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1. AI regulatory environment and policies
- AI regulatory framework in the European Union: the EU AI regulation 2024
- Legal and compliance implications for businesses
- Industry-specific regulations and their impact on AI projects
- Practical workshop: adapting internal AI policies in light of new regulations
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2. Ethics and responsability in AI
- Risk and security management in AI projects
- Bias in algorithms and how to mitigate it
- Development of internal ethical policies for the responsible use of AI
- Practical workshop: ethical assessment of AI models in business case studies
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3. AI governance and strategy in the organization
- Creating an effective AI governance framework
- Roles and responsabilities in AI management and oversight
- Culture of innovation and technological adoption in the company
- Practical workshop: design of an AI governance plan tailored to each participant's organization
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4. Measuring impact and return on investment (ROI) in AI projects
- Establishing KPIs and success metrics for AI initiatives
- Cost-benefit analysis and justification of AI investments
- Success stories in demonstrating added value to the business
- Hands-on workshop: developing an ROI model for a specific AI project
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5. Practical implementation of AI projects
- In-house development vs. outsourcing: advantages, challenges and strategic considerations
- Strategies for the effective execution of AI projects
- AI integration with existing systems and data management
- Hands-on workshop: detailed planning of the execution of a real AI project in a business scenario
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6. Specialized masterclasses
- AI and business ethics
- AI in the energy sector
- AI and business sustainability
- AI and the future of work
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7. Final project and presentations
- Development of a customized AI implementation plan for each participant's company
- Mentoring and personalized advice from AI experts
- Final project presentations and group discussion
- Detailed feedback and recommendations for the viability of the projects
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