Python Training in Bologna

Python serves as the foundational language for developing and orchestrating autonomous AI agents. This course emphasizes practical implementation using contemporary SDKs and frameworks, such as LangChain and AutoGen, to construct, link, and oversee agent workflows.

This instructor-led live training (available online or onsite) is designed for intermediate-level backend engineers, platform engineers, and ML engineers looking to implement and orchestrate autonomous agents utilizing Python tooling and APIs.

Upon completing this training, participants will be able to:

• Set up and configure Python-based environments for agentic systems.
• Leverage popular agent SDKs like 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.

Course Format

• Interactive lectures and discussions.
• Hands-on programming exercises and live demonstrations.
• Practical projects focused on building end-to-end agent workflows.

Course Customization Options

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

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

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

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

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

Course Format

• Interactive lectures and discussions.
• Hands-on labs for building agents using Python and popular SDKs.
• Project-based exercises resulting in deployable prototypes.

Course Customization Options

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

Artificial Intelligence with Python involves creating intelligent systems by leveraging Python's comprehensive ecosystem of AI and machine learning libraries.

This instructor-led live training, available online or onsite, is designed for intermediate-level Python developers who want 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 Bologna (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.

This instructor-led, live training in Bologna (online or onsite) is designed for expert-level data analysts who aim to harness Python's data analysis capabilities within Power BI, thereby improving their effectiveness in analyzing and visualizing data.

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

• Understand how to integrate Python into Power BI for data analysis.
• Employ Python scripts to load, clean, and preprocess data within the Power BI environment.
• Expand data visualization capabilities by developing custom and interactive visualizations using Python.
• Gain advanced data analysis skills through Python.

Python is a highly versatile programming language extensively utilized for data manipulation, automation, and analytics. Libraries such as Pandas and Polars offer robust and practical tools for handling large-scale tabular data.

This instructor-led, live training (available online or onsite) is designed for beginner to intermediate professionals looking to leverage Python for routine data analysis, file processing, and process automation using Pandas and Polars.

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

• Utilize Python to read, transform, and write CSV and Excel files.
• Execute common data cleaning and transformation tasks using Pandas and Polars.
• Automate repetitive data processes through Python scripts.
• Package simple scripts into executables and adhere to project best practices.

Format of the Course

• Interactive coding demonstrations and concise lectures.
• Hands-on exercises supported by guided code examples.
• Practical mini-projects designed to automate real-world tasks.

Course Customization Options

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

This intensive, hands-on course explores advanced Python techniques, engineering best practices, and widely adopted design patterns to help you build maintainable, testable, and high-performance Python applications. It emphasizes modern tooling, type hinting, concurrency models, architectural patterns, and deployment-ready workflows.

Delivered as instructor-led live training (either online or onsite), this program is designed for intermediate to advanced Python developers seeking to adopt professional practices and patterns for production-grade Python systems.

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

• Leverage Python typing, dataclasses, and type-checking to enhance code reliability.
• Utilize design patterns and architectural principles to structure robust applications.
• Correctly implement concurrency and parallelism using asyncio and multiprocessing.
• Develop well-tested code using pytest, property-based testing, and CI pipelines.
• Profile, optimize, and secure Python applications for production environments.
• Package, distribute, and deploy Python projects using modern tools and container technologies.

Course Format

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

Customization Options

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

This instructor-led, live training in Bologna (online or on-site) is tailored for beginner-level developers and data analysts who wish to acquire Python programming skills from scratch using Google Colab.

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

• Understand the basics of Python programming language.
• Implement Python code in Google Colab environment.
• Utilize control structures to manage the flow of a Python program.
• Create functions to organize and reuse code effectively.
• Explore and use basic libraries for Python programming.

This instructor-led live training, offered online or onsite, is tailored for developers aiming to utilize the FARM (FastAPI, React, and MongoDB) stack to construct dynamic, high-performance, and scalable web applications.

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

• Setting up the required development environment that integrates FastAPI, React, and MongoDB.
• Understanding the key concepts, features, and benefits of the FARM stack.
• Learning how to build REST APIs with FastAPI.
• Learning how to design interactive applications with React.
• Developing, testing, and deploying applications (front end and back end) using the FARM stack.

This instructor-led, live training in Bologna (online or onsite) targets beginner to intermediate, and potentially advanced-level robotics developers who wish to learn how to use ROS to program mobile robots using Python.

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

• Configure a development environment comprising ROS, Python, and a mobile robot platform.
• Create and execute ROS nodes, topics, services, and actions using Python.
• Utilize ROS tools and utilities to monitor and debug ROS applications.
• Apply ROS packages and libraries to perform common tasks for mobile robots.
• Integrate ROS with other frameworks and tools.
• Perform troubleshooting and debugging of ROS applications.

This course is tailored for individuals looking to master the Python programming language. It places a strong focus on the Python language itself, its core libraries, and the selection of the most valuable libraries developed by the Python community. Python is widely adopted by businesses and scientists globally, making it one of the most popular programming languages in the world.

The course can be delivered using the latest Python version 3.x, with practical exercises designed to harness its full potential. It is compatible with any operating system, including all UNIX variants (such as Linux and Mac OS X) as well as Microsoft Windows.

Practical exercises make up approximately 70% of the course duration, while the remaining 30% consists of demonstrations and presentations. Participants are encouraged to ask questions and engage in discussions throughout the training.

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

This instructor-led, live training in Bologna (online or onsite) is designed for developers looking to master advanced Python programming techniques, such as applying this versatile language to solve problems in distributed applications, data analysis and visualization, UI programming, and maintenance scripting.

This course caters to individuals eager to master the Python programming language. The focus lies on the Python language itself, its core libraries, and the selection of the most effective and useful libraries cultivated by the Python community. Python is a cornerstone for businesses and is widely utilized by scientists globally, ranking among the most popular programming languages.

This instructor-led, live training in Bologna 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.

During this instructor-led live training in Bologna, participants will master the most relevant and cutting-edge machine learning techniques in Python by developing a series 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 solve complex problems.
• Apply deep learning and semi-supervised learning approaches to applications involving image, music, text, and financial data.
• Maximize the potential of Python algorithms.
• Utilize libraries and packages such as NumPy and Theano.

This instructor-led, live training in Bologna (online or onsite) is designed for intermediate-level Python developers and data analysts looking to enhance their data analysis and manipulation skills using Pandas and NumPy.

Upon completing this training, participants will be able to:

• Set up a development environment comprising Python, Pandas, and NumPy.
• Develop a data analysis application utilizing Pandas and NumPy.
• Execute advanced data wrangling, sorting, and filtering operations.
• Perform 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 develop practical proficiency in applying Machine Learning methods. Leveraging Python and its extensive libraries, along with numerous hands-on examples, participants will learn to utilize the core components of Machine Learning. The curriculum covers making informed data modeling decisions, interpreting algorithm outputs, and validating results.

We strive to equip you with the confidence to master the essential tools in the Machine Learning toolbox, while helping you avoid common pitfalls associated with Data Science applications.

Python has emerged as a dominant programming language within the financial sector. Widely adopted by leading investment banks and hedge funds, it serves as the foundation for numerous financial applications, spanning from core trading systems to advanced risk management platforms.

Through this instructor-led live training, participants will acquire the skills necessary to leverage Python for developing practical solutions to specific finance-related challenges.

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

• Grasping the fundamental concepts of the Python programming language
• Downloading, installing, and managing optimal development tools for building financial applications in Python
• Selecting and applying appropriate Python packages and programming techniques to organize, visualize, and analyze financial data from diverse sources (such as CSV files, Excel spreadsheets, databases, and web APIs)
• Developing applications that address issues related to asset allocation, risk analysis, investment performance, and more
• Troubleshooting, integrating, deploying, and optimizing Python applications

Audience

• Developers
• Analysts
• Quants

Format of the course

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

Note

• This training is designed to offer solutions for key challenges faced by finance professionals. If there is a specific topic, tool, or technique you would like to include or explore in greater depth, please contact us to arrange accordingly.

This course explores practical methodologies for Data Science and AI using Python, equipping professionals with the expertise to analyze data, develop machine learning models, and deploy AI-powered applications within business environments. It covers the CRISP-DM framework, statistical analysis, supervised and unsupervised learning, deep learning with TensorFlow, natural language processing, big data processing with Spark, and data-driven storytelling. It is ideal for beginners looking to obtain a Python data science certification and receive career-focused analytics training.

This course on Applied AI from Scratch in Python provides programmers and data analysts with the essential skills needed to develop machine learning solutions entirely from the ground up using Python. It covers the fundamental concepts of supervised learning (including classification and regression) and unsupervised learning (such as clustering and anomaly detection), alongside an exploration of advanced neural network architectures. Participants will examine effective techniques for leveraging scikit-learn, Apache Spark MLlib, and Jupyter notebooks to facilitate hands-on AI development. The curriculum supports professionals in implementing practical machine learning models, assessing the constraints of various algorithms, and completing applied projects designed to solve real-world challenges.

Selenium is an open-source framework designed for automating web application testing across various browsers. With the release of Selenium 4, users gain access to enhanced WebDriver APIs, native relative locators, and improved grid support. Python complements these capabilities with its simplicity and robust integration with testing frameworks such as Pytest, making it an excellent choice for building scalable and maintainable test automation suites.

This instructor-led live training, available either online or onsite, targets beginner to intermediate testers and developers who aim to leverage Selenium with Python to automate web application testing in real-world scenarios.

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

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

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical 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 Bologna (online or onsite) is aimed at Matlab users who wish to explore or 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 Bologna (online or on-site) is aimed at individuals who wish to learn enough Python to begin analyzing data from sales, traffic analytics, customer interactions, and more.

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

• Install and configure the necessary software, libraries, and development environment to start writing Python code for data analysis.
• Analyze data from sources such as Excel, CSV, JSON files, and databases.
• Clean data to improve its usefulness prior to analysis.
• Perform basic statistical analysis.
• Generate reports that present data in the appropriate format, from raw numbers to data visualizations.
• Gain valuable insights from data, including performance trends and problematic areas.

This instructor-led, live training session Bologna (online or onsite) is tailored for business analysts who wish to automate trading processes using algorithmic trading, Python, and R.

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

• Utilize algorithms to rapidly buy and sell securities at specialized intervals.
• Lower transaction costs associated with trading through the use of algorithmic strategies.
• Automatically track stock prices and execute trades accordingly.

Course Overview

This practical training is tailored for professionals with a data engineering background who aim to develop tangible skills in artificial intelligence, Python, and large language models (LLMs). The curriculum emphasizes real-world applications, addressing model utilization, prompt engineering, and the creation of AI-driven solutions. Participants will engage in progressive exercises that advance from foundational concepts to the construction of deployable AI workflows.

Training Format

• Classroom-based in-person training

• Instructor-led sessions featuring guided practice

• Interactive discussions and analysis of real-world case studies

• Daily hands-on exercises

Course Objectives

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

• Enhance Python capabilities for AI development and data workflows

• Comprehend the mechanics of large language models and utilize them effectively

• Design and refine prompts to ensure reliable outputs

• Develop end-to-end AI solutions leveraging APIs and frameworks

• Integrate AI functionalities into data engineering pipelines

This instructor-led live training, conducted Bologna (online or onsite), is designed for developers aiming to utilize FastAPI with Python to build, test, and deploy RESTful APIs with greater speed and ease.

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

• Set up the necessary development environment to create APIs using Python and FastAPI.
• Develop APIs more quickly and simply using the FastAPI library.
• Understand how to create data models and schemas based on Pydantic and OpenAPI.
• Connect APIs to a database using SQLAlchemy.
• Implement security and authentication features in APIs using FastAPI tools.
• Create container images and deploy web APIs to cloud servers.

This instructor-led, live training in Bologna (online or onsite) is tailored for data scientists who want to use TensorFlow to analyze 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 analyzing fraud data.

This instructor-led, live training in Bologna (online or onsite) is tailored for 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 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 instructor-led, live training in Bologna (online or on-site) 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.

This instructor-led, live training in Bologna (online or onsite) is aimed at penetration testers who wish to penetrate test networks in Kali Linux using Python.

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

• Create Python programs to seek network vulnerabilities.
• Explore and use Kali web shells and shellcode in exploits.
• Apply various Kali tools for penetration testing.
• Exploit systems with Python.

This instructor-led, live training (available online or onsite) is designed for advanced-level users.

Course Format

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

Options for Customizing the Course

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

Computer Vision is a discipline focused on the automatic extraction, analysis, and interpretation of valuable insights from digital media. Python, renowned for its clean syntax and readability, serves as an ideal high-level programming language for this purpose.

In this instructor-led live training, participants will explore the fundamentals of Computer Vision while guiding them through the development of a series of simple Computer Vision applications using Python.

Upon completing this training, participants will be able to:

• Grasp the core concepts of Computer Vision
• Apply Python to execute Computer Vision tasks
• Develop custom systems for face, object, and motion detection

Audience

• Python programmers looking to enter the field of Computer Vision

Course Format

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

This practical course is tailored for Unix and shell users aiming to boost their automation skills through the use of Python. Although shell scripting remains effective for straightforward tasks, Python offers superior flexibility, readability, and scalability, making it ideal for complex automation, system administration, and DevOps workflows.

Tableau is a business intelligence and data visualization tool. Python is a widely used programming language which provides support for a wide variety of statistical and machine learning techniques. Tableau's data visualization power and Python's machine learning capabilities, when combined, help developers rapidly build advanced data analytics applications for various business use cases.

In this instructor-led, live training, participants will learn how to combine Tableau and Python to carry out advanced analytics. Integration of Tableau and Python will be done via the TabPy API.

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

• Integrate Tableau and Python using TabPy API
• Use the integration of Tableau and Python to analyze complex business scenarios with few lines of Python code

Audience

• Developers
• Data scientists

Format of the course

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