The Writing Effective Prompts with Prompt Engineering training helps participants professionalise their use of AI assistants by learning to better structure their requests. It explains why prompt quality directly impacts result quality, and how to turn a vague request into a clear, precise and productive instruction.
An essential training to improve the quality of AI-generated results
During this training, participants discover prompt engineering principles applied to business use. They learn to provide context, specify an objective, set an output format, correct or enrich a response and build reusable prompts for their work. This course is an excellent complement to any use of ChatGPT, Claude, Gemini, Copilot or other conversational assistants.
Module 1: Introduction to Prompt Engineering
Module 2: The Foundations of an Effective Prompt
Module 3: Structuring Your Prompts
Module 4: Adapting Prompts to Different Use Cases
Module 5: Iterating to Improve Responses
Module 6: Building Your Prompt Library
Module 7: Limitations and Best Practices
Prompt engineering is the art of formulating precise instructions to get the best possible results from generative AI tools. This skill has become essential for any professional who uses ChatGPT, Claude, Gemini or other AI assistants in their daily work.
Prompt quality directly determines response quality. A well-crafted prompt can turn a mediocre result into an immediately usable deliverable, making prompt engineering a significant productivity lever.
An effective prompt is built on several components. Context defines the scope of the task. The role assigned to the AI sets the tone and level of expertise. The instruction specifies what is expected. The format determines the shape of the result. Constraints outline what should be avoided.
Combining these elements in a structured prompt yields relevant responses from the first iteration, which dramatically reduces the time spent reformulating and correcting results.
Beyond the basics, several techniques allow users to go further. Few-shot prompting provides examples to guide the model. Chain-of-thought prompting forces step-by-step reasoning. Tree-of-thought explores multiple avenues before converging on the best solution.
Meta-prompting involves asking the AI to improve a prompt itself. Prompt chaining sequences several instructions to handle complex tasks in order. These advanced techniques open up considerable possibilities for users who master them.
Prompt engineering applies across all business domains. In writing, it produces texts with the right tone and appropriate structure. In analysis, it guides the extraction of relevant information from large documents. In project management, it facilitates the creation of action plans, risk matrices or decision summaries.
Communication professionals use prompting to generate taglines, posts or creative briefs. Developers use it to produce code, debug or document their projects. Every profession finds specific applications.
Prompt engineering evolves alongside models. The techniques that work today will be complemented by new approaches in the future. Building a deep understanding of the underlying mechanisms enables professionals to adapt quickly to technological changes.
ITTA delivers this training in Geneva and Lausanne with a resolutely practical approach. Participants work on real-world scenarios drawn from their professional reality and leave with a set of templates and methods they can apply immediately.
Switzerland holds a privileged position in the global AI landscape. Federal polytechnic schools, research centres and innovative companies across the country are actively contributing to AI technology advances. Geneva hosts several international organisations working on AI regulation and ethics, giving Swiss professionals a unique perspective on global challenges.
For businesses in French-speaking Switzerland, AI training represents a strategic investment. Proximity to European decision-making centres, a high-quality workforce and a strong local technology ecosystem provide favourable conditions for adopting these technologies. AI-trained professionals are in particularly high demand on the Swiss job market, where demand far exceeds the available talent pool.
Participants develop prompt engineering expertise that transforms the way they interact with all AI tools. They become capable of building structured, reusable prompts for the most common tasks in their work. This transferable skill applies to all language models and represents a lasting investment in professional efficiency, regardless of how tools evolve over time.
Is prompt engineering a technical skill?
No, prompt engineering requires no programming skills. It relies on the ability to formulate clear and structured instructions in natural language, a skill accessible to all professional profiles.
Does the same prompt work across all AI tools?
The core principles are transferable, but each tool has its own specifics. A prompt optimised for ChatGPT may need adjustments for Claude or Gemini. The training covers these differences to ensure maximum versatility.
How long does it take to master prompt engineering?
The foundations can be acquired in one training day. Advanced mastery develops with practice. Participants typically notice a significant improvement in their results within the first hours of training.
Will prompt engineering still be useful in the future?
Yes, even as models become more capable, the ability to formulate precise, contextualised instructions will remain a decisive advantage. Professionals who master prompting consistently achieve better results.
Can you create reusable prompts for your team?
Yes, creating standardised prompt templates is an excellent practice. It enables teams to share best practices and ensures consistent quality in the results obtained.
Monday to Friday
8:30 AM to 6:00 PM
Tel. 058 307 73 00
ITTA
Route des jeunes 35
1227 Carouge, Suisse
Monday to Friday, from 8:30 am to 06:00 pm.
