Python Programming Fundamentals Training Course

This intensive, practical course explores advanced Python techniques, engineering best practices, and widely-used design patterns to help you build 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 who aim to adopt professional practices and patterns for production-grade Python systems.

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

• Apply 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.
• Write 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 containers.

Course Format

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

Course Customization Options

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

This course provides practical engineering methodologies for designing, constructing, testing, and deploying autonomous (agentic) systems using Python. It explores the agent lifecycle, tool integrations, memory and state management, orchestration patterns, safety controls, and critical production considerations.

Delivered as an instructor-led, live training session (available online or onsite), this program is tailored for intermediate to advanced ML engineers, AI developers, and software engineers aiming to build robust, production-ready autonomous agents using Python.

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

• Design and implement the agent loop alongside decision-making workflows.
• Integrate external tools and APIs to expand agent capabilities.
• Develop short-term and long-term memory architectures for agents.
• Coordinate multi-step orchestrations and ensure agent composability.
• Apply best practices for safety, access control, and observability in deployed agents.

Course Format

• Interactive lectures and discussions.
• Hands-on labs involving the construction of agents with Python and popular SDKs.
• Project-based exercises that result in deployable prototypes.

Course Customization Options

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

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

The course is delivered with examples and exercises using Python

Artificial Intelligence with Python focuses on building intelligent systems by leveraging Python’s comprehensive ecosystem of AI and machine learning libraries.

This instructor-led live training, available either online or onsite, is designed for intermediate Python programmers who aim to design, implement, and deploy AI solutions using Python.

Upon completion 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.
• Ample exercises and practice.
• 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 in Portugal (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 four-day course provides an introduction to Artificial Intelligence and its practical application using the Python programming language. Participants have the option to extend their learning by adding an extra day dedicated to completing a real-world AI project upon finishing the course.

This instructor-led, live training in Portugal (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 automated programs that mimic human conversation through chat interfaces. They enable organizations to optimize operational efficiency by offering faster and more streamlined user interaction channels.

During this instructor-led live training, participants will acquire the skills necessary to construct chatbots using Python.

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

• Grasp the fundamental principles of chatbot development
• Construct, evaluate, deploy, and resolve issues with various types of chatbots using Python

Audience

• Developers

Course Format

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

Note

• To arrange customized training for this course, please get in touch with us.

This instructor-led, live training in Portugal (online or onsite) is designed for 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.

Course Overview

This practical training is tailored for data engineering professionals seeking to develop hands-on expertise in artificial intelligence, Python, and large language models. Emphasising real-world application, the course covers model utilisation, prompt engineering, and the creation of AI-driven solutions. Participants will progress through structured exercises, advancing from foundational concepts to the development of deployable AI workflows.

Training Format

• In-person classroom-based learning

• Instructor-led sessions featuring guided practice

• Interactive discussions supported by real-world case studies

• Daily practical exercises

Course Objectives

• Grasp core AI and machine learning concepts pertinent to contemporary applications

• Enhance Python proficiency for AI development and data workflows

• Comprehend the mechanics of large language models and effective usage strategies

• Design and refine prompts to ensure consistent and reliable outputs

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

• Integrate AI capabilities into data engineering pipelines

This instructor-led live training, conducted in Portugal (online or onsite), is designed for data scientists and software engineers who wish to utilize 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 Portugal (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, available online or onsite, targets 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 Portugal (available online or onsite) is tailored for developers aiming to use FastAPI with Python to build, test, and deploy RESTful APIs with greater ease and speed.

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

• Set up the required development environment for creating APIs with Python and FastAPI.
• Create APIs more quickly and simply using the FastAPI library.
• Learn how to build data models and schemas based on Pydantic and OpenAPI.
• Connect APIs to a database using SQLAlchemy.
• Implement security and authentication in APIs using FastAPI tools.
• Build container images and deploy web APIs to a cloud server.

This instructor-led, live training in Portugal (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.