Python Training in Patras

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

This instructor-led live training, available either online or onsite, is designed for intermediate-level backend, platform, and machine learning engineers who aim to implement and orchestrate autonomous agents using Python tools and APIs.

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

• Establish and configure Python-based environments for agentic systems.
• Utilize 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 arrange a customized training session for this course, please get in touch with us.

This course delivers practical engineering strategies for designing, constructing, evaluating, and deploying agentic (autonomous) systems using Python. Key topics include the agent loop, tool integration, memory and state management, orchestration patterns, safety controls, and essential production considerations.

Delivered as instructor-led live training (either online or onsite), this program targets intermediate to advanced ML engineers, AI developers, and software engineers who aim to build robust, production-ready autonomous agents using Python.

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

• Design and implement the core 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 ensure agent composability.
• Apply best practices for safety, access control, and observability in deployed agents.

Course Format

• Interactive lectures and discussions.
• Hands-on labs focused on building agents with Python and popular SDKs.
• Project-based exercises resulting in deployable prototypes.

Customization Options

• To request customized training for this course, please contact us to arrange your specific requirements.

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

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

By the end of 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

• 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 Patras (online or onsite) is aimed at intermediate-level Python developers who wish to enhance their Python development experience using AWS Cloud9.

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

• Set up and configure AWS Cloud9 for Python development.
• Understand the AWS Cloud9 IDE interface and 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 Patras (online or onsite) is aimed at 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 highly versatile programming language, extensively utilized for data manipulation, automation, and analytics. Libraries such as Pandas and Polars offer robust, practical tools for managing tabular data on a large scale.

This instructor-led live training, available online or onsite, targets beginner to intermediate professionals looking to leverage Python for daily data analysis, file processing, and process automation using Pandas and Polars.

Upon completing this training, participants will be able to:

• Utilize Python to read, transform, and write CSV and Excel files.
• Execute common data cleaning and transformation tasks using Pandas and Polars.
• Automate repetitive data processes through Python scripts.
• Package simple scripts into executables and adhere to best practices for project management.

Course Format

• Interactive coding demonstrations combined with concise lectures.
• Practical exercises featuring guided code examples.
• Real-world mini-projects focused on automating actual tasks.

Course Customization Options

• To request a customized training session for this course, please get in touch with us to arrange details.

This immersive, practical course delves into advanced Python techniques, engineering best practices, and widely adopted design patterns to help you build maintainable, testable, and high-performance Python applications. The curriculum emphasizes modern tooling, type hinting, concurrency models, architectural patterns, and deployment-ready workflows.

Delivered as an instructor-led live training (available online or onsite), this programme is tailored for intermediate to advanced Python developers who aim to adopt professional practices and patterns for production-grade Python systems.

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

• Leverage Python typing, dataclasses, and type-checking to enhance code reliability.
• Utilize design patterns and architectural principles to structure robust applications.
• Correctly implement concurrency and parallelism using asyncio and multiprocessing.
• Develop well-tested code using pytest, property-based testing, and CI pipelines.
• Profile, optimize, and harden Python applications for production environments.
• Package, distribute, and deploy Python projects using modern tools and containers.

Format of the Course

• Interactive lectures and concise demonstrations.
• Hands-on labs and coding exercises each day.
• A capstone mini-project integrating patterns, testing, and deployment.

Course Customization Options

• To request customized training or focus areas (data, web, or infrastructure), please contact us to arrange.

This instructor-led live training in Patras (available online or onsite) targets beginner-level developers and data analysts eager to learn Python programming from scratch using Google Colab.

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

• Understand the basics of the Python programming language.
• Implement Python code in the Google Colab environment.
• Utilize control structures to manage the flow of a Python program.
• Create functions to organize and reuse code effectively.
• Explore and use basic libraries for Python programming.

This instructor-led live training (online or onsite) targets developers who wish to use 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 Patras (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.
• Troubleshoot and debug ROS applications.

This course is tailored for individuals eager to master the Python programming language. The curriculum focuses heavily on the Python language itself, its essential libraries, and the selection of the most effective tools developed by the vibrant Python community. Widely adopted by businesses and scientists globally, Python stands as one of the most popular programming languages in use today.

The training utilizes the latest Python 3.x version, incorporating practical exercises to fully leverage its capabilities. It is compatible with any operating system, including all UNIX variants (such as Linux and macOS) as well as Microsoft Windows.

The course structure allocates approximately 70% of the time to practical exercises, with the remaining 30% dedicated to demonstrations and presentations. Participants are encouraged to engage in discussions and ask questions throughout the sessions.

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

This instructor-led, live training in Patras (online or onsite) is designed for developers who want to master advanced Python programming techniques. It covers how to leverage this versatile language to address challenges in distributed applications, data analysis and visualization, UI development, and scripting for system maintenance.

Designed for individuals eager to master the Python programming language, this course places its primary focus on Python itself, its essential core libraries, and the selection of the most valuable tools developed by the vibrant Python community. As one of the world's most popular programming languages, Python is widely utilized by businesses and scientists globally.

This instructor-led, live training in Patras 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 Patras, participants will explore the most pertinent and state-of-the-art machine learning techniques in Python. Through the creation of a series of demonstrative applications involving image, music, text, and financial data, learners will gain practical expertise.

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

• Implement machine learning algorithms and techniques to address complex challenges.
• Apply deep learning and semi-supervised learning methods to applications dealing with image, music, text, and financial datasets.
• Maximize the potential of Python algorithms.
• Utilize libraries and packages such as NumPy and Theano.

This instructor-led, live training in Patras (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 practical proficiency in applying Machine Learning methodologies. Using the Python programming language along with its extensive library ecosystem and drawing on numerous real-world examples, the training covers the essential components of Machine Learning. Participants will learn how to make informed decisions regarding data modeling, interpret algorithm outputs, and validate results effectively.

The primary objective is to empower learners with the confidence to utilize fundamental Machine Learning tools while avoiding common pitfalls associated with Data Science applications.

Python has emerged as a highly popular programming language within the financial sector. Widely adopted by major investment banks and hedge funds, it is utilized to develop a diverse array of financial applications, ranging from core trading systems to sophisticated risk management tools.

Through this instructor-led live training, participants will gain the skills necessary to use Python for developing practical applications that address specific financial challenges.

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

• Grasp the fundamental concepts of Python programming
• Download, install, and maintain optimal development tools for building financial applications in Python
• Choose and apply appropriate Python packages and programming techniques to organize, visualize, and analyze financial data from various sources (CSV, Excel, databases, web, etc.)
• Construct applications that solve issues related to asset allocation, risk analysis, investment performance, and more
• Troubleshoot, integrate, deploy, and optimize a Python application

Audience

• Developers
• Analysts
• Quants

Format of the course

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

Note

• This training is designed to offer solutions to key problems faced by finance professionals. If there is a specific topic, tool, or technique you wish to include or expand upon, please contact us to arrange.

This course delves into practical methodologies for Data Science and AI leveraging Python, empowering professionals with the expertise to analyze data, develop machine learning models, and implement AI-driven solutions within business environments. Key topics include the CRISP-DM workflow, statistical analysis, supervised and unsupervised learning, deep learning with TensorFlow, natural language processing, big data processing with Spark, and data-driven storytelling. It is particularly suitable for beginners looking to obtain a Python data science certification and receive career-focused analytics training.

This course empowers programmers and data analysts with the essential techniques needed to construct machine learning solutions from the ground up using Python. It explores fundamental concepts of supervised learning, including classification and regression, as well as unsupervised learning methods such as clustering and anomaly detection, alongside advanced neural network designs. Participants will examine proven strategies for utilizing scikit-learn, Apache Spark MLlib, and Jupyter notebooks for practical AI development. The program enables professionals to build effective ML models, assess algorithm constraints, and execute applied projects that address real-world challenges.

Selenium is a free and 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 better Grid support. Python complements Selenium well due to its simplicity and robust integration with testing frameworks such as Pytest, making it an excellent choice for creating scalable and easy-to-maintain test automation suites.

This instructor-led live training (available online or on-site) is designed for testers and developers at the beginner to intermediate level who want to leverage Selenium and Python to automate web application testing in practical, real-world scenarios.

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

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

Course Format

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

Course Customization Options

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

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

By the end 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 obtain insights from various datasets.
• Convert existing Matlab applications to Python.
• Integrate Matlab and Python applications.

This instructor-led, live training in Patras (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.

In this instructor-led, live training, attendees will master advanced Python programming techniques, including applying this versatile language to address challenges in domains like distributed applications, data analysis and visualization, UI programming, and maintenance scripting.

Course Format

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

Course Customization Options

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

This instructor-led, live training in Patras (online or onsite) is aimed at 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:

• Set up the environment to start building big data processing with 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 (Numpy, SciPy, and Pandas) using Dask.
• Optimize the Dask environment to maintain high performance in handling large datasets.

This instructor-led, live training in Patras (available online or onsite) is tailored for business analysts seeking to automate trading using algorithmic strategies, Python, and R.

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

• Utilize algorithms to rapidly buy and sell securities at specific, specialized increments.
• Lower costs associated with trading through the application of algorithmic methods.
• Automatically monitor stock prices and execute trades.

Course Overview

This practical training programme is tailored for data engineering professionals looking to develop concrete competencies in artificial intelligence, Python, and large language models. Emphasizing real-world application, the curriculum covers model utilization, prompt engineering, and the creation of AI-driven solutions. Participants will engage in a series of progressive exercises, advancing from foundational concepts to the construction of deployable AI workflows.

Training Format

• Face-to-face classroom instruction

• Instructor-led sessions featuring guided practice

• Interactive discussions and analysis of real-world case studies

• Daily practical exercises

Course Objectives

• Gain a solid understanding of core AI and machine learning principles applicable to contemporary solutions

• Enhance Python proficiency for AI development and data processing workflows

• Comprehend the mechanics of large language models and apply them effectively

• Craft and refine prompts to ensure consistent and reliable outputs

• Develop comprehensive AI solutions leveraging APIs and frameworks

• Seamlessly integrate AI capabilities into data engineering pipelines

This instructor-led, live training in Patras (online or onsite) is aimed at developers who wish to use FastAPI with Python to build, test, and deploy RESTful APIs easier and faster.

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 Patras (online or onsite) targets data scientists who wish to utilize TensorFlow for analyzing potential fraud data.

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

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

This instructor-led live training, held in Patras (online or onsite), is tailored for network engineers seeking 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 Patras (online or onsite) is aimed at business professionals and data analysts with intermediate Python skills who wish to apply Python to automate workflows, analyse business data, and generate dynamic Excel-based reports.

This instructor-led live training in Patras (online or onsite) is aimed at penetration testers who wish to perform network penetration tests in Kali Linux using Python.

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

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

Designed for advanced practitioners, this instructor-led live training is available either online or at your location.

Course Format

• Engaging lectures combined with interactive discussions.
• Extensive exercises and practical application.
• Practical implementation within a live-lab environment.

Customization Options

• For tailored training on this subject, please reach out to us to make arrangements.

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 leverage Python for quantitative finance.

By the conclusion 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 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 interpretation of valuable information from digital media. Python, a high-level programming language renowned for its clarity and code readability, serves as the primary tool for this training.

Through this instructor-led live session, participants will grasp 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 concepts of Computer Vision
• Utilize Python to execute Computer Vision tasks
• Develop custom systems for detecting faces, objects, and motion

Target Audience

• Python developers keen on exploring Computer Vision

Course Format

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

This practical course is tailored for Unix and shell users aiming to boost their automation capabilities by utilizing Python. Although shell scripting is still effective for straightforward tasks, Python offers far greater flexibility, readability, and scalability for complex automation, system administration, and DevOps workflows.

Tableau serves as a prominent business intelligence and data visualization platform, while Python is a versatile programming language offering extensive support for statistical and machine learning techniques. By leveraging Tableau's visualization strengths alongside Python's machine learning capabilities, developers can efficiently construct advanced data analytics solutions tailored to diverse business requirements.

Through this instructor-led live training, participants will acquire the skills necessary to integrate Tableau and Python for performing sophisticated analytics. This integration is achieved utilizing the TabPy API.

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

• Integrate Tableau and Python via the TabPy API
• Utilize the synergy between Tableau and Python to analyze complex business scenarios with minimal Python code

Audience

• Developers
• Data scientists

Course Format

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