Process Mining w Python Training Course

This intensive, hands-on course covers advanced Python techniques, engineering best practices, and commonly used design patterns to build maintainable, testable, and high-performance Python applications. It emphasizes modern tooling, typing, concurrency models, architecture patterns, and deployment-ready workflows.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level Python developers who wish to adopt professional practices and patterns for production-grade Python systems.

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

• Apply Python typing, dataclasses, and type-checking to increase code reliability.
• Use design patterns and architecture principles to structure robust applications.
• Implement concurrency and parallelism correctly using asyncio and multiprocessing.
• Build well-tested code with pytest, property-based testing, and CI pipelines.
• Profile, optimize, and harden Python applications for production.
• Package, distribute, and deploy Python projects using modern tools and containers.

Format of the Course

• Interactive lectures and short demos.
• Hands-on labs and coding exercises each day.
• Capstone mini-project integrating patterns, testing, and deployment.

Course Customization Options

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

This course teaches practical engineering techniques to design, build, test, and deploy agentic (autonomous) systems using Python. It covers the agent loop, tool integrations, memory and state management, orchestration patterns, safety controls, and production considerations.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level ML engineers, AI developers, and software engineers who wish to build robust, production-ready autonomous agents using Python.

By the end 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.

Format of the Course

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

Course Customization Options

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

This is a 5 day introduction to Data Science and Artificial Intelligence (AI).

The course is delivered with examples and exercises using Python

This instructor-led, live training in Qatar (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 Qatar (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 (a.k.a Digital Insurance) refers to the convergence of insurance + new technologies. In the field of Insurtech "digital insurers" apply technology innovations to their business and operating models in order to reduce costs, improve the customer experience and enhance the agility of their operations.

In this instructor-led training, participants will gain an understanding of the technologies, methods and mindset needed to bring about a digital transformation within their organizations and in the industry at large. The training is aimed at managers who need to gain a big picture understanding, break down the hype and jargon, and take the first steps in establishing an Insurtech strategy.

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

• Discuss Insurtech and all its component parts intelligently and systematically
• Identify and demystify the role of each key technology within Insurtech.
• Draft a general strategy for implementing Insurtech within their organization

Audience

• Insurers
• Technologists within the insurance industry
• Insurance stakeholders
• Consultants and business analysts

Format of the course

• Part lecture, part discussion, exercises and case study group activities

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 Qatar (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 Qatar, participants will gain an understanding of the technologies, methods and mindset needed to implement a Fintech strategy.

This training is aimed at managers who need to gain a "big picture" understanding of Fintech, break down the hype and jargon, and take tangible first steps towards the adoption of new technologies applicable to financial business and services.

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

• Present viable Fintech strategies for their organization.
• Understand and explain the role and functionality of key technologies.
• Draft an action plan for introducing new technologies in step-by-step fashion.

Insurance in the Digital Era is 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) is a key discipline within software and systems development, focused on identifying, documenting, and managing the needs and constraints of stakeholders to ensure project success.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to deepen their understanding of practical Requirements Engineering while preparing for the IREB CPRE – Foundation Level certification exam.

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

• Understand and apply the key concepts and terminology defined by 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.
• Use 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 development methodology that enables faster, more cost-effective development of dynamic systems such as control systems, signal processing and communication systems. It relies on graphic modeling rather than the traditional text based programming.

In this instructor-led, live training participants will learn how to apply MBD methodologies to reduce development costs and accelerate the time to market of their embedded software products.

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

• Select and utilize the right tools for implementing MBD.
• Use MBD to carry out rapid development in the early stages of their embedded software project.
• Shorten the release of their embedded software into the market.

Format of the course

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

This instructor-led, live training in Qatar (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 Qatar (online or onsite) is aimed at persons who wish to understand requirements analysis and conduct requirements analysis efficiently and accurately using analysis techniques for their projects.

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

• identify different types of requirements.
• understand the overall concepts of, and activities within, requirements analysis.
• be familiar with the requirements analysis methodology.
• use different requirements analysis techniques to their advantage.
• structure requirements in order to communicate efficiently with architects and developers through an iterative requirement gathering process.

This course demonstrates through hands-on practice the fundamentals and applications of software engineering, requirements engineering and testing.