Web Scraping with Python Training Course

This immersive, practical course delves into advanced Python techniques, engineering best practices, and widely adopted design patterns to help you build maintainable, testable, and high-performance Python applications. The curriculum emphasizes modern tooling, type hinting, concurrency models, architectural patterns, and deployment-ready workflows.

Delivered as an instructor-led live training (available online or onsite), this programme is tailored 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:

• 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 harden Python applications for production environments.
• Package, distribute, and deploy Python projects using modern tools and containers.

Format of the Course

• Interactive lectures and concise 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 areas (data, web, or infrastructure), please contact us to arrange.

This course delivers practical engineering strategies for designing, constructing, evaluating, and deploying agentic (autonomous) systems using Python. Key topics include the agent loop, tool integration, memory and state management, orchestration patterns, safety controls, and essential production considerations.

Delivered as instructor-led live training (either online or onsite), this program targets intermediate to advanced ML engineers, AI developers, and software engineers who aim to build robust, production-ready autonomous agents using Python.

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

• Design and implement the core 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 ensure agent composability.
• Apply best practices for safety, access control, and observability in deployed agents.

Course Format

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

Customization Options

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

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

The training is delivered through practical examples and exercises utilizing Python.

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 online or onsite) is designed for intermediate-level Python programmers 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.
• Extensive 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 Greece (available online or onsite) is tailored for business analysts seeking to automate trading using algorithmic strategies, Python, and R.

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

• Utilize algorithms to rapidly buy and sell securities at specific, specialized increments.
• Lower costs associated with trading through the application of algorithmic methods.
• Automatically monitor stock prices and execute trades.

This comprehensive four-day course provides an introduction to Artificial Intelligence and its practical implementation using the Python programming language. Upon successful completion, participants have the option to extend their learning with an additional day dedicated to executing a real-world AI project.

This instructor-led, live training in Greece (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. These tools enable organizations to optimize operational efficiency by offering streamlined and rapid user engagement options.

This instructor-led live training equips participants with the skills necessary to construct chatbots using Python.

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

• Grasping the core principles of chatbot development
• Constructing, testing, deploying, and troubleshooting a variety of chatbots via Python

Target Audience

• Software Developers

Course Format

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

Important Note

• For tailored training solutions, please reach out to us for arrangement.

This instructor-led live training Greece (online or on-site) is targeted at intermediate-level developers wishing to use CUDA to construct Python applications that execute in parallel on NVIDIA GPUs.

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

• Utilize the Numba compiler to speed up Python applications on NVIDIA GPUs.
• Create, compile, and launch custom CUDA kernels.
• Manage GPU memory.
• Convert CPU-based applications into GPU-accelerated solutions.

Course Overview

This practical training programme is tailored for data engineering professionals looking to develop concrete competencies in artificial intelligence, Python, and large language models. Emphasizing real-world application, the curriculum covers model utilization, prompt engineering, and the creation of AI-driven solutions. Participants will engage in a series of progressive exercises, advancing from foundational concepts to the construction of deployable AI workflows.

Training Format

• Face-to-face classroom instruction

• Instructor-led sessions featuring guided practice

• Interactive discussions and analysis of real-world case studies

• Daily practical exercises

Course Objectives

• Gain a solid understanding of core AI and machine learning principles applicable to contemporary solutions

• Enhance Python proficiency for AI development and data processing workflows

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

• Craft and refine prompts to ensure consistent and reliable outputs

• Develop comprehensive AI solutions leveraging APIs and frameworks

• Seamlessly integrate AI capabilities into data engineering pipelines

This instructor-led, live training in Greece (online or onsite) is aimed at 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:

• 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 Greece (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 (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 Greece (online or onsite) is aimed at developers who wish to use FastAPI with Python to build, test, and deploy RESTful APIs easier and faster.

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

• Set up the necessary development environment to develop APIs with Python and FastAPI.
• Create APIs quicker and easier 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 Greece (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.