Advanced Python - 1 Day Training Course

This intensive, hands-on course covers advanced Python techniques, engineering best practices, and commonly used design patterns to build maintainable, testable, and high-performance Python applications. It emphasizes modern tooling, typing, concurrency models, architecture patterns, and deployment-ready workflows.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level Python developers who wish 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 increase code reliability.
• Use design patterns and architecture 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.

Format of the Course

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

Course Customization Options

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

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

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level ML engineers, AI developers, and software engineers who wish to build robust, production-ready autonomous agents using Python.

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

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

Course Format

• 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.

This is a 5-day introduction to Data Science and Artificial Intelligence (AI).

The course is delivered with examples and exercises using Python

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

This instructor-led live training, available either online or on-site, is designed for intermediate-level Python developers who aim to design, implement, and deploy AI solutions using Python.

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

• Implementing AI algorithms using Python’s core AI libraries.
• Working with supervised, unsupervised, and reinforcement learning models.
• Integrating AI solutions into existing applications and workflows.
• Evaluating model performance and optimizing 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 Romania (online or onsite) is designed for business analysts who wish to automate trading using algorithmic strategies, Python, and R.

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

• Use algorithms to rapidly buy and sell securities at specialized intervals.
• Reduce costs associated with trading through algorithmic trading.
• Automatically monitor stock prices and execute trades.

This intensive 4-day program provides a comprehensive introduction to Artificial Intelligence and its practical application using Python. Upon completion, participants may choose to extend the course by one additional day to undertake a dedicated AI project.

This instructor-led, live training in Romania (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 computer programs designed to simulate human conversation through chat interfaces. By offering quicker and more convenient interaction options, they enable organizations to enhance operational efficiency.

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

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

• Grasp the core principles of chatbot development
• Create, evaluate, deploy, and troubleshoot diverse chatbot applications using Python

Target Audience

• Software Developers

Course Format

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

Note

• For customized training arrangements, please contact us directly.

This instructor-led, live training in Romania (online or onsite) is aimed at intermediate-level developers who wish to use CUDA to build Python applications that run in parallel on NVIDIA GPUs.

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

• Use the Numba compiler to accelerate Python applications running on NVIDIA GPUs.
• Create, compile and launch custom CUDA kernels.
• Manage GPU memory.
• Convert a CPU based application into a GPU-accelerated application.

Course Overview

This practical training program is tailored for data engineering professionals seeking to develop applied skills in artificial intelligence, Python programming, and large language models. The curriculum emphasizes real-world application, addressing model integration, prompt engineering, and the creation of AI-driven solutions. Through a series of progressive exercises, participants will advance from foundational principles to constructing deployable AI workflows.

Training Format

• On-site classroom instruction

• Instructor-led sessions accompanied by 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 concepts applicable to contemporary solutions

• Enhance Python proficiency for AI development and data workflow management

• Comprehend the mechanics of large language models and learn effective utilization strategies

• Design and optimize prompts to ensure consistent and reliable outputs

• Develop complete AI solutions utilizing APIs and frameworks

• Seamlessly integrate AI capabilities into data engineering pipelines

This instructor-led live training, delivered Romania (online or onsite), is designed for data scientists and software engineers who aim to utilize Dask within the Python ecosystem to build, scale, and analyze large datasets.

Upon completing this training, participants will be capable of:

• Configuring the environment necessary to begin building big data processing workflows with Dask and Python.
• Exploring the features, libraries, tools, and APIs offered by Dask.
• Gaining insight into how Dask accelerates parallel computing capabilities in Python.
• Learning techniques to scale the Python ecosystem (including NumPy, SciPy, and Pandas) using Dask.
• Optimizing the Dask environment to ensure high performance when managing large datasets.

This instructor-led, live training in Romania (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, offered online or onsite, targets developers who want to use the FARM stack (FastAPI, React, and MongoDB) to build dynamic, high-performance, and scalable web applications.

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

• Set up a 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 Romania (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 Romania (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.