Python Training in Delft

Python serves as the foundational language for developing and orchestrating autonomous AI agents. This course concentrates on practical implementation, leveraging modern SDKs and frameworks such as LangChain and AutoGen to construct, link, and manage agent workflows.

This instructor-led live training (available online or onsite) targets intermediate-level backend, platform, and ML engineers who aim to implement and orchestrate autonomous agents using Python tools and APIs.

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

• Set up and configure Python-based environments for agentic systems.
• Utilize prominent agent SDKs, including LangChain and AutoGen, to develop functional agents.
• Integrate tools and APIs to expand agent capabilities.
• Orchestrate multi-agent workflows and communication patterns.
• Apply best practices for debugging, testing, and maintaining agentic codebases.

Format of the Course

• Interactive lectures and discussions.
• Hands-on programming exercises and live demonstrations.
• Practical projects involving end-to-end agent workflow development.

Course Customization Options

• For a customized training session, please contact us to arrange.

This course imparts practical engineering techniques for designing, building, testing, and deploying agentic (autonomous) systems using Python. Key topics include the agent loop, tool integrations, memory and state management, orchestration patterns, safety controls, and production considerations.

Delivered as instructor-led live training (available online or onsite), this program is tailored for intermediate to advanced ML engineers, AI developers, and software engineers who aim to construct 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 extend agent capabilities.
• Implementing short-term and long-term memory architectures for agents.
• Coordinating multi-step orchestrations and agent composability.
• Applying 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.

Artificial Intelligence with Python involves 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-level Python programmers who want to design, implement, and deploy AI solutions using Python.

Upon completing this training, participants will be able to:

• Implement AI algorithms utilizing 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, held Delft (online or onsite), is designed for intermediate-level Python developers seeking to enhance their development capabilities using AWS Cloud9.

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

• Set up and configure AWS Cloud9 for Python development.
• Navigate the AWS Cloud9 IDE interface and utilize its key features.
• Write, debug, and deploy Python applications directly within AWS Cloud9.
• Collaborate effectively with other developers via the AWS Cloud9 platform.
• Integrate AWS Cloud9 with additional AWS services to facilitate advanced deployments.

This instructor-led, live training in Delft (online or on-site) is aimed at expert-level data analysts who wish to leverage Python's data analysis capabilities within Power BI, enhancing their ability to analyze and visualize data effectively.

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

• Learn how Python can be integrated into Power BI for data analysis.
• Use Python scripts to load, clean, and preprocess data within the Power BI environment.
• Enhance data visualization capabilities by creating custom and interactive visualizations using Python.
• Acquire advanced data analysis skills using Python.

Python is a versatile programming language widely used for data manipulation, automation, and analytics. Libraries like Pandas and Polars provide powerful, practical tools for working with tabular data at scale.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level professionals who wish to apply Python for everyday data analysis, file processing, and process automation using Pandas and Polars.

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

• Use Python to read, transform, and write CSV and Excel files.
• Perform common data cleaning and transformation tasks with Pandas and Polars.
• Automate repetitive data processes with Python scripts.
• Package simple scripts into executables and follow best practices for projects.

Format of the Course

• Interactive coding demonstrations and short lectures.
• Hands-on exercises with guided code examples.
• Practical mini-projects to automate real-world tasks.

Course Customization Options

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

This intensive, hands-on course explores advanced Python techniques, engineering best practices, and widely used design patterns to help you build maintainable, testable, and high-performance Python applications. It 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 want 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 enhance code reliability.
• Utilize design patterns and architectural 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.

Course Format

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

Customization Options

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

This instructor-led, live training in Delft (online or onsite) is aimed at beginner-level developers and data analysts who wish to learn Python programming from scratch using Google Colab.

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

• Grasp the core concepts of the Python programming language.
• Write and implement Python code within the Google Colab environment.
• Apply control structures to effectively manage the flow of a Python program.
• Develop functions to organize and reuse code efficiently.
• Explore and utilize fundamental libraries essential for Python programming.

This instructor-led, live training (online or onsite) is designed for 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 Delft (online or on-site) is designed for robotics developers at beginner, intermediate, and potentially advanced levels who wish to learn how to program mobile robots using ROS and Python.

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

• Set up a development environment that includes ROS, Python, and a mobile robot platform.
• Create and run ROS nodes, topics, services, and actions using Python.
• Use ROS tools and utilities to monitor and debug ROS applications.
• Use ROS packages and libraries to perform common tasks for mobile robots.
• Integrate ROS with other frameworks and tools.
• Troubleshoot and debug ROS applications.

This course is tailored for individuals eager to master the Python programming language. The focus lies on understanding Python itself, its essential libraries, and identifying the most valuable resources developed by the vibrant Python community. Python is a cornerstone for businesses globally and is extensively utilized by scientists worldwide, making it one of the most popular programming languages in use today.

The training utilizes the latest Python 3.x version, featuring hands-on exercises that fully leverage its capabilities. It supports delivery across all major operating systems, including various UNIX distributions (such as Linux and Mac OS X) as well as Microsoft Windows.

Approximately 70% of the course time is dedicated to practical exercises, while the remaining 30% consists of demonstrations and presentations. Participants are encouraged to engage in discussions and ask questions throughout the session.

Note: The curriculum can be customized to meet specific requirements upon prior request before the scheduled course date.

This instructor-led, live training in Delft (online or onsite) targets developers keen on mastering advanced Python programming techniques. It covers how to leverage this versatile language to tackle challenges in domains such as distributed applications, data analysis and visualization, UI development, and maintenance scripting.

This course is tailored for individuals aiming to master the Python programming language. The focus lies on Python itself, its core libraries, and the selection of the most valuable resources developed by the Python community. Widely regarded as one of the most popular programming languages, Python powers businesses globally and is extensively used by scientists around the world.

This instructor-led, live training in Delft is based on the popular book, "Automate the Boring Stuff with Python", by Al Sweigart. It is aimed at beginners and covers essential Python programming concepts through practical, hands-on exercises and discussions. The focus is on learning to write code to dramatically increase office productivity.

By the end of this training, participants will know how to program in Python and apply this new skill for:

• Automating tasks by writing simple Python programs.
• Writing programs that can do text pattern recognition with "regular expressions".
• Programmatically generating and updating Excel spreadsheets.
• Parsing PDFs and Word documents.
• Crawling web sites and pulling information from online sources.
• Writing programs that send out email notifications.
• Use Python's debugging tools to quickly resolve bugs.
• Programmatically controlling the mouse and keyboard to click and type for you.

In this instructor-led, live training in Delft, participants will acquire the most relevant and cutting-edge machine learning techniques in Python while developing a series of demo applications that utilize image, music, text, and financial data.

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

• Implementing machine learning algorithms and techniques to solve complex problems.
• Applying deep learning and semi-supervised learning to applications involving image, music, text, and financial data.
• Maximizing the potential of Python algorithms.
• Utilizing libraries and packages such as NumPy and Theano.

This instructor-led, live training in Delft (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 course aims to build general proficiency in applying Machine Learning methods in real-world scenarios. By leveraging the Python programming language and its extensive library ecosystem, along with a wide range of practical examples, this course teaches you how to utilize the core components of Machine Learning. You will learn to make informed data modeling decisions, interpret algorithm outputs, and validate results effectively.

Our objective is to equip you with the confidence to understand and apply the most fundamental tools in the Machine Learning toolbox, while helping you avoid common pitfalls associated with Data Science applications.

Python has become immensely popular within the financial sector. Utilized by major investment banks and hedge funds, it is employed to construct a diverse array of financial applications, ranging from core trading systems to risk management frameworks.

In this instructor-led live training, participants will learn how to leverage Python to develop practical solutions for various specific finance-related challenges.

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

• Grasp the fundamentals of the Python programming language
• Download, install, and maintain the optimal development tools for creating financial applications in Python
• Select and employ the most appropriate Python packages and techniques to organize, visualize, and analyze financial data from multiple sources (CSV, Excel, databases, web, etc.)
• Construct applications that address issues related to asset allocation, risk analysis, investment performance, and more
• Troubleshoot, integrate, deploy, and optimize a Python application

Audience

• Developers
• Analysts
• Quants

Format of the course

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

Note

• This training focuses on providing solutions for key problems encountered by finance professionals. If you have a specific topic, tool, or technique you wish to add or expand upon, please contact us to arrange this.

This course explores practical methodologies for Data Science and AI via Python, empowering professionals with the expertise to analyze data, construct machine learning models, and implement AI-driven applications within business settings. It encompasses CRISP-DM workflows, statistical analysis, supervised and unsupervised learning, deep learning with TensorFlow, natural language processing, big data technologies using Spark, and data-driven storytelling. This program is ideal for beginners aiming to obtain a Python data science certification and receive career-focused analytics training.

Applied AI from Scratch in Python provides programmers and data analysts with the foundational techniques needed to build machine learning solutions from the ground up using Python. The course covers core principles of supervised learning (classification and regression), unsupervised learning (clustering and anomaly detection), and advanced neural network architectures. It examines proven methods for working with scikit-learn, Apache Spark MLlib, and Jupyter notebooks to facilitate hands-on AI development. This training helps professionals implement practical ML models, evaluate algorithm limitations, and complete applied projects aimed at solving real-world problems.

Selenium is an open-source framework designed for automating web application testing across various browsers. With the release of Selenium 4, users can benefit from enhanced WebDriver APIs, native relative locators, and improved grid support. Python stands out as a powerful choice for creating scalable and maintainable test automation suites due to its simplicity and robust integration with testing frameworks like Pytest.

This instructor-led live training, available both online and onsite, targets testers and developers at beginner to intermediate levels who aim to leverage Selenium with Python for automating web application tests in real-world scenarios.

Upon completing this training, participants will be able to:

• n Install and configure Selenium with Python within a test environment.
• Develop robust test automation scripts using Selenium WebDriver alongside Pytest.
• Utilize the Page Object Model (POM) to create maintainable test frameworks.
• Execute tests across multiple browsers via Selenium Grid.
• Integrate automated tests into CI/CD pipelines.
• Troubleshoot common issues and apply best practices to ensure automation stability.

Format of the Course

• Interactive lectures and discussions.
• Numerous exercises and practical sessions.
• Hands-on implementation within a live-lab environment.

Course Customization Options

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

This instructor-led, live training in Delft (online or on-site) is aimed at Matlab users who wish to explore and transition to Python for data analytics and visualization.

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

• Install and configure a Python development environment.
• Understand the differences and similarities between Matlab and Python syntax.
• Use Python to obtain insights from various datasets.
• Convert existing Matlab applications to Python.
• Integrate Matlab and Python applications.

This instructor-led, live training in Delft (online or onsite) is aimed at persons who wish to learn just enough Python to begin crunching numbers from sales data, traffic analytics, customer interactions, etc..

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

• Install and configure the necessary software, libraries and development environment to begin writing Python code for data analysis.
• Analyze data from sources such as Excel, CSV, JSON files and databases.
• Clean data to improve its usefulness before analyzing it.
• Perform simple statistical analysis.
• Generate reports that present the desired data in just the right format, from straight numbers to data visualizations.
• Gain valuable insight from data, including trends in performance, problematic areas.

Course Overview

This practical training is tailored for data engineering professionals aiming to develop hands-on expertise in artificial intelligence, Python, and large language models. The program emphasizes real-world applications, including the utilization of models, prompt engineering, and the creation of AI-driven solutions. Participants will engage in progressive exercises that transition from foundational concepts to the development of deployable AI workflows.

Training Format

• In-person classroom instruction

• Instructor-led sessions featuring guided practice

• Interactive discussions and real-world case studies

• Daily hands-on 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 learn to utilize them effectively

• Design and optimize prompts to ensure reliable outputs

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

• Integrate AI capabilities into data engineering pipelines

This instructor-led live training, located in Delft (online or onsite), targets developers seeking to utilize FastAPI alongside 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 developing APIs with Python and FastAPI.
• Create APIs more quickly and easily 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 Delft (online or onsite) is intended for data scientists aiming to utilize TensorFlow for the analysis of potential fraud data.

By the conclusion of this training, participants will be capable of:

• Creating a fraud detection model using Python and TensorFlow.
• Building linear regressions and linear regression models to predict fraud.
• Developing an end-to-end AI application for analyzing fraud data.

This instructor-led live training in Delft (online or onsite) targets network engineers who wish to maintain, manage, and design computer networks using Python.

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

• Optimize and leverage Paramiko, Netmiko, Napalm, Telnet, and pyntc for network automation with Python.
• Master multi-threading and multiprocessing in network automation.
• Use GNS3 and Python for network programming.

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

Computer Vision enables the automatic extraction, analysis, and interpretation of meaningful data from digital media. Python is a high-level programming language renowned for its clear syntax and code readability.

In this instructor-led live training, participants will grasp the fundamentals of Computer Vision by building a series of simple Computer Vision applications using Python.

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

• Understand the basics of Computer Vision
• Use Python to implement Computer Vision tasks
• Build their own face, object, and motion detection systems

Audience

• Python programmers interested in Computer Vision

Format of the course

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

This practical training is tailored for professionals experienced with Unix and shell environments who wish to elevate their automation skills through Python. Although shell scripting remains effective for straightforward tasks, Python offers vastly superior flexibility, code clarity, and scalability for managing complex automation, system administration, and DevOps processes.