Python Training in Plovdiv

Python serves as the foundational language for developing and orchestrating autonomous AI agents. This course emphasizes practical implementation through modern SDKs and frameworks, such as LangChain and AutoGen, to build, link, and manage agent workflows effectively.

Delivered by an instructor in either online or onsite format, this training is designed for intermediate-level backend, platform, and ML engineers aiming to implement and orchestrate autonomous agents using Python tooling and APIs.

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

• Configure Python-based environments tailored for agentic systems.
• Utilize leading agent SDKs, including LangChain and AutoGen, to develop functional agents.
• Integrate tools and APIs to enhance agent capabilities.
• Orchestrate multi-agent workflows and establish communication patterns.
• Implement best practices for debugging, testing, and maintaining codebases related to agents.

Course Format

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

Customization Options

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

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.

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 Plovdiv (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 Plovdiv (online or onsite) is designed for experienced data analysts looking to harness Python's data analysis capabilities within Power BI, thereby improving their efficiency 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 purposes.
• Apply Python scripts to load, clean, and preprocess data within the Power BI environment.
• Expand data visualization options by developing custom and interactive visualizations with Python.
• Develop advanced data analysis skills using Python.

Python is a versatile programming language widely used for data manipulation, automation, and analytics. Libraries like Pandas and Polars provide powerful, practical tools for working with tabular data at scale.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level professionals who wish to apply Python for everyday data analysis, file processing, and process automation using Pandas and Polars.

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

• Use Python to read, transform, and write CSV and Excel files.
• Perform common data cleaning and transformation tasks with Pandas and Polars.
• Automate repetitive data processes with Python scripts.
• Package simple scripts into executables and follow best practices for projects.

Format of the Course

• Interactive coding demonstrations and short lectures.
• Hands-on exercises with guided code examples.
• Practical mini-projects to automate real-world tasks.

Course Customization Options

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

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 instructor-led, live training in Plovdiv (online or onsite) is aimed at beginner-level developers and data analysts who wish to learn Python programming from scratch using Google Colab.

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

• Gain a solid understanding of the fundamental concepts of the Python programming language.
• Write and execute Python code effectively within the Google Colab environment.
• Apply control structures to manage the flow of execution in Python programs.
• Develop functions to organize code efficiently and promote reusability.
• Explore and utilize essential libraries to enhance Python programming capabilities.

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 Plovdiv (online or onsite) is aimed at beginner-level to intermediate-level and potentially advanced-level robotics developers who wish to learn how to use ROS to program mobile robots using Python.

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

• Set up a development environment that includes ROS, Python, and a mobile robot platform.
• Create and run ROS nodes, topics, services, and actions using Python.
• Use ROS tools and utilities to monitor and debug ROS applications.
• Use ROS packages and libraries to perform common tasks for mobile robots.
• Integrate ROS with other frameworks and tools.
• Troubleshooting and debugging ROS applications.

This course is tailored for individuals looking to master the Python programming language. The curriculum focuses on the Python language itself, its core libraries, and the selection of the most valuable and effective tools developed by the Python community. Python is a globally popular programming language that powers businesses and is widely used by scientists around the world.

The course can be conducted using the latest version of Python 3.x, incorporating practical exercises that leverage its full capabilities. It is compatible with any operating system, including all variants of UNIX (such as Linux and Mac OS X) and Microsoft Windows.

Approximately 70% of the course time is dedicated to practical exercises, 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 session in Plovdiv (online or onsite) is designed for developers looking to master advanced Python programming techniques. The course covers how to leverage this versatile language to address challenges in areas such as distributed applications, data analysis and visualization, UI development, and maintenance scripting.

This course caters to individuals eager to master the Python programming language. The curriculum focuses on the Python language itself, its core libraries, and the selection of the most valuable and effective libraries contributed by the Python community. Python is a powerhouse driving businesses globally and is widely utilized by scientists around the world, making it one of the most popular programming languages today.

This instructor-led, live training in Plovdiv 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.

In this instructor-led, live training session in Plovdiv, participants will learn the most relevant and cutting-edge machine learning techniques in Python by building a series of demo applications involving image, music, text, and financial data.

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

• Implement machine learning algorithms and techniques for solving complex problems.
• Apply deep learning and semi-supervised learning to applications involving image, music, text, and financial data.
• Push Python algorithms to their maximum potential.
• Use libraries and packages such as NumPy and Theano.

This instructor-led, live training in Plovdiv (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 course is designed to equip participants with the essential skills needed to effectively apply Machine Learning techniques in real-world scenarios. Utilizing Python and its extensive ecosystem of libraries, alongside numerous hands-on examples, the curriculum guides learners through the core components of Machine Learning. It focuses on making informed decisions during data modeling, interpreting algorithm outputs, and validating results.

Our objective is to empower you with the confidence to leverage fundamental Machine Learning tools and help you steer clear of common pitfalls associated with Data Science applications.

Python has emerged as a highly popular programming language within the financial sector. Adopted by leading investment banks and hedge funds, it is utilized to develop a diverse array of financial applications, spanning from core trading systems to risk management solutions.

Through this instructor-led live training, participants will acquire the skills necessary to leverage Python for creating practical applications that address specific challenges in finance.

Upon completing this training, participants will be capable of:

• Grasping the fundamental concepts of the Python programming language
• Downloading, installing, and managing the optimal development tools for building financial applications in Python
• Choosing and employing the most appropriate Python packages and programming techniques to organize, visualize, and analyze financial data from various sources (such as CSV, Excel, databases, and web platforms)
• Developing applications that resolve issues related to asset allocation, risk analysis, investment performance, and other areas
• 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 focuses on providing solutions to key challenges faced by finance professionals. If there is a specific topic, tool, or technique you wish to explore or expand upon, please contact us to arrange for customization.

This course explores practical methodologies for Data Science and Artificial Intelligence utilizing Python. It empowers professionals with the essential skills to analyze data, develop machine learning models, and implement AI-driven solutions within business environments. The curriculum covers CRISP-DM workflows, statistical analysis, supervised and unsupervised learning, deep learning with TensorFlow, natural language processing, big data processing with Spark, and data-driven storytelling. It is ideally suited for beginners aiming to obtain a Python data science certification and receive career-ready analytics training.

Applied AI from Scratch in Python empowers programmers and data analysts with the fundamental techniques required to construct machine learning solutions entirely from the ground up using Python. The course covers essential principles of supervised learning, including classification and regression, as well as unsupervised learning methods like clustering and anomaly detection, alongside advanced neural network architectures. It explores established practices for utilizing scikit-learn, Apache Spark MLlib, and Jupyter notebooks to facilitate practical AI development. Participants will learn to implement functional ML models, assess the limitations of various algorithms, and execute applied projects designed for real-world problem-solving.

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 this by offering simplicity and strong integration with testing frameworks such as Pytest, making it a highly effective choice for developing scalable and maintainable test automation solutions.

This instructor-led live training, available both online and onsite, targets beginner to intermediate testers and developers who aim to leverage Selenium with Python for automating 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.
• Implement the Page Object Model (POM) to ensure maintainable test frameworks.
• Execute tests across multiple browsers utilizing Selenium Grid.
• Integrate automated tests into CI/CD pipelines.
• Troubleshoot common issues and apply best practices to enhance automation stability.

Format of the Course

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

Course Customization Options

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

This instructor-led, live training in Plovdiv (online or onsite) is designed for Matlab users who want 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 extract insights from various datasets.
• Convert existing Matlab applications to Python.
• Integrate Matlab and Python applications.

This instructor-led, live training in Plovdiv (online or onsite) is aimed at persons who wish to learn just enough Python to begin crunching numbers from sales data, traffic analytics, customer interactions, etc..

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

• Install and configure the necessary software, libraries and development environment to begin writing Python code for data analysis.
• Analyze data from sources such as Excel, CSV, JSON files and databases.
• Clean data to improve its usefulness before analyzing it.
• Perform simple statistical analysis.
• Generate reports that present the desired data in just the right format, from straight numbers to data visualizations.
• Gain valuable insight from data, including trends in performance, problematic areas.

In this instructor-led, live training, participants will learn advanced Python programming techniques, including how to apply this versatile language to solve problems in areas such as distributed applications, data analysis and visualization, UI programming and maintenance scripting.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• If you wish to add, remove or customize any section or topic within this course, please contact us to arrange.

This instructor-led, live training in Plovdiv (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 Plovdiv (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.

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 Plovdiv (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 Plovdiv (online or on-site) targets data scientists aiming to utilize TensorFlow for analyzing potential fraud data.

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

• Build a fraud detection model using Python and TensorFlow.
• Implement linear regressions and models to predict fraud.
• Develop a complete AI application for fraud data analysis.

This instructor-led, live training in Plovdiv (online or onsite) is aimed at 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 utilize Paramiko, Netmiko, Napalm, Telnet, and pyntc for network automation with Python.
• Master multi-threading and multiprocessing in the context of network automation.
• Use GNS3 and Python for network programming.

This instructor-led, live training in Plovdiv (online or onsite) 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 Plovdiv (online or onsite) is designed for penetration testers who wish to conduct network penetration tests in Kali Linux using Python.

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

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

This live, instructor-led training session (available online or on-site) is designed for advanced-level professionals.

Course Structure

• Engaging lectures and interactive discussions.
• Extensive practical exercises and hands-on practice.
• Real-world implementation within a live laboratory environment.

Customization Options

• For tailored training solutions, please reach out to us to make arrangements.

Python is a high-level programming language renowned for its clear syntax and code readability.

In this instructor-led, live training session, participants will acquire the skills to utilize Python for quantitative finance.

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

• Gaining a solid understanding of Python programming fundamentals
• Applying Python to financial tasks, including the implementation of mathematical techniques, stochastic models, and statistical methods
• Developing financial algorithms using high-performance Python

Audience

• Developers
• Quantitative analysts

Format of the course

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

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

During this instructor-led live training, participants will grasp the fundamentals of Computer Vision by developing a series of simple applications using Python.

Upon completing this training, participants will be able to:

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

Audience

• Python programmers seeking to expand into 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 looking to boost their automation skills through the use of Python. Although shell scripting is still effective for straightforward tasks, Python offers much greater flexibility, clarity, and scalability for handling complex automation, system administration, and DevOps workflows.

Tableau serves as a powerful business intelligence and data visualization platform, while Python is a versatile programming language that supports a broad range of statistical and machine learning methods. By leveraging Tableau's robust data visualization capabilities alongside Python's machine learning strengths, developers can efficiently construct sophisticated data analytics solutions tailored to diverse business needs.

Through this instructor-led live training, attendees will discover how to effectively merge Tableau and Python to perform advanced analytics. This integration is achieved through the TabPy API.

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

• Integrate Tableau and Python via the TabPy API
• Leverage the combined power of Tableau and Python to analyze intricate business scenarios using minimal Python code

Audience

• Developers
• Data scientists

Format of the course

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