Amplifying management skills with generative AI

Duration : 3,5 hour

© AFI Expertise inc.

This practical, intensive training course, available in 3,5 hour format, propels you into the concrete use of AI tools to amplify your management and leadership capabilities. After a targeted introduction to specialized AI tools for decision-making and organization steering, you will directly experience their use through practical exercises based on real managerial situations. The emphasis is on the immediate application of the knowledge acquired to your day-to-day challenges: data analysis, strategic decision-making, project management and process optimization. You'll leave with a personalized toolbox and the confidence to integrate AI into your management style, significantly increasing your decision-making efficiency and your organization's performance.

Audience

This training course is aimed at management professionals who want to understand and exploit artificial intelligence in their missions:

· General managers and executive committee members

· Business unit managers

· Operations managers

· Project managers

· Department heads and middle managers

· Team leaders

· Project portfolio managers

Prerequisites

Have a basic understanding of key concepts and terminology in artificial intelligence.

General Objectives

Identifying the right generative AI tools

Identify relevant AI tools, their key functionalities, appropriate contexts of use, and associated best practices.

Understanding how to use generative AI
Understand AI tools, interpret their results, distinguish appropriate use cases and classify the forms of assistance offered by AI in the workplace.

Applying good prompting practices in tools
Use AI tools independently, apply best practices, adapt prompts according to needs and daily work tasks.

Specific Objectives

At the end of this course, participants will be able to:

Remember

· Identify the main AI tools relevant to their professional context

· Name the key functionalities of each tool presented

· Recognize the situations conducive to the use of each tool

· List best practices for using AI tools

Understand

· Explain the general operation of the AI tools presented

· Interpret the results produced by AI tools

· Distinguish the appropriate use cases for each tool

· Classify the different types of assistance that AI can bring to their work

Apply

· Use the AI tools presented independently

· Demonstrate correct use of the main functionalities

· Implement good AI interaction practices

· Adapt prompts and queries to specific needs

· Perform professional tasks with AI assistance

Analyze

· Examine the quality of results produced by AI

· Diagnose common problems in the use of tools

· Differentiate between situations where AI is relevant and those where it is not

· Analyze the effectiveness of different approaches to tool use

Evaluate

· Assess the suitability of an AI tool for a given task

· Judge the quality and reliability of the outputs generated

· Measure the efficiency gains brought about by the use of AI

· Justify the choice of whether or not to use AI for specific tasks

Create

· Develop customized prompts tailored to their needs

· Build their own customized AI toolbox

· Generate innovative solutions by combining different AI tools

Contents

Module: Introduction to LLMs and Generative AI (30mins)

• LLM definition and fundamentals
• Architecture and basic operation
• Model types and their characteristics
• Current capabilities and limitations
• Key concepts: tokens, embeddings, prompts
• Impact on different business sectors

Module: Security and confidentiality when using LLMs (30mins)

• Understanding confidentiality issues
• Good security practices
• Ethical communication with AI

Module: Producing text with an LLM (60mins)

• Basic principles of prompt engineering
• Content generation techniques
• Structure and format of effective prompts
• Tone and style control
• Optimizing results
• Best practices and pitfalls to avoid

Module: Analyzing and synthesizing text with an LLM (60mins)

• Text analysis and information extraction techniques
• Key information extraction
• Structural analysis
• Pattern identification
• Content classification
• Comparative analysis
• Summary structuring
• Adaptable synthesis levels
• Accuracy validation