Python Advanced Training Course

This intensive, practical course delves into advanced Python techniques, engineering standards, and widely used 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 workflows ready for production deployment.

This instructor-led live training, available online or onsite, is designed 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:

• Utilize Python typing, dataclasses, and type-checking to enhance code reliability.
• Leverage design patterns and architectural principles to structure robust applications.
• Correctly implement concurrency and parallelism using asyncio and multiprocessing.
• Create well-tested code employing 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 brief demonstrations.
• Hands-on labs and coding exercises every day.
• A capstone mini-project that integrates patterns, testing, and deployment.

Course Customization Options

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

This course provides practical engineering methodologies for designing, building, testing, and deploying autonomous (agentic) systems using Python. It explores key topics such as the agent loop, tool integrations, memory and state management, orchestration patterns, safety mechanisms, and considerations for production environments.

Offered as an instructor-led live training session (available online or on-site), this program is designed for intermediate to advanced ML engineers, AI developers, and software engineers seeking to construct robust, production-grade autonomous agents using Python.

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

• Designing and implementing agent loops and decision-making workflows.
• Integrating external tools and APIs to enhance agent functionalities.
• Developing short-term and long-term memory structures for agents.
• Coordinating multi-step orchestrations and ensuring agent composability.
• Applying best practices for safety, access control, and observability in deployed agents.

Course Format

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

Customization Options

• To request a customized training version of this course, please contact us to make arrangements.

This five-day program serves as a comprehensive introduction to Data Science and Artificial Intelligence (AI).

The course is taught through practical examples and hands-on exercises utilizing 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, targets intermediate-level Python programmers looking to design, implement, and deploy AI solutions using Python.

Upon completing 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 Bulgaria (online or onsite) is aimed at business analysts who wish to automate trade with algorithmic trading, Python, and R.

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

• Employ algorithms to buy and sell securities at specialized increments rapidly.
• Reduce costs associated with trade using algorithmic trading.
• Automatically monitor stock prices and place trades.

This is a 4-day course introducing AI and its application using the Python programming language. There is an option to have an additional day to undertake an AI project on completion of this course.

This instructor-led, live training in Bulgaria (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 more efficient and rapid interaction options, chatbots enable organizations to optimize their operational performance.

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

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

• Grasping the core principles behind chatbot development
• Creating, testing, deploying, and resolving issues with various chatbot systems using Python

Target Audience

• Software Developers

Course Format

• A blend of lectures, group discussions, practical exercises, and extensive hands-on programming

Note

• For information on arranging a customized training session for this course, please contact us.

This instructor-led, live training in Bulgaria (online or onsite) is designed for intermediate-level developers who want to utilize CUDA to construct Python applications that execute in parallel on NVIDIA GPUs.

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

• Leveraging the Numba compiler to enhance the performance of Python applications running on NVIDIA GPUs.
• Creating, compiling, and launching custom CUDA kernels.
• Handling GPU memory resources.
• Transforming a CPU-based application into one accelerated by the GPU.

Course Overview

This practical training program is tailored for data engineering professionals aiming to develop concrete expertise in artificial intelligence, Python, and large language models. The curriculum emphasizes real-world implementation, addressing model application, prompt engineering, and the creation of AI-driven solutions. Participants will engage in progressive exercises that transition from foundational concepts to the construction of deployable AI workflows.

Training Format

• In-person classroom instruction

• Instructor-led sessions featuring guided practice

• Interactive discussions alongside 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 master their effective utilization

• Design and optimize prompts to ensure reliable outputs

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

• Integrate AI capabilities into data engineering pipelines

This instructor-led, live training in Bulgaria (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 Bulgaria (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 utilize the FARM stack (FastAPI, React, and MongoDB) to build dynamic, high-performance, and scalable web applications.

Upon completing this training, participants will be able to:

• Configure the essential development environment integrating FastAPI, React, and MongoDB.
• Grasp the core concepts, features, and advantages of the FARM stack.
• Master the creation of REST APIs using FastAPI.
• Design interactive user interfaces with React.
• Develop, test, and deploy both front-end and back-end applications using the FARM stack.

This instructor-led live training in Bulgaria (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 Bulgaria (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.