Python Training in Prague

Python serves as the foundational language for developing and orchestrating autonomous AI agents. This course emphasizes practical implementation, leveraging modern SDKs and frameworks such as LangChain and AutoGen to construct, integrate, and manage agent workflows.

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

Upon completion of this training, participants will be capable of:

• Setting up and configuring Python-based environments for agentic systems.
• Utilizing popular agent SDKs like LangChain and AutoGen to develop functional agents.
• Integrating tools and APIs to enhance agent capabilities.
• Orchestrating multi-agent workflows and communication patterns.
• Applying 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 customized training for this course, please contact us to arrange.

This course provides practical engineering methodologies for designing, building, testing, and deploying agentic (autonomous) systems using Python. It covers essential topics such as the agent loop, tool integrations, memory and state management, orchestration patterns, safety controls, and production-ready considerations.

This instructor-led, live training (available online or onsite) is designed for intermediate to advanced-level 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 agent loop and decision-making workflows.
• Integrate external tools and APIs to extend 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 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.

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

This instructor-led live training, available either online or onsite, is designed for intermediate-level Python programmers who want 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

• Interactive lectures and discussions.
• Ample exercises and practice opportunities.
• 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, conducted Prague (online or onsite), is designed for intermediate Python developers aiming to elevate their 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 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 Prague (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 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

• 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 intensive, practical course delves into advanced Python techniques, engineering best practices, and widely used 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 instructor-led live training (available online or onsite), this program is designed for intermediate to advanced Python developers aiming to adopt professional practices and patterns suitable for production-grade Python systems.

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

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

Course Format

• Interactive lectures and concise demonstrations.
• Hands-on labs and coding exercises conducted daily.
• A capstone mini-project that integrates patterns, testing, and deployment.

Customization Options

• To request customized training or focus on a specific area (data, web, or infrastructure), please contact us to arrange.

This instructor-led, live training in Prague (online or on-site) targets beginner-level developers and data analysts interested in learning Python programming from scratch via Google Colab.

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

• Understand the foundational concepts of the Python programming language.
• Implement Python code within the Google Colab environment.
• Employ control structures to direct the flow of a Python program.
• Build functions to organize and reuse code effectively.
• Explore and apply essential libraries for Python programming.

This instructor-led, live training in (online or onsite) is aimed at 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 Prague (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 places primary emphasis on Python itself, its core libraries, and the most valuable tools developed by the vibrant Python community. Python powers businesses globally and is widely adopted by scientists, making it one of the most prevalent programming languages in use today.

The course utilizes the latest Python version 3.x, featuring practical exercises that harness its full potential. It is compatible with all major operating systems, including various UNIX distributions (such as Linux and Mac OS X) as well as Microsoft Windows.

Approximately 70% of the course time is dedicated to hands-on practical exercises, while the remaining 30% consists of demonstrations and presentations. Participants are encouraged to engage in discussions and ask questions throughout the session.

Note: The training content can be customized to meet specific requirements if requested in advance of the scheduled course date.

This instructor-led, live training in Prague (online or onsite) is designed for developers who wish to learn advanced Python programming techniques, including how to apply this versatile language to solve problems in areas such as distributed applications, data analysis and visualization, UI programming and maintenance scripting.

This course is tailored for individuals looking to master the Python programming language. It places strong emphasis on the core Python language and its essential libraries, while also guiding you in selecting the most valuable tools developed by the vibrant Python community. Widely used by scientists globally and integral to modern business operations, Python stands as one of the most popular programming languages today.

This instructor-led, live training in Prague 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 Prague, participants will learn the most relevant and cutting-edge machine learning techniques in Python as they build a series of demo applications involving image, music, text, and financial data.

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

• Implement machine learning algorithms and techniques for solving 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.
• Use libraries and packages such as NumPy and Theano.

This instructor-led, live training in Prague (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 is designed to equip participants with practical proficiency in applying Machine Learning techniques. Utilizing the Python programming language and its extensive ecosystem of libraries, along with numerous hands-on examples, the curriculum covers the essential components of Machine Learning. Participants will learn to make informed decisions regarding data modeling, interpret algorithm outputs, and validate results effectively.

The primary objective is to provide you with the confidence to understand and utilize the core tools from the Machine Learning toolkit, while avoiding common pitfalls associated with Data Science applications.

Python has become immensely popular within the financial sector. It is widely adopted by leading investment banks and hedge funds to develop a diverse array of financial applications, from core trading platforms to risk management systems.

During this instructor-led live training, participants will learn to leverage Python to create practical solutions for various specific finance challenges.

Upon completing this training, participants will be able to:

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

Target Audience

• Developers
• Analysts
• Quants

Course Format

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

Note

• This training focuses on providing solutions to key problems faced by finance professionals. If you have a specific topic, tool, or technique you wish to include or expand upon, please contact us to arrange a custom agenda.

This course explores practical applications of Data Science and AI through Python, equipping professionals with the ability to analyze data, construct machine learning models, and implement AI-powered solutions in business environments. It covers the CRISP-DM methodology, statistical analysis, supervised and unsupervised learning techniques, deep learning with TensorFlow, natural language processing, big data handling with Spark, and the art of data-driven storytelling. Designed for beginners seeking Python data science certification and career-focused analytics training.

The course 'Applied AI from Scratch in Python' provides programmers and data analysts with the essential techniques required to develop machine learning solutions entirely from the ground up using Python. The curriculum covers the fundamental principles of supervised learning, including classification and regression, as well as unsupervised learning methods such as clustering and anomaly detection, alongside advanced neural network architectures. Participants will explore proven methodologies for leveraging tools like scikit-learn, Apache Spark MLlib, and Jupyter notebooks to facilitate hands-on AI development. The program is designed to help professionals implement practical ML models, critically evaluate the limitations of various algorithms, and complete applied projects aimed at solving real-world problems.

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, known for its simplicity and robust integration with testing frameworks such as Pytest, stands out as a powerful choice for creating scalable and maintainable test automation suites.

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

Upon completing this training, participants will be able to:

• Install and set up Selenium with Python within a testing environment.
• Develop robust test automation scripts using Selenium WebDriver and Pytest.
• Implement the Page Object Model (POM) to create maintainable test frameworks.
• Execute tests across multiple browsers utilizing 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.
• Extensive exercises and practical practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• For those seeking a customized training experience for this course, please contact us to arrange it.

This instructor-led, live training in Prague (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 Prague (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 the right format, from raw numbers to data visualizations.
• Gain valuable insights from data, including performance trends and problematic areas.

Course Overview

This practical training program is tailored for data engineering professionals aiming to develop tangible skills in artificial intelligence, Python, and large language models. The curriculum emphasizes real-world applications, including the utilization of models, prompt engineering, and the creation of AI-driven solutions. Participants will engage in a series of progressive exercises that transition from foundational concepts to the development of deployable AI workflows.

Format of Training

• In-person classroom instruction

• Instructor-led sessions featuring guided practice

• Interactive discussions supported by real-world case studies

• Daily hands-on exercises

Course Objectives

• Gain a solid understanding of core AI and machine learning concepts applicable to modern scenarios

• Enhance Python proficiency for AI development and data workflows

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

• Design and optimize prompts to ensure reliable outputs

• Construct end-to-end AI solutions leveraging APIs and frameworks

• Seamlessly integrate AI capabilities into data engineering pipelines

This instructor-led live training in Prague (online or onsite) is aimed at 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 Prague (online or on-site) targets data scientists who wish to utilize 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 Prague (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 utilize Paramiko, Netmiko, Napalm, Telnet, and pyntc for network automation with Python.
• Master multi-threading and multiprocessing in network automation.
• Utilize GNS3 and Python for network programming.

This instructor-led, live training in Prague (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.

Computer Vision is a discipline focused on automatically extracting, analyzing, and interpreting valuable information from digital media. Python, a high-level programming language, is renowned for its clear syntax and code readability.

In this instructor-led live training, participants will grasp the fundamentals of Computer Vision while stepping through the development of a series of simple Computer Vision applications using Python.

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

• Comprehend the core concepts of Computer Vision
• Utilize Python to execute Computer Vision tasks
• Develop their own systems for face, object, and motion detection

Audience

• Python programmers interested in Computer Vision

Format of the course

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

This practical course is tailored for Unix and shell users aiming to upgrade their automation skills by leveraging Python. Although shell scripting is still effective for basic tasks, Python offers far greater flexibility, clarity, and scalability for complex automation, system administration, and DevOps workflows.