Python Trainings

Python: the most versatile language on the IT market

Python has established itself as a widely used tool language for data science, machine learning, artificial intelligence, automation and infrastructure scripting. Its readable syntax, library ecosystem (NumPy, pandas, scikit-learn, TensorFlow, PyTorch, FastAPI, Django, Flask) and very large community make it the first choice for data, AI and DevOps profiles. It is also increasingly present in backend development, IT automation and the construction of AI agents leveraging Anthropic Claude, OpenAI, Google Gemini or Azure OpenAI APIs.

In French-speaking Switzerland, Geneva private banks, international organisations, pharmaceutical companies, scale-ups, IT service companies, university hospitals and cantonal administrations use Python for data analysis, machine learning model construction, infrastructure automation, API and AI agent development. ITTA offers a Python catalogue covering the language fundamentals, its application to AI development and data science, its practice in automation and its integration with the main frameworks on the market. Our training is delivered by Python developers active on data, AI and automation projects for Swiss and international clients.

Following a recognised Python training opens access to highly demanded roles: backend developer, data analyst, data scientist, machine learning engineer, AI engineer, DevOps engineer, automation engineer, API developer. Python systematically appears among the most demanded languages in data, AI and DevOps in French-speaking Switzerland, complementing SQL and the main cloud frameworks.

Whether you are a developer ramping up on Python, a business analyst seeking to automate processing, a data analyst moving to data science, a DevOps engineer building orchestration scripts or an AI profile developing with LLMs, our Python training in Geneva and Lausanne covers the full spectrum, from fundamentals to AI application and data pipeline development.

The ITTA Python catalogue

Python Fundamentals and good practices

Python – Fundamentals is the natural entry for any profile discovering the language. The programme covers syntax, data structures (lists, dictionaries, tuples, sets), functions, modules and packages, object-oriented programming, exception handling, file reading and writing, use of pip and virtual environments (venv, conda), as well as good practices for project structuring and testing. It is the indispensable foundation before approaching data science, AI or web development.

Python for AI application development

Developing AI Applications with Python covers the construction of modern AI applications in Python: LLM API integration (Anthropic Claude, OpenAI GPT, Mistral, Gemini), prompt engineering patterns, RAG (Retrieval Augmented Generation) with vector bases, AI agent construction, tools and function calling management, multi-model orchestration, observability and costs. This course targets developers and data engineers industrialising generative AI in their applications.

Python for data science and machine learning

From Data to Decision with Data Science and AI covers the complete data pipeline in Python: exploration and cleaning with pandas, visualisation with matplotlib and seaborn, supervised and unsupervised modelling with scikit-learn, deep learning introduction, model deployment. Understanding and Applying Machine Learning in Business deepens model productionisation, ML Ops, data quality and business use cases.

Python for DevOps, scripting and web frameworks

Python is heavily used in infrastructure automation and scripting (Ansible relies extensively on Python, cloud SDKs for Azure, AWS, GCP are available in Python, Cisco DevNet tools and the Kubernetes ecosystem integrate Python). On the web framework side, Django and Flask remain the references for building APIs and backend applications. Our catalogue covers these uses in complement to fundamentals, consistent with the needs of data, AI and DevOps profiles.

Python and the publisher ecosystem at ITTA

Python fits into a broader development ecosystem. The programming languages sub-domain regroups our Python, Java, C# and JavaScript training. The data science sub-domain covers the Python data ecosystem (pandas, scikit-learn, models). The DevOps and development sub-domain covers automation and industrialisation, where Python serves as a transversal scripting tool. ITTA Artificial Intelligence regroups our AI catalogue, strongly relying on Python for agent and RAG pipeline development. Anthropic and OpenAI complement Python on the LLM API side.

Python trends in 2026

Python continues to progress in 2026 on all fronts. Python 3.13 brings notable performance improvements and an experimental no-GIL mode. The data ecosystem is consolidated around pandas 2, Polars as high-performance alternative, and DuckDB for embedded analytics. On the AI side, LangChain, LlamaIndex, Haystack frameworks and native Anthropic and OpenAI SDKs dominate LLM orchestration. FastAPI imposes itself as a modern API framework complementing Django and Flask. Packaging and environment tools (uv, Poetry, Hatch) modernise project practices. Our pedagogical content regularly integrates these evolutions to remain aligned with current practices.

Python training in Geneva, Lausanne and online

All our Python courses are available on-site in our Geneva and Lausanne centres, as well as in interactive virtual classroom with an experienced Python developer live. Our sessions are organised in 5-week cycles. Each session includes hands-on labs on Jupyter and VS Code, code to write from the first hours, real datasets to manipulate, end-to-end projects (data pipeline, AI application, automation script). Customised corporate training is also possible at your premises, in Geneva, Lausanne, Vaud and across French-speaking Switzerland, with a programme adapted to your internal stack (cloud, data warehouse, AI frameworks) and priority business cases.

Why train on Python at ITTA

ITTA offers a Python catalogue regrouping the language fundamentals, its application to AI development, data science and machine learning, and its use in automation. Our Python trainers are developers and data scientists active on data, AI and DevOps projects for Swiss and international clients, covering the full spectrum (web, API, data, ML, generative AI). Our pedagogical team supports you in choosing the right path, identifying complementary modules (LLM, data science, ML, DevOps) and identifying funding solutions adapted to your professional situation.

Our pedagogical approach favours learning by doing, with Python code to write from the first hours, Jupyter notebooks to manipulate, real datasets to explore, ML models to train and AI prototypes to build (RAG, Claude agents, OpenAI agents). Each session combines training time, applied exercises and exchanges with the trainer, allowing each participant to progress at their own pace and leave with skills directly usable in their professional context.

Our training is aimed at varied audiences: developers ramping up, data analysts moving to data science, DevOps engineers building automation scripts, AI profiles developing with LLMs, business analysts seeking to automate processing, data teams in internal training. Our pedagogical team adapts the content to the participants’ context.

Featured courses in this catalogue

Here is a selection of reference training courses in this catalogue, accessible directly:

• Python – Fundamentals
• Developing AI Applications with Python
• From Data to Decision with Data Science and AI
• Understanding and Applying Machine Learning in Business

FAQ

Which Python course to choose to start?

Python Fundamentals is the natural entry for any profile discovering the language. It is the indispensable foundation before approaching data science, AI or web development. Profiles already comfortable with Python wishing to specialise in data or AI can start directly with Developing AI Applications with Python or Data Science modules. Our pedagogical team guides you.

Python or R for data science?

Python is today the dominant reference in data science and machine learning thanks to its ecosystem (pandas, scikit-learn, TensorFlow, PyTorch) and its natural integration with modern AI frameworks. R remains heavily used in academic statistics and biostatistics. Most data and AI teams in French-speaking Switzerland rely on Python. Our Python data science catalogue covers this scope.

Is Python suitable for web development and APIs?

Yes. Django remains a mature web framework for complete applications. Flask is appreciated for its lightness. FastAPI imposes itself as a modern framework for REST and asynchronous APIs, particularly for AI and data services. Our courses cover Python use in backend in complement to data and AI. Our pedagogical team guides you according to your project.

Are your Python courses available for companies?

Yes, the entire Python catalogue is available in-house, in Geneva, Lausanne and in virtual classroom, with a programme adapted to your internal stack (cloud, data warehouse, AI frameworks, DevOps tools) and priority business cases. Our team builds the specifications with you and organises sessions according to your calendar.