The Developing with the OpenAI API: GPT, Assistants and RAG training course teaches participants how to build modern applications around OpenAI language models. It helps them move beyond simple conversational interfaces toward a development approach based on APIs, request orchestration, assistants and contextual enrichment through information retrieval.
An essential training course for developers who want to go beyond simple prompting
During this course, participants learn to query models via API, structure interactions, manage context, design assistants and understand the fundamentals of RAG to make responses more relevant and better grounded in targeted content. The training lays a solid foundation before moving on to more advanced approaches with LangChain, orchestration or multi-agent architectures.
Module 1: Understanding the OpenAI APIs and their use cases
Module 2: Structuring exchanges with a GPT model
Module 3: Building application-level assistants
Module 4: Understanding and implementing RAG fundamentals
Module 5: Development use cases
Module 6: Best practices and limitations
The OpenAI API provides programmatic access to the most powerful GPT models on the market. It enables the construction of applications that integrate text generation, document analysis, contextual conversation, code generation and multimodal processing. Mastering this API is a fundamental skill for any AI application developer.
Beyond simple calls, the OpenAI API offers advanced features such as persistent assistants, file search and function calls that enable the construction of sophisticated applications.
The OpenAI API is based on a request-response model where each call contains a set of messages and configuration parameters. Managing system, user and assistant roles, controlling temperature and limiting tokens are essential concepts for obtaining precise results and controlling costs.
Response streaming, parallel request processing and rate limit management are important technical aspects for production applications that must handle a significant volume of interactions.
The Assistants API enables the creation of persistent AI assistants that maintain conversational context, access files and use tools. This approach significantly simplifies the construction of complex conversational applications by delegating state and memory management to the OpenAI infrastructure.
Use cases include customer support assistants, document analysts, intelligent tutors and productivity assistants. The training covers the design, implementation and optimization of these assistants.
Retrieval-Augmented Generation enriches model responses with information from specific data sources. This technique is essential for building applications that respond accurately on specialized topics or proprietary data.
Implementing RAG involves indexing documents in a vector database, performing semantic search for relevant passages and injecting those passages into the model context. The training covers the different approaches and their trade-offs.
Moving from a working prototype to a production application requires particular attention to reliability, security and costs. Error handling, retry mechanisms, result caching and performance monitoring are essential components of a robust architecture.
ITTA offers this technical training in Geneva and Lausanne for developers who want to master the OpenAI API and build professional-grade AI applications.
The Swiss market for AI application development is experiencing sustained growth. Technology companies, startups, financial institutions and international organizations are actively seeking developers capable of building intelligent solutions. Skills in AI development with Python, language model APIs and frameworks like LangChain are among the most in-demand on the French-speaking Swiss job market.
The presence of AWS, Google and Azure cloud regions in Switzerland facilitates the development and deployment of AI applications that comply with local data protection requirements. Developers trained on these platforms benefit from direct access to the necessary infrastructure and active technical communities in French-speaking Switzerland. This dynamic creates an ecosystem that fosters innovation and career development in the AI field.
Developers trained on the OpenAI API are able to build sophisticated conversational applications, augmented search systems and specialized AI assistants. They master advanced patterns such as RAG and function calls that enable the creation of solutions surpassing the limitations of simple chatbots. This expertise is particularly sought after on the Swiss software development market.
What is the difference between the API and ChatGPT?
ChatGPT is a consumer-facing user interface. The API is a programmatic service that allows the same models to be integrated into custom applications, with full control over behavior and user experience.
How much does OpenAI API usage cost?
The API is billed on a pay-per-use basis according to the number of tokens processed. Costs vary depending on the model chosen. The optimization techniques covered in the training can significantly reduce expenses.
Is RAG necessary for all applications?
RAG is necessary when the application must respond accurately about specific data not included in the model’s training. For general-purpose use cases, the model’s native capabilities may be sufficient.
Is data sent to the API kept confidential?
OpenAI contractually commits to not using API customer data for training its models. Security and confidentiality conditions are detailed in the API terms of service.
Can the OpenAI API be used with languages other than Python?
Yes, the OpenAI API is accessible via REST and has official SDKs for Python, Node.js and several other languages. The training uses Python as the primary language but the concepts are transferable.
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.
