Python Training in Bratislava

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

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

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

• Establish and configure Python environments tailored for agentic systems.
• Leverage leading agent SDKs, including LangChain and AutoGen, to develop functional agents.
• Incorporate tools and APIs to expand agent capabilities.
• Orchestrate complex multi-agent workflows and communication patterns.
• Implement best practices for debugging, testing, and maintaining codebases for agentic systems.

Course Format

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

Course Customization Options

• For customized training requests, please reach out to us to arrange.

This course imparts practical engineering methodologies for designing, developing, testing, and deploying agentic (autonomous) systems via Python. Key topics include the agent loop, tool integrations, memory and state management, orchestration patterns, safety mechanisms, and production-grade considerations.

Designed as an instructor-led live training session (available online or on-site), this program targets intermediate to advanced ML engineers, AI developers, and software engineers seeking to create robust, production-ready autonomous agents using Python.

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

• Designing and implementing the agent loop and decision-making workflows.
• Integrating external tools and APIs to expand agent functionality.
• Implementing memory architectures that support both short-term and long-term retention.
• Coordinating complex orchestrations and enabling agent composability.
• Applying 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.

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 comprehensive ecosystem of AI and machine learning libraries.

Designed for intermediate-level Python developers, this instructor-led live training (available online or onsite) focuses on designing, implementing, and deploying AI solutions using Python.

Upon completing this training, participants will be equipped 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 Bratislava (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 Bratislava (online or on-site) is designed for expert-level data analysts who want to leverage Python’s data analysis capabilities within Power BI, thereby 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 immersive, practical course explores advanced Python techniques, engineering best practices, and widely adopted design patterns to help you create maintainable, testable, and high-performance Python applications. The curriculum focuses on modern tooling, type hinting, concurrency models, architectural patterns, and deployment-ready workflows.

This instructor-led, live training (available online or onsite) is designed for intermediate to advanced Python developers looking to implement 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 containerization.

Course Format

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

Course Customization Options

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

This instructor-led live training in Bratislava (available online or on-site) is targeted 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:

• 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, offered online or onsite, is designed for developers aiming to utilize 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 required development environment integrating FastAPI, React, and MongoDB.
• Understand the core concepts, features, and benefits of the FARM stack.
• Learn how to construct REST APIs with FastAPI.
• Learn how to design interactive applications with React.
• Develop, test, and deploy applications (both front end and back end) using the FARM stack.

This instructor-led, live training in Bratislava (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 focus is on Python itself, its core libraries, and the selection of the most valuable libraries contributed by the Python community. Python powers businesses globally and is widely used by scientists, making it one of the most popular programming languages.

Instruction utilizes the latest Python 3.x version, complemented by hands-on exercises that leverage its full capabilities. The course is compatible with any operating system, including all UNIX variants (Linux, Mac OS X) and Microsoft Windows.

Practical exercises comprise approximately 70% of the course duration, while demonstrations and presentations make up the remaining 30%. Participants are encouraged to ask questions and engage in discussions throughout the training.

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 Bratislava (online or onsite) is designed for developers looking to master advanced Python programming techniques. The course covers applying 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 eager to master the Python programming language. The curriculum focuses on Python itself, its core libraries, and the selection of the most valuable libraries contributed by the Python community. Python powers businesses globally and is utilized by scientists worldwide, making it one of the most widely adopted programming languages.

This instructor-led, live training in Bratislava 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 Bratislava, participants will master the most relevant and cutting-edge machine learning techniques in Python by building a series of demo applications that utilize image, music, text, and financial data.

Upon completing this training, participants will be able to:

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

This instructor-led, live training in Bratislava (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 methodologies. By leveraging the Python programming language and its extensive ecosystem of libraries, along with numerous hands-on examples, learners will master the essential components of Machine Learning. The curriculum focuses on making informed data modeling decisions, interpreting algorithmic outputs, and validating results effectively.

Our primary objective is to empower you with the confidence to utilize core Machine Learning tools and steer clear of typical pitfalls associated with Data Science applications.

Python has become increasingly popular within the financial sector. Major investment banks and hedge funds have adopted it to develop a diverse array of financial applications, from core trading systems to risk management tools.

During this instructor-led live training, participants will learn how to leverage Python to create practical applications that address specific financial challenges.

By the conclusion of this training, participants will be capable of:

• Gaining a solid understanding of Python programming fundamentals
• Downloading, installing, and managing optimal development tools for building financial applications in Python
• Choosing and applying appropriate Python packages and techniques to organize, visualize, and analyze financial data from various sources (such as CSV, Excel, databases, and web APIs)
• Developing applications that solve issues related to asset allocation, risk analysis, investment performance, and more
• Troubleshooting, integrating, deploying, and optimizing Python applications

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 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.

This course offers a hands-on exploration of Data Science and AI methodologies using Python. It is designed to empower professionals with the essential skills to analyze data, develop machine learning models, and implement AI-powered solutions within business environments. The curriculum spans the CRISP-DM framework, statistical analysis, supervised and unsupervised learning techniques, deep learning with TensorFlow, natural language processing, big data processing with Spark, and the art of data-driven storytelling. It is particularly well-suited for beginners aiming to obtain a Python data science certification and acquire career-ready analytics training.

Applied AI from Scratch in Python empowers programmers and data analysts with the foundational techniques needed to build machine learning solutions from the ground up using Python. The course covers core principles of supervised learning, including classification and regression, as well as unsupervised learning techniques such as clustering and anomaly detection, alongside advanced neural network architectures. It examines proven methods for working with scikit-learn, Apache Spark MLlib, and Jupyter notebooks to facilitate hands-on AI development. This training helps professionals implement practical ML models, evaluate algorithm limitations, and complete applied projects designed for real-world problem solving.

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

This instructor-led live training, available online or onsite, is designed for testers and developers at beginner to intermediate levels 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.
• Create robust test automation scripts using Selenium WebDriver and Pytest.
• Apply the Page Object Model (POM) to build 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 for automation stability.

Course Format

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

Course Customization Options

• For customized training on this course, please contact us to arrange details.

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

Upon completing this training, participants will be capable of:

• Installing and setting up a Python development environment.
• Recognizing the similarities and differences between Matlab and Python syntax.
• Leveraging Python to extract insights from diverse datasets.
• Migrating existing Matlab applications to Python.
• Integrating Matlab and Python applications.

This instructor-led, live training in Bratislava (online or onsite) is aimed at individuals who wish to learn enough Python to begin analyzing data from sales, traffic analytics, customer interactions, and more.

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 analysis.
• Perform basic statistical analysis.
• Generate reports that present data in the appropriate format, from raw numbers to data visualizations.
• Gain valuable insights from data, including performance trends and problematic areas.

This instructor-led, hands-on training course equips participants with advanced Python programming skills. Attendees will explore how to leverage this versatile language to address challenges across various domains, including distributed applications, data analysis and visualization, user interface programming, and the creation of maintenance scripts.

Course Format

• Interactive lectures and group discussions.
• Extensive exercises and practical practice sessions.
• Direct implementation within a live laboratory environment.

Customization Options

• To add, remove, or tailor specific sections or topics of this course, please reach out to us to arrange.

This instructor-led, live training in Bratislava (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 Bratislava (online or onsite) is designed for business analysts who wish to automate trading using algorithmic methods, Python, and R.

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

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

This instructor-led, live training in Bratislava (online or onsite) is designed for beginner to intermediate developers aiming to use Python for building blockchain and cryptocurrency applications.

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

• Utilize Python to create and manipulate blockchain and cryptocurrency systems and data.
• Leverage Python libraries and frameworks such as Flask, PyCrypto, and web3.py to interact with blockchain and cryptocurrency networks and services.
• Implement smart contracts, consensus algorithms, and cryptographic protocols for blockchain and cryptocurrency applications using Python.
• Develop and deploy decentralized applications (DApps) on blockchain and cryptocurrency platforms using Python.
• Perform data analysis and visualization on blockchain and cryptocurrency data using Python.

Course Overview

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

Training Format

• Instructor-led classroom sessions

• Guided practice with expert instruction

• Interactive discussions complemented by real-world case studies

• Daily practical exercises

Course Objectives

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

• Enhance Python proficiency for AI development and data management workflows

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

• Design and refine prompts to ensure reliable and accurate outputs

• Construct comprehensive AI solutions using APIs and relevant frameworks

• Seamlessly integrate AI capabilities into existing data engineering pipelines

This instructor-led, live training in Bratislava (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 Bratislava (online or onsite) is aimed at data scientists who wish 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 Bratislava (online or onsite) is aimed at network engineers who wish to maintain, manage, and design computer networks with 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 live, instructor-led training, available in Bratislava (online or onsite), is designed for business professionals and data analysts with intermediate Python skills who aim to apply Python for automating workflows, analyzing business data, and generating dynamic Excel-based reports.

This instructor-led, live training in Bratislava (online or onsite) is aimed at penetration testers who wish to penetrate test networks in Kali Linux using Python.

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

• Create Python programs to seek network vulnerabilities.
• Explore and use Kali web shells and shellcode in exploits.
• Apply various Kali tools for penetration testing.
• Exploit systems with 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 apply Python to quantitative finance.

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

• Grasp the fundamentals of Python programming
• Utilize Python for financial applications, including the implementation of mathematical techniques, stochastic models, and statistical methods
• Develop financial algorithms using optimized Python code

Audience

• Developers
• Quantitative analysts

Format of the course

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

Computer Vision is a discipline focused on the automatic extraction, analysis, and comprehension of meaningful data from digital media. Python, a high-level programming language, is renowned for its readability and clean syntax.

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

By the conclusion of this course, 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 developers interested in Computer Vision

Course Format

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

This course serves as a follow-up to the one-day introductory session on Python and Data Visualization, which took place on February 11th.

It is tailored for individuals eager to master the Python programming language. The curriculum places strong emphasis on the core syntax of Python, its essential libraries, and the curation of the most valuable tools contributed by the Python community. As a leading programming language, Python is widely adopted by businesses globally and is a preferred choice among scientists worldwide.

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

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