Who is this training for?
- Operational professionals looking to optimize their daily tasks
- Knowledge workers in all sectors
- Executives and managers looking to improve their personal productivity.
Training objectives
- Identify relevant AI tools, their key functionalities, appropriate contexts of use and associated best practices.
- Understand AI tools, interpret their results, distinguish appropriate use cases, and classify the forms of assistance offered by AI in the workplace.
- Autonomously use AI tools, apply best practices, adapt prompts according to needs and daily business tasks.
- Evaluate the quality, relevance and effectiveness of AI tools as well as diagnose problems and justify the use or not of AI according to the situation.
- Develop custom prompts tailored to your needs, build your own custom AI toolkit, and generate innovative solutions by combining different AI tools.
Summary
This practical and intensive training propels you into the concrete use of AI tools to optimize your daily work. After a targeted introduction to the tools relevant to your business, you will experience their use directly through individual and group practical exercises. The focus is on the immediate application of the knowledge acquired to your specific professional challenges, allowing for a quick and effective upskilling process. You'll leave with a personalized toolkit and the confidence to integrate AI into your work processes, significantly increasing your productivity and professional efficiency.
Course outline
Module: Introduction to LLMs and Generative AI (30 minutes)
- Definition and fundamentals of LLMs
- Basic architecture and operation
- Types of models and their characteristics
- Current capabilities and limitations
- Key concepts: tokens, embeddings, prompts
- Impact on different business sectors
Module: Security and privacy in the use of LLMs (30 minutes)
- Understanding privacy issues
- Security best practices
- Ethics of Communication with AI Module: Producing Text Using an LLM (60 minutes)
- Prompt Engineering Basics
- Content Generation Techniques
- Effective Prompt Structure and Formats
- Tone and Style Control
- Maximizing Results
- Best Practices and Pitfalls to Avoid
Module: Analyzing and Synthesizing Text Using an LLM (60 minutes)
- Textual Analysis and Information Extraction Techniques
- Key Information Extraction
- Analysis
- Pattern Identification
- Content Classification
- Comparative Analysis
- Abstract Structuring
- Adaptable Synthesis Levels
- Accuracy Validation
Module: Transforming and Formatting Text Using an LLM (30 minutes)
- Rewriting and Rephrasing Techniques
- Adapting Style and Language Level
- Formatting for Different Media
- Converting Between Formats
- Document Structuring
- Quality Checking and Improvement
Module: Translating and Localizing with AI (30 minutes)
- Machine Translation Principles
- Cultural Adaptation and Localization
- Preserving Context and Meaning
- Quality Checking
- Idiom Management
Module: Analyzing Visuals Using an LLM (30 minutes)
- Image Recognition
- Visual Content Description and Analysis
- Information Extraction
- Image Classification
- Object and Scene Detection
- Layout Analysis
Module: Analyzing Data with AI (30 minutes)
- Data Preparation and Cleaning
- Statistical Analysis Techniques
- Data Visualization
- Interpreting Results
- Identifying Trends
- Data-Driven Recommendations
Module: Search (web and otherwise) with the help of LLMs (30 minutes)
- Advanced Search Techniques Source Validation
- Limitations of LLMs Search Capabilities
Module: Learning with the help of an LLM (30 minutes)
- Personalizing learning
- Creating learning paths
- Self-assessment techniques
- Adapting content
- Tracking progress
Module: Ideation using an LLM (30 minutes)
- Idea generation techniques
- Stimulating creativity
- Exploring concepts
- Developing alternatives
- Evaluating ideas
- Refining concepts
Approach and methodology
This course favors a practical and experiential approach, combining short conceptual contributions with numerous exercises applied on generative AI tools. Learning is focused on direct experimentation, solving concrete professional tasks and adapting prompting techniques to different work contexts. The training promotes a rapid appropriation of the tools through practical workshops, exchanges and the creation of a personalized toolbox.
Recommendations
Have a rough understanding of key concepts and basic terminology in artificial intelligence.
