studies and highlight the techniques available to the participants.

Daily Agenda

Daily Schedule (Monday to Friday)
- 09:00 AM – 10:30 AM Technical Session 1
- 10:30 AM – 12:00 PM Technical Session 2
- 12:00 PM – 01:00 PM Technical Session 3
- 01:00 PM – 02:00 PM Lunch Break (If Applicable)
- Participants are expected to engage in guided self-study, reading, or personal reflection on the day’s content. This contributes toward the CPD accreditation and deepens conceptual understanding.
- 02:00 PM – 04:00 PM Self-Study & Reflection

Please Note:
- All training sessions are conducted from Monday to Friday, following the standard working week observed in the United Kingdom and European Union. Saturday and Sunday are official weekends and are not counted as part of the course duration.
- Coffee and refreshments are available on a floating basis throughout the morning. Participants may help themselves at their convenience to ensure an uninterrupted learning experience Provided if applicable and subject to course delivery arrangements.
- Lunch Provided if applicable and subject to course delivery arrangements.

Course Outlines

Part 1 / 9
Day 1:
Introduction to AI in Healthcare

* Overview of AI technologies and their relevance to healthcare.
* Historical development and future trends of AI in medicine.
* Case studies of successful AI implementations in healthcare settings.
* Discussion on the strategic importance of AI for healthcare executives.​

Day 2:
Data Management and AI
* Understanding healthcare data sources and structures.
* Data quality, integration, and interoperability challenges.
* Techniques for data preprocessing and management for AI applications.
* Ensuring data privacy and compliance with regulations like GDPR.​

Day 3:
AI Applications in Clinical Decision-Making
* Exploration of AI tools for diagnostics and treatment planning.
* Integration of AI into clinical workflows and decision support systems.
* Evaluating the effectiveness and reliability of AI-driven clinical tools.
* Addressing clinician concerns and fostering trust in AI systems.​

Day 4:
Operational Efficiency through AI
* Utilizing AI for resource allocation and scheduling optimization.
* Predictive analytics for patient flow and demand forecasting.
* Automation of administrative tasks and its impact on staff productivity.
* Measuring ROI and performance improvements from AI initiatives.​

Day 5:
Ethical and Legal Considerations
* Identifying potential biases in AI algorithms and their implications.
* Frameworks for ethical AI deployment in healthcare.
* Navigating legal responsibilities and liability issues.
* Developing policies for ethical AI governance.

Part 2 / 9

Day 6:
Integrating AI into Clinical Decision Support Systems
* Analyzing the role of AI in enhancing clinical workflows and decision accuracy.
* Designing AI models to support diagnostic and treatment decisions.
* Evaluating the integration of AI with existing EHR systems.
* Reviewing case studies on AI-enabled decision support tools in hospitals and clinics.

Day 7:
AI in Population Health and Public Health Intelligence
* Leveraging AI for disease surveillance, prevention, and health forecasting.
* AI applications in managing chronic disease and behavioral health trends.
* Using machine learning for social determinants of health (SDoH) analysis.
* Real-world applications of AI in pandemic preparedness and resource allocation.

Day 8:
AI Governance, Ethics, and Regulatory Compliance
* Developing frameworks for ethical governance of AI in healthcare.
* Understanding local and global AI regulatory landscapes (e.g., GDPR, HIPAA).
* Navigating liability, accountability, and transparency in AI decision-making.
* Engaging patients, staff, and boards in responsible AI adoption.

Day 9:
Monitoring, Evaluating, and Optimizing AI Performance
* Establishing KPIs and success metrics for AI implementation in healthcare.
* Creating dashboards and analytics tools to monitor AI efficacy.
* Performing audits and continuous improvement of AI systems.
* Applying lessons learned from failed or underperforming AI initiatives.

Day 10:
Capstone Workshop – Strategic Roadmapping and Future Readiness
* Group presentations of strategic AI projects tailored to real-life healthcare challenges.
* Facilitated peer review and expert feedback sessions.
* Discussion on emerging technologies and AI trends in digital health.
* Guidance on continuing education, professional development, and certification pathways.