Artificial intelligence Course
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Objectives: Provide a practical understanding of Narrow and Generative AI, with a focus on enterprise data preparation and prompt engineering techniques for the effective use of Generative Artificial Intelligence tools, understand the fundamental principles that govern the development and implementation of the 'AI, apply the principles of Prompt Engineering and GenAI Models, plan a Narrow AI project in an enterprise context, understand the ethical risks and operational challenges of implementing AI, and evaluate the long-term scalability of enterprise projects.
Introduction and development of artificial intelligence Artificial
​Intelligence and the European Regulatory Framework [2h]:
• Illustrate the European Regulatory Framework of the AI ​​ACT, with a focus on its impact for companies;
• Provide an overview of AI through its philosophical, logical, mathematical and statistical foundations;
• Case studies and quizzes to evaluate the practical application of AI ACT.
​​Introduction to Artificial Intelligence Narrow [2h]
• Narrow AI application fields: focus on business solutions (forecasts, data analysis, automation);
• AI Narrow real-world business case studies
Preparing company data for artificial intelligence [3h]
• What is a dataset and why is it important for AI;
• Data classification and categorization:
o Types of data: structured, unstructured, semi-structured;
o Data cleaning, normalization and enrichment techniques.
• Data preparation tools: Excel, Python (pandas)
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Prompt Engineering for Generative AI [3h]
• What is Prompt Engineering:
o Definition, role and generative models such as GPT, DALL-E and others;
o Differences between AI NARROW and Generative (focus on interaction via prompts)
• Structuring an Engineering Prompt:
o Basic techniques: clarity, contextualization, specificity;
o Using constraints and commands to obtain targeted outputs; o Interactive prompt: test and optimize
• GenAI Business Applications:
o Automatic generation of texts (emails, reports);
o Data analysis with descriptions;
o Creative automation (design, brainstorming).​
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Integration of AI Narrow into business processes [3h]
• How to define business objectives for an AI project:
• Structuring a project: data identification, choice of algorithm and implementation; practical example:
o Preparation of a company dataset;
o Creation of a customer classification model;
o Evaluation and presentation of results
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Integration of Narrow and Generative AI into business processes [3h]
• Structure a complete AI project:
o Definition of company objectives;
o Preparation of datasets, choice of model (Narrow or Generative)
• Practical demonstration
o Creation of a data classification model;
o Use of GenAI for analysis and presentation of results
• Advanced Engineering Prompt:
o Designing prompts for complex use cases;
o Business case analysis: create tailored content, automated responses
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​Ethical aspects and scalability of AI [2h]
• Ethical implications of using AI: data bias, customer provacy;
• Scalability of AI projects in the company: necessary tools and infrastructure;
• Future trends: AI explainability, advanced automation
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Final test: using AI Narrow and GenAI to classify and analyze company data [1h]
• Prepare a business dataset and apply a classification model;
• Create a prompt to generate automatic data insights (e.g. summaries, suggestions, etc.);
• Present results using Prompt Engineering and data visualization techniques;
• Practical project with final report;
• Certificate of completion with digital badge
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The course is held by Valeria Lazzaroli, economist, sociologist, Risk Manager and Chief AI Officer as well as President of the National Agency for Artificial Intelligence and Founder and Chief AI Officer of a University Spin Off of the Polytechnic of Turin that develops AI algorithms to support the Risk Management and Risk Engineering function.
Today she pursues the specialization of the study of Neuroscience for the development of AI algorithms to support psychosocial risks.
She is a member of the Italy Chapter Committee of GARP, Digital Committee Member of FERMA, Scientific Committee of CONSUMERISMO, Board Expert of Valore Rischio e Sistemi, Professor of the University of Rome TRE for the Executive Program of Risk Management of FEDERMANAGER, faculty member of SOLE24 Ore Formazione.