Python Security 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

Artificial Intelligence with Python is the development of intelligent systems using Python’s extensive ecosystem of AI and machine learning libraries.

This instructor-led, live training (online or onsite) is aimed at intermediate-level Python programmers who wish 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.
• Lots of 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 Denmark (online or onsite) is aimed at business analysts who wish to automate trade with algorithmic trading, Python, and R.

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

• Employ algorithms to buy and sell securities at specialized increments rapidly.
• Reduce costs associated with trade using algorithmic trading.
• Automatically monitor stock prices and place trades.

This is a 4 day course introducing AI and it's application using the Python programming language. There is an option to have an additional day to undertake an AI project on completion of this course. 

This instructor-led, live training in Denmark (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.

ChatBots are computer programs that automatically simulate human responses via chat interfaces. ChatBots help organizations maximize their operations efficiency by providing easier and faster options for their user interactions.

In this instructor-led, live training, participants will learn how to build chatbots in Python.

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

• Understand the fundamentals of building chatbots
• Build, test, deploy, and troubleshoot various chatbots using Python

Audience

• Developers

Format of the course

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

Note

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

This instructor-led, live training in Denmark (online or onsite) is aimed at intermediate-level developers who wish to use CUDA to build Python applications that run in parallel on NVIDIA GPUs.

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

• Use the Numba compiler to accelerate Python applications running on NVIDIA GPUs.
• Create, compile and launch custom CUDA kernels.
• Manage GPU memory.
• Convert a CPU based application into a GPU-accelerated application.

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

In this instructor-led, live training in Denmark (onsite or remote), participants will learn how to use Python skope-rules to automatically generate rules based on existing data sets.

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

• Use skope-rules to extract rules from available data.
• Apply skope-rules to carry out classification, particularly useful in supervised anomaly detection, or imbalanced classification. 
• Generate rules for classifying new incoming data.
• Fit rules to address real-world problems in fraud detection, predictive maintenance, intrusion detection, insurance application approvals, etc.