Description
This course provides a comprehensive overview of Data Science, Machine Learning, Deep Learning, and Generative AI, with a specific focus on the needs of business leaders. The goal is to offer practical tools to understand, evaluate, and lead AI and Data Science projects, from business needs to valuable solutions. The course is interactive and full of real-world examples, with attention to metrics, workflows, ROI, governance, and adoption strategies.
Main Topics
- Introduction to Data Science: definitions, fundamental rules, data-driven mindset
- Building and managing Data Science teams: roles, skills, interaction with ICT
- Success metrics and workflows for data-driven projects
- Machine Learning for Business Leaders: data-driven decision-making, model interpretability, metric evaluation, ML project lifecycle management, collaboration between business and data scientists
- Deep Learning for Business Leaders: neural networks, main architectures, solution reusability, intellectual property, business requirements, ROI evaluation and roadmap planning
- Generative AI for Business Leaders: Large Language Models (LLM), synthetic data, embeddings, agentic applications, adoption costs, governance, risks, and implementation strategies
- Effective communication of results and insights
- Data lakes, data products, reporting, and dashboards
- Data valuation and monetization
- Optimizing interactions with domain experts
- Future: Quantum Artificial Intelligence and emerging trends
Duration
2 days
Prerequisites
None.
Audience
This course is intended for business leaders, managers, professionals, and decision makers who want to understand the potential of Data Science, Machine Learning, Deep Learning, and Generative AI, and communicate effectively with technical teams. It is also suitable for Data Scientists who want to gain a strategic vision and improve communication with the business side.