Python Programming Fundamentals Training Course

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 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.

This five-day course provides a comprehensive introduction to Data Science and Artificial Intelligence (AI).

Instruction is delivered through practical examples and hands-on exercises using Python.

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 session Italy (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.

This four-day course provides an introduction to Artificial Intelligence and its practical applications using the Python programming language. Upon completion of this course, participants have the option to dedicate an additional day to working on a dedicated AI project.

This instructor-led, live training in Italy (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 software applications designed to mimic human conversation through chat-based interfaces. They enable organizations to optimize operational efficiency by streamlining user interactions with faster and more accessible solutions.

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

Upon completing this training, participants will be capable of:

• Grasping the core principles of chatbot development
• Creating, testing, deploying, and resolving issues in various types of chatbots utilizing Python

Target Audience

• Software Developers

Course Format

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

Important Note

• For customized training requests regarding this course, please contact us to arrange your schedule.

This instructor-led, live training in Italy (online or onsite) is designed for developers with intermediate skills who want to leverage CUDA to create Python applications capable of parallel execution on NVIDIA GPUs.

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

• Leverage the Numba compiler to speed up Python applications running on NVIDIA GPUs.
• Develop, compile, and execute custom CUDA kernels.
• Handle GPU memory resources effectively.
• Transform CPU-based applications into GPU-accelerated solutions.

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 in Italy (online or on-site) targets 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:

• Configure the environment to begin building big data processing workflows 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 when handling large datasets.

This instructor-led, live training in Italy (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 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, conducted Italy (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 Italy (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.