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.

Explores practical methodologies for Data Science and Artificial Intelligence (AI) using Python. This course empowers professionals with the expertise to analyse data, develop machine learning models, and implement AI-driven solutions within business environments. Topics include CRISP-DM workflows, statistical analysis, supervised and unsupervised learning, deep learning with TensorFlow, natural language processing, big data processing with Spark, and data-driven storytelling. It is particularly suitable for beginners looking to obtain a Python data science certification and gain career-focused analytics training.

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.

Applied AI from Scratch in Python empowers programmers and data analysts with the essential techniques required to build machine learning solutions from the ground up using Python. The course covers the core principles of supervised learning (classification and regression), unsupervised learning (clustering and anomaly detection), and advanced neural network architectures. It examines proven methodologies for utilizing scikit-learn, Apache Spark MLlib, and Jupyter notebooks to facilitate hands-on AI development. Participants will learn to implement practical ML models, assess algorithm limitations, and complete applied projects designed for real-world problem-solving.

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.

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 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 designed for data scientists who wish to utilise TensorFlow to analyse 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 analysing fraud data.

This course is designed to equip participants with practical proficiency in applying Machine Learning techniques. By leveraging the Python programming language and its extensive library ecosystem, and through numerous hands-on examples, the curriculum covers the essential components of Machine Learning. Participants will learn to make informed data modelling decisions, interpret algorithmic outputs, and validate results effectively.

Our objective is to empower you with the confidence to utilise the core tools of the Machine Learning toolkit while avoiding the common pitfalls associated with Data Science applications.

This instructor-led live training in Portugal (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 utilize Paramiko, Netmiko, Napalm, Telnet, and pyntc for network automation with Python.
• Master multi-threading and multiprocessing techniques in network automation.
• Apply GNS3 and Python for network programming.

This instructor-led, live training in Portugal (online or onsite) is aimed at business professionals and data analysts with intermediate Python skills who wish to apply Python to automate workflows, analyze business data, and generate dynamic Excel-based reports.

In this instructor-led, live training in Portugal, attendees will master the most pertinent and state-of-the-art machine learning techniques in Python while developing a range of demo applications that handle image, music, text, and financial data.

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

• Implement machine learning algorithms and techniques to address 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.