Python Training in Rennes

Python serves as the foundational language for developing and orchestrating autonomous AI agents. This course emphasizes practical implementation using contemporary SDKs and frameworks, such as LangChain and AutoGen, to build, connect, and manage agent workflows.

Delivered as an instructor-led live training (available online or onsite), this program is designed for intermediate-level backend, platform, and ML engineers who aim to implement and orchestrate autonomous agents using Python tooling and APIs.

Upon completion of this training, participants will be equipped to:

• Set up and configure Python-based environments for agentic systems.
• Leverage popular agent SDKs, including LangChain and AutoGen, to develop functional agents.
• Integrate tools and APIs to expand agent capabilities.
• Orchestrate multi-agent workflows and communication patterns.
• Apply best practices for debugging, testing, and maintaining agentic codebases.

Course Format

• Interactive lectures and discussions.
• Hands-on programming exercises and live demonstrations.
• Practical projects focused on building end-to-end agent workflows.

Course Customization Options

• To request a customized training session for this course, please contact us to arrange.

This course delivers practical engineering methodologies for designing, building, testing, and deploying agentic (autonomous) systems using Python. It explores the agent loop, tool integrations, memory and state management, orchestration patterns, safety controls, and production considerations.

This instructor-led, live training (available online or onsite) is designed for intermediate to advanced ML engineers, AI developers, and software engineers seeking to build robust, production-ready autonomous agents using Python.

By the conclusion of this training, participants will be able to:

• Design and implement the agent loop and decision-making workflows.
• Integrate external tools and APIs to expand agent capabilities.
• Implement short-term and long-term memory architectures for agents.
• Coordinate multi-step orchestrations and agent composability.
• Apply safety, access control, and observability best practices for deployed agents.

Course Format

• Interactive lecture and discussion.
• Hands-on labs building agents with Python and popular SDKs.
• Project-based exercises that produce deployable prototypes.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Artificial Intelligence with Python involves building intelligent systems by leveraging Python’s robust ecosystem of AI and machine learning libraries.

This instructor-led live training, available online or onsite, is designed for intermediate Python programmers looking to design, implement, and deploy AI solutions using Python.

Upon completing this training, participants will be able to:

• Implement AI algorithms using Python’s core AI libraries.
• Work with supervised, unsupervised, and reinforcement learning models.
• Integrate AI solutions into existing applications and workflows.
• Evaluate model performance and optimize for accuracy and efficiency.

Format of the Course also allows for the evaluation of participants.

• Interactive lecture and discussion.
• Extensive exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Rennes (online or onsite) is designed for intermediate-level Python developers who aim to enhance their Python development experience using AWS Cloud9.

By the conclusion of this training, participants will be able to:

• Set up and configure AWS Cloud9 for Python development.
• Understand the AWS Cloud9 IDE interface and its features.
• Write, debug, and deploy Python applications in AWS Cloud9.
• Collaborate with other developers using the AWS Cloud9 platform.
• Integrate AWS Cloud9 with other AWS services for advanced deployments.

This instructor-led, live training in Rennes (online or onsite) targets expert-level data analysts who wish to leverage Python's data analysis capabilities within Power BI, enhancing their ability to analyze and visualize data effectively.

By the end of this training, participants will be able to:

• Learn how Python can be integrated into Power BI for data analysis.
• Use Python scripts to load, clean, and preprocess data within the Power BI environment.
• Enhance data visualization capabilities by creating custom and interactive visualizations using Python.
• Acquire advanced data analysis skills using Python.

Python is a versatile programming language widely used for data manipulation, automation, and analytics. Libraries like Pandas and Polars provide powerful, practical tools for working with tabular data at scale.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level professionals who wish to apply Python for everyday data analysis, file processing, and process automation using Pandas and Polars.

By the end of this training, participants will be able to:

• Use Python to read, transform, and write CSV and Excel files.
• Perform common data cleaning and transformation tasks with Pandas and Polars.
• Automate repetitive data processes with Python scripts.
• Package simple scripts into executables and follow best practices for projects.

Format of the Course also allows for the evaluation of participants.

• Interactive coding demonstrations and short lectures.
• Hands-on exercises with guided code examples.
• Practical mini-projects to automate real-world tasks.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Rennes (online or onsite) is aimed at experienced developers who wish to gain a comprehensive understanding of Python programming and its applications in cybersecurity.

By the end of this training, participants will be able to:

• Use Python programming for defensive cybersecurity.
• Understand and use Python for ethical offensive techniques and digital forensics tasks.
• Recognize legal and ethical considerations surrounding offensive cybersecurity and vulnerability disclosure.

This intensive, hands-on course explores advanced Python techniques, engineering best practices, and widely used design patterns to help you build Python applications that are maintainable, testable, and high-performing. It places emphasis on modern tooling, type hinting, concurrency models, architectural patterns, and deployment-ready workflows.

Delivered as instructor-led live training (online or onsite), this program targets intermediate to advanced Python developers aiming to adopt professional practices and patterns for production-grade Python systems.

Upon completion of this training, participants will be able to:

• Enhance code reliability by applying Python typing, dataclasses, and type-checking.
• Structure robust applications using design patterns and architectural principles.
• Correctly implement concurrency and parallelism utilizing asyncio and multiprocessing.
• Develop well-tested code through the use of pytest, property-based testing, and CI pipelines.
• Profile, optimize, and harden Python applications for production environments.
• Package, distribute, and deploy Python projects employing modern tools and containers.

Course Format

• Interactive lectures paired with concise demonstrations.
• Daily hands-on labs and coding exercises.
• A capstone mini-project that integrates patterns, testing, and deployment.

Course Customization Options

• To request customized training or focus on specific areas (data, web, or infrastructure), please contact us to make arrangements.

This instructor-led, live training in Rennes (online or onsite) is aimed at beginner-level developers and data analysts who wish to learn Python programming from scratch using Google Colab.

By the end of this training, participants will be able to:

• Grasp the fundamentals of the Python programming language.
• Write and run Python code within the Google Colab environment.
• Apply control structures to manage the flow of a Python program.
• Develop functions to organize and reuse code effectively.
• Explore and utilize basic libraries for Python programming.

This instructor-led live training, offered online or onsite, is intended for developers aiming to leverage the FARM (FastAPI, React, and MongoDB) stack to build dynamic, high-performance, and scalable web applications.

By the end of this training, participants will be able to:

• Set up the necessary development environment that integrates FastAPI, React, and MongoDB.
• Understand the key concepts, features, and benefits of the FARM stack.
• Learn how to build REST APIs with FastAPI.
• Learn how to design interactive applications with React.
• Develop, test, and deploy applications (front end and back end) using the FARM stack.

This instructor-led, live training in Rennes (online or onsite) is aimed at beginner-level to intermediate-level and potentially advanced-level robotics developers who wish to learn how to use ROS to program mobile robots using Python.

By the end of this training, participants will be able to:

• Set up a development environment that includes ROS, Python, and a mobile robot platform.
• Create and run ROS nodes, topics, services, and actions using Python.
• Use ROS tools and utilities to monitor and debug ROS applications.
• Use ROS packages and libraries to perform common tasks for mobile robots.
• Integrate ROS with other frameworks and tools.
• Troubleshooting and debugging ROS applications.

This course is tailored for individuals eager to master the Python programming language. The curriculum focuses on the Python language itself, its core libraries, and the selection of the most valuable and widely adopted libraries within the Python community. Python is a powerhouse for businesses and is extensively utilized by scientists globally, ranking among the most popular programming languages today.

The course can be conducted using the latest Python 3.x version, featuring practical exercises that leverage the full capabilities of the language. It is compatible with any operating system, including all variations of UNIX (such as Linux and Mac OS X) as well as Microsoft Windows.

Approximately 70% of the course duration is dedicated to practical exercises, while the remaining 30% covers demonstrations and presentations. Participants are encouraged to engage in discussions and ask questions throughout the training.

Note: The training can be customized to meet specific requirements upon prior request before the scheduled course date.

This instructor-led, live training in Rennes (online or on-site) is designed for developers who want to master advanced Python programming techniques. The course covers how to leverage this versatile language to address challenges in areas such as distributed applications, data analysis and visualization, UI development, and maintenance scripting.

This course is tailored for individuals eager to master the Python programming language. The focus lies on the Python language itself, its core libraries, and the curation of the most valuable and effective libraries contributed by the Python community. Python is a cornerstone for businesses and a preferred tool for scientists globally, ranking among the most popular programming languages in use today.

This course aims to build foundational proficiency in applying Machine Learning techniques in real-world scenarios. Utilizing Python and its extensive ecosystem of libraries, along with numerous practical examples, the curriculum covers the essential components of Machine Learning. Participants will learn how to make informed decisions regarding data modeling, interpret algorithmic outputs, and validate results effectively.

The objective is to equip you with the confidence to leverage core Machine Learning tools while helping you avoid common pitfalls associated with Data Science applications.

This instructor-led, live training in Rennes is based on the popular book, "Automate the Boring Stuff with Python", by Al Sweigart. It is aimed at beginners and covers essential Python programming concepts through practical, hands-on exercises and discussions. The focus is on learning to write code to dramatically increase office productivity.

By the end of this training, participants will know how to program in Python and apply this new skill for:

• Automating tasks by writing simple Python programs.
• Writing programs that can do text pattern recognition with "regular expressions".
• Programmatically generating and updating Excel spreadsheets.
• Parsing PDFs and Word documents.
• Crawling web sites and pulling information from online sources.
• Writing programs that send out email notifications.
• Use Python's debugging tools to quickly resolve bugs.
• Programmatically controlling the mouse and keyboard to click and type for you.

In this instructor-led live training in Rennes, participants will master the most relevant and cutting-edge machine learning techniques in Python by building a series of demonstration applications that process image, music, text, and financial data.

By the end of this training, participants will be able to:

• Implement machine learning algorithms and techniques to solve complex problems.
• Apply deep learning and semi-supervised learning to applications involving image, music, text, and financial data.
• Push Python algorithms to their maximum potential.
• Utilize libraries and packages such as NumPy and Theano.

This instructor-led, live training in Rennes (online or onsite) is aimed at intermediate-level Python developers and data analysts who wish to enhance their skills in data analysis and manipulation using Pandas and NumPy.

By the end of this training, participants will be able to:

• Set up a development environment that includes Python, Pandas, and NumPy.
• Create a data analysis application using Pandas and NumPy.
• Perform advanced data wrangling, sorting, and filtering operations.
• Conduct aggregate operations and analyze time series data.
• Visualize data using Matplotlib and other visualization libraries.
• Debug and optimize their data analysis code.

This course aims to equip participants with general proficiency in applying Machine Learning methods in real-world scenarios. By leveraging the Python programming language and its extensive ecosystem of libraries, and supported by a wide range of practical examples, the course demonstrates how to utilize the essential components of Machine Learning. Participants will learn to make informed data modeling decisions, interpret algorithm outputs, and validate results effectively.

Our objective is to empower you with the confidence to understand and apply the core tools of the Machine Learning toolkit, while helping you steer clear of common pitfalls associated with Data Science applications.

Python has become immensely popular in the financial sector. Adopted by top investment banks and hedge funds, it is used to develop a diverse array of financial applications, from core trading systems to risk management platforms.

Through this instructor-led live training, participants will learn how to leverage Python to create practical solutions for various financial challenges.

By the conclusion of this training, participants will be able to:

• Grasp the fundamentals of Python programming
• Download, install, and configure the most effective development tools for building financial applications in Python
• Select and apply appropriate Python packages and programming techniques to organize, visualize, and analyze financial data from diverse sources (CSV, Excel, databases, web, etc.)
• Build applications that address issues such as asset allocation, risk analysis, investment performance, and more
• Troubleshoot, integrate, deploy, and optimize Python applications

Audience

• Developers
• Analysts
• Quants

Course Format

• A blend of lectures, discussions, exercises, and extensive hands-on practice

Note

• This training is designed to address key challenges faced by finance professionals. If you have a specific topic, tool, or technique you would like to include or expand upon, please contact us to arrange.

This course offers a practical exploration of Data Science and AI through Python, empowering professionals with the capabilities to analyze data, construct machine learning models, and implement AI-powered applications within business environments. It addresses CRISP-DM methodologies, statistical analysis, supervised and unsupervised learning, deep learning with Tensorflow, natural language processing, big data analytics via Spark, and data-driven storytelling. This program is ideal for beginners aiming to obtain a Python data science certification and acquire career-ready analytics skills.

This is a 4-day course introducing AI and its applications using the Python programming language. There is an option to have an additional day to undertake an AI project upon completion of this course.

Selenium is an open-source framework designed for automating web application testing across various browsers. With the release of Selenium 4, users gain access to enhanced WebDriver APIs, native relative locators, and improved grid support. Python is chosen for its simplicity and robust integration with testing frameworks such as Pytest, making it an excellent choice for building scalable and maintainable test automation suites.

This instructor-led live training, available online or onsite, targets beginner to intermediate testers and developers who want to leverage Selenium with Python to automate web application testing in real-world scenarios.

Upon completion of this training, participants will be able to:

• Install and configure Selenium with Python within a test environment.
• Develop robust test automation scripts using Selenium WebDriver and Pytest.
• Apply the Page Object Model (POM) to create maintainable test frameworks.
• Execute tests across multiple browsers using Selenium Grid.
• Integrate automated tests with CI/CD pipelines.
• Troubleshoot common issues and implement best practices to ensure automation stability.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practical sessions.
• Hands-on implementation in a live-lab environment.

Customization Options

• To arrange customized training for this course, please contact us.

During this instructor-led live training in Rennes (onsite or remote), participants will learn how to combine the capabilities of Python and Excel.

By the end of this training, participants will be able to:

• Install and configure packages to integrate Python and Excel.
• Read, write, and manipulate Excel files using Python.
• Call Python functions from within Excel.

This instructor-led live training in Rennes (online or onsite) is designed for Matlab users who wish to explore or transition to Python for data analytics and visualization.

Upon completion of this training, participants will be able to:

• Install and configure a Python development environment.
• Understand the differences and similarities between Matlab and Python syntax.
• Use Python to extract insights from various datasets.
• Convert existing Matlab applications to Python.
• Integrate Matlab and Python applications.

This instructor-led, live training in Rennes (online or onsite) is aimed at persons who wish to learn just enough Python to begin crunching numbers from sales data, traffic analytics, customer interactions, etc..

By the end of this training, participants will be able to:

• Install and configure the necessary software, libraries and development environment to begin writing Python code for data analysis.
• Analyze data from sources such as Excel, CSV, JSON files and databases.
• Clean data to improve its usefulness before analyzing it.
• Perform simple statistical analysis.
• Generate reports that present the desired data in just the right format, from straight numbers to data visualizations.
• Gain valuable insight from data, including trends in performance, problematic areas.

During this instructor-led live training, participants will master advanced Python programming techniques, applying this versatile language to address challenges in areas such as distributed applications, data analysis and visualization, UI programming, and maintenance scripting.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practice sessions.
• Practical implementation within a live-lab environment.

Customization Options

• To add, remove, or customize any section or topic within this course, please contact us to make arrangements.

This instructor-led, live training in Rennes (online or onsite) is designed for data scientists and software engineers who wish to use Dask with the Python ecosystem to build, scale, and analyze large datasets.

By the end of this training, participants will be able to:

• Configure the environment to begin building big data processing solutions using Dask and Python.
• Explore the features, libraries, tools, and APIs available in Dask.
• Understand how Dask accelerates parallel computing in Python.
• Learn how to scale the Python ecosystem (including NumPy, SciPy, and Pandas) using Dask.
• Optimize the Dask environment to maintain high performance when handling large datasets.

This instructor-led live training in Rennes (online or onsite) is designed for business analysts aiming to automate trading via algorithmic methods, Python, and R.

By the end of this training, participants will be able to:

• Use algorithms to rapidly buy and sell securities at specialized intervals.
• Reduce trade-related costs through algorithmic trading.
• Automatically monitor stock prices and execute trades.

This instructor-led, live training in Rennes (online or onsite) is aimed at intermediate-level developers who wish to use CUDA to build Python applications that run in parallel on NVIDIA GPUs.

By the end of this training, participants will be able to:

• Use the Numba compiler to accelerate Python applications running on NVIDIA GPUs.
• Create, compile and launch custom CUDA kernels.
• Manage GPU memory.
• Convert a CPU based application into a GPU-accelerated application.

Course Overview

This practical training program is tailored for data engineering professionals seeking to develop applied skills in artificial intelligence, Python, and large language models. The curriculum emphasizes real-world use cases, including model utilization, prompt engineering, and the creation of AI-driven solutions. Participants will engage in progressive exercises that advance from foundational concepts to the construction of deployable AI workflows.

Training Format

• In-person classroom instruction

• Instructor-led sessions with guided practice

• Interactive discussions and real-world case studies

• Daily hands-on exercises

Course Objectives

• Grasp core AI and machine learning concepts applicable to modern solutions

• Enhance Python proficiency for AI development and data workflows

• Comprehend the mechanics of large language models and learn to leverage them effectively

• Design and optimize prompts to ensure reliable outputs

• Develop end-to-end AI solutions utilizing APIs and frameworks

• Integrate AI capabilities into data engineering pipelines

This instructor-led live training in Rennes (online or onsite) targets developers who wish to use FastAPI with Python to build, test, and deploy RESTful APIs more easily and quickly.

By the end of this training, participants will be able to:

• Set up the necessary development environment to develop APIs with Python and FastAPI.
• Create APIs quicker and easier using the FastAPI library.
• Learn how to create data models and schemas based on Pydantic and OpenAPI.
• Connect APIs to a database using SQLAlchemy.
• Implement security and authentication in APIs using the FastAPI tools.
• Build container images and deploy web APIs to a cloud server.

This instructor-led live training in Rennes (online or onsite) targets data scientists who want to use TensorFlow to analyze potential fraud data.

By the end of this training, participants will be able to:

• Create a fraud detection model in Python and TensorFlow.
• Build linear regressions and linear regression models to predict fraud.
• Develop an end-to-end AI application for analyzing fraud data.

This instructor-led, live training in Rennes (online or onsite) is designed for network engineers who want to maintain, manage, and design computer networks using Python.

By the end of this training, participants will be able to:

• Optimize and leverage Paramiko, Netmiko, Napalm, Telnet, and pyntc for network automation with Python.
• Master multi-threading and multiprocessing in network automation.
• Use GNS3 and Python for network programming.

This instructor-led, live training in Rennes (online or onsite) is aimed at business professionals and data analysts with intermediate Python skills who wish to apply Python to automate workflows, analyze business data, and generate dynamic Excel-based reports.

This instructor-led live training in Rennes (online or onsite) is designed for penetration testers who wish to conduct network penetration tests using Kali Linux and Python.

By the end of this training, participants will be able to:

• Create Python programs to identify network vulnerabilities.
• Explore and use Kali web shells and shellcode in exploits.
• Apply various Kali tools for penetration testing.
• Exploit systems using Python.

Python is a high-level programming language renowned for its clear syntax and code readability.

In this instructor-led, live training, participants will learn how to use Python for quantitative finance.

By the end of this training, participants will be able to:

• Understand the fundamentals of Python programming
• Use Python for financial applications including implementing mathematical techniques, stochastics, and statistics
• Implement financial algorithms using performance-oriented Python

Audience

• Developers
• Quantitative analysts

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

Computer Vision is a discipline focused on the automatic extraction, analysis, and comprehension of valuable insights from digital media. Python, a high-level programming language renowned for its clean syntax and readability, serves as the foundation for this course.

Through this instructor-led live training, participants will master the fundamentals of Computer Vision by developing a series of simple applications using Python.

Upon completion of this training, participants will be able to:

• Grasp the core principles of Computer Vision
• Utilize Python to execute Computer Vision tasks
• Develop custom systems for face, object, and motion detection

Audience

• Python programmers seeking to specialize in Computer Vision

Format of the course

• A blend of lectures, discussions, exercises, and extensive hands-on practice

This course introduces students to the Python language using a security-first pedagogical approach. Upon completion, students will be able to write non-trivial Python programs addressing a wide range of domains while applying industry-standard secure coding principles. Topics include language components, working with professional IDEs, control flow constructs, strings, input/output, collections, classes, modules, and regular expressions—all evaluated through the lenses of vulnerability mitigation and secure architecture. The course is supplemented with numerous hands-on labs, secure solutions, and code examples.

After completing the course, students will be able to demonstrate knowledge and understanding of Python Security Principles, environment-scoped security policies (skope-rules), dependency isolation, automated SAST/DAST integration, and DevSecOps-aligned secure development workflows.

This practical course is tailored for Unix and shell users aiming to upgrade their automation skills through the power of Python. While shell scripting is effective for basic tasks, Python offers superior flexibility, readability, and scalability, making it the ideal choice for complex automation, system administration, and DevOps workflows.

This instructor-led, live training (available online or onsite) is designed for developers and data scientists who want to leverage spaCy to process massive volumes of text, identify patterns, and extract actionable insights.

By the conclusion of this training, participants will be able to:

• Install and configure spaCy.
• Gain a comprehensive understanding of spaCy’s approach to Natural Language Processing (NLP).
• Extract patterns and derive business insights from large-scale data sources.
• Integrate the spaCy library into existing web and legacy applications.
• Deploy spaCy in live production environments to predict human behavior.
• Utilize spaCy to pre-process text for Deep Learning applications.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request customized training for this course, please contact us to arrange details.
• For more information about spaCy, please visit: https://spacy.io/

Tableau is a business intelligence and data visualization tool. Python is a widely used programming language which provides support for a wide variety of statistical and machine learning techniques. Tableau's data visualization power and Python's machine learning capabilities, when combined, help developers rapidly build advanced data analytics applications for various business use cases.

In this instructor-led, live training, participants will learn how to combine Tableau and Python to carry out advanced analytics. Integration of Tableau and Python will be done via the TabPy API.

By the end of this training, participants will be able to:

• Integrate Tableau and Python using TabPy API
• Use the integration of Tableau and Python to analyze complex business scenarios with few lines of Python code

Audience

• Developers
• Data scientists

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

This instructor-led live training in Rennes (online or on-site) is intended for data scientists and developers who wish to use Modin to build and implement parallel computations with Pandas for faster data analysis.

By the end of this training, participants will be able to:

• Configure the necessary environment to begin developing scalable Pandas workflows with Modin.
• Gain an understanding of Modin's features, architecture, and benefits.
• Distinguish between Modin, Dask, and Ray.
• Execute Pandas operations more efficiently using Modin.
• Implement the full Pandas API and its functions.