Process Mining w Python Training Course

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 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.

This is a 5-day introductory course on Data Science and Artificial Intelligence (AI).

The course is delivered with examples and exercises using Python

This instructor-led, live training in Slovakia (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 Slovakia (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.

Insurtech (also known as Digital Insurance) represents the intersection of insurance and emerging technologies. Within the Insurtech landscape, "digital insurers" leverage technological innovations to transform their business and operational models, aiming to lower costs, enhance customer experiences, and increase operational agility.

This instructor-led training helps participants understand the technologies, methodologies, and mindset required to drive digital transformation within their organizations and across the wider industry. The course is designed for managers who need a comprehensive overview, wish to cut through hype and jargon, and are ready to take initial steps toward building an Insurtech strategy.

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

• Discuss Insurtech and its various components with intelligence and systematic clarity
• Identify and clarify the role of each key technology in the Insurtech ecosystem
• Develop a general strategy for implementing Insurtech within their organization

Audience

• Insurance professionals
• Technologists working within the insurance industry
• Stakeholders in the insurance sector
• Consultants and business analysts

Course Format

• A mix of lectures, discussions, exercises, and group case study activities

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 Slovakia (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.

In this instructor-led live training in Slovakia, participants will develop a comprehensive understanding of the technologies, methodologies, and mindset required to successfully implement a Fintech strategy.

This course is designed for managers seeking a high-level grasp of the Fintech landscape, helping them cut through industry hype and jargon while taking concrete first steps toward adopting technologies relevant to financial businesses and services.

Upon completion of this training, participants will be able to

• Present viable Fintech strategies tailored to their organization.
• Understand and articulate the roles and functionalities of key technologies.
• Develop a step-by-step action plan for introducing new technologies.

Insurance in the Digital Era provides an applied overview of how digital transformation reshapes products, operations, and customer engagement in the insurance industry.

This instructor-led, live training (online or onsite) is aimed at intermediate-level insurance professionals who wish to understand and apply digital technologies, data-driven strategies, and innovation frameworks to modernize insurance offerings and operations.

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

• Explain the role of AI, Big Data, IoT, and automation in modern insurance workflows.
• Identify InsurTech trends and how they affect the insurance ecosystem.
• Design customer-centric strategies enabled by digital tools and data insights.
• Apply data-driven approaches to risk management and decision making.
• Develop an innovation and change management approach suitable for insurers.
• Assess real-world case studies and translate lessons into local initiatives.

Format of the Course

• Interactive lecture and discussion.
• Case study analysis and group workshops.
• Practical exercises and action planning for participants’ organizations.

Course Customization Options

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

Requirements Engineering (RE) serves as a pivotal discipline in software and systems development, centered on identifying, documenting, and managing stakeholder needs and constraints to guarantee project success.

This instructor-led live training, available online or onsite, targets intermediate-level professionals aiming to deepen their grasp of practical Requirements Engineering while preparing for the IREB CPRE – Foundation Level certification exam.

After completing this training, participants will be able to:

• Comprehend and apply the core concepts and terminology outlined in the IREB CPRE Foundation syllabus.
• Identify and elicit requirements using effective and context-appropriate techniques.
• Model, document, and validate requirements for real-world projects.
• Manage requirements changes, traceability, and prioritization throughout the project lifecycle.
• Utilize Requirements Engineering tools and best practices to enhance communication and project outcomes.
• Be fully prepared to take and pass the IREB CPRE – Foundation Level certification exam.

Format of the Course

• Interactive lecture and discussion.
• Case-based exercises and collaborative workshops.
• Exam preparation sessions and practice questions.

Course Customization Options

• Additional modules or industry-specific case studies can be added on request.

Model-Based Development (MBD) is a software engineering approach that accelerates and reduces the cost of developing dynamic systems, including control systems, signal processing applications, and communication infrastructure. This methodology prioritizes graphical modeling over conventional text-based coding.

In this instructor-led live training, attendees will discover how to leverage MBD techniques to cut development expenses and speed up the market launch of embedded software solutions.

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

• Choose and implement appropriate tools for MBD implementation.
• Apply MBD to facilitate rapid development during the initial phases of embedded software projects.
• Reduce the time required to release embedded software to the market.

Course Format

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

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

• Set up the necessary environment to start developing Pandas workflows at scale with Modin.
• Understand the features, architecture, and advantages of Modin.
• Know the differences between Modin, Dask, and Ray.
• Perform Pandas operations faster with Modin.
• Implement the entire Pandas API and functions.

This instructor-led live training in Slovakia (online or onsite) is designed for professionals seeking to understand requirements analysis and execute it efficiently and accurately using appropriate analysis techniques for their projects.

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

• Differentiating between various types of requirements.
• Comprehending the core concepts and activities associated with requirements analysis.
• Gaining familiarity with established requirements analysis methodologies.
• Leveraging diverse requirements analysis techniques for optimal results.
• Organizing requirements to facilitate efficient communication with architects and developers through an iterative gathering process.

Through practical, hands-on exercises, this course illustrates the core principles and real-world applications of software engineering, requirements engineering, and testing.