Python Training in Opole

Python is the core language powering the development and orchestration of autonomous AI agents. This course focuses on practical implementation using modern SDKs and frameworks such as LangChain and AutoGen to build, connect, and manage agent workflows.

This instructor-led, live training (online or onsite) is aimed at intermediate-level backend engineers, platform engineers, and ML engineers who wish to implement and orchestrate autonomous agents using Python tooling and APIs.

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

• Set up and configure Python-based environments for agentic systems.
• Use popular agent SDKs like LangChain and AutoGen to create functional agents.
• Integrate tools and APIs to extend agent capabilities.
• Orchestrate multi-agent workflows and communication patterns.
• Apply best practices for debugging, testing, and maintaining agentic codebases.

Format of the Course

• Interactive lecture and discussion.
• Hands-on programming exercises and live demos.
• Practical projects building end-to-end agent workflows.

Course Customization Options

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

This course teaches practical engineering techniques to design, build, test, and deploy 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.

Format of the Course

• 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.

Artificial Intelligence with Python is the development of intelligent systems using Python’s extensive ecosystem of AI and machine learning libraries.

This instructor-led, live training (online or onsite) is aimed at intermediate-level Python programmers who wish 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 in Opole (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 Opole (online or onsite) is aimed at expert-level data analysts who wish to leverage Python's data analysis capabilities within Power BI, enhancing their ability to analyze and visualize data effectively.

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

• Learn how Python can be integrated into Power BI for data analysis.
• Use Python scripts to load, clean, and preprocess data within the Power BI environment.
• Enhance data visualization capabilities by creating custom and interactive visualizations using Python.
• Acquire 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 instructor-led, live training in Opole (online or onsite) is aimed at experienced developers who wish to gain a comprehensive understanding of Python programming and its applications in cybersecurity.

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

• Use Python programming for defensive cybersecurity.
• Understand and use Python for ethical offensive techniques and digital forensics tasks.
• Recognize legal and ethical considerations surrounding offensive cybersecurity and vulnerability disclosure.

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 instructor-led, live training in Opole (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:

• Understand the basics of Python programming language.
• Implement Python code in Google Colab environment.
• Utilize control structures to manage the flow of a Python program.
• Create functions to organize and reuse code effectively.
• Explore and use basic libraries for Python programming.

This instructor-led, live training in Opole (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 designed for those wishing to learn the Python programming language. The emphasis is on the Python language, the core libraries, as well as on the selection of the best and most useful libraries developed by the Python community. Python drives businesses and is used by scientists all over the world – it is one of the most popular programming languages.

The course can be delivered using the latest Python version 3.x with practical exercises making use of the full power. This course can be delivered on any operating system (all flavours of UNIX, including Linux and Mac OS X, as well as Microsoft Windows).

The practical exercises constitute about 70% of the course time, and around 30% are demonstrations and presentations. Discussions and questions can be asked throughout the course.

Note: the training can be tailored to specific needs upon prior request ahead of the proposed course date.

This instructor-led, live training in Opole (online or onsite) is aimed at developers who wish to 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.

This course is designed for those wishing to learn the Python programming language. The emphasis is on the Python language, the core libraries, as well as on the selection of the best and most useful libraries developed by the Python community. Python drives businesses and is used by scientists all over the world – it is one of the most popular programming languages.

The training course will help the participants prepare for Web Application Development using Python Programming with Data Analytics. Such data visualization is a great tool for Top Management in decision making.

The aim of this course is to provide a basic proficiency in applying Machine Learning methods in practice. Through the use of the Python programming language and its various libraries, and based on a multitude of practical examples this course teaches how to use the most important building blocks of Machine Learning, how to make data modeling decisions, interpret the outputs of the algorithms and validate the results.

Our goal is to give you the skills to understand and use the most fundamental tools from the Machine Learning toolbox confidently and avoid the common pitfalls of Data Sciences applications.

This instructor-led, live training in Opole 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 in Opole, participants will learn the most relevant and cutting-edge machine learning techniques in Python as they build 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 Opole (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.

The aim of this course is to provide general proficiency in applying Machine Learning methods in practice. Through the use of the Python programming language and its various libraries, and based on a multitude of practical examples this course teaches how to use the most important building blocks of Machine Learning, how to make data modeling decisions, interpret the outputs of the algorithms and validate the results.

Our goal is to give you the skills to understand and use the most fundamental tools from the Machine Learning toolbox confidently and avoid the common pitfalls of Data Sciences applications.

Python is a programming language that has gained huge popularity in the financial industry. Adopted by the largest investment banks and hedge funds, it is being used to build a wide range of financial applications ranging from core trading programs to risk management systems.

In this instructor-led, live training, participants will learn how to use Python to develop practical applications for solving a number of specific finance related problems.

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

• Understand the fundamentals of the Python programming language
• Download, install and maintain the best development tools for creating financial applications in Python
• Select and utilize the most suitable Python packages and programming techniques to organize, visualize, and analyze financial data from various sources (CSV, Excel, databases, web, etc.)
• Build applications that solve problems related to asset allocation, risk analysis, investment performance and more
• Troubleshoot, integrate, deploy, and optimize a Python application

Audience

• Developers
• Analysts
• Quants

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

Note

• This training aims to provide solutions for some of the principle problems faced by finance professionals. However, if you have a particular topic, tool or technique that you wish to append or elaborate further on, please 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

This is a 4 day course introducing AI and it's 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. 

Selenium is an open-source framework for automating web application testing across different browsers. With Selenium 4, enhanced WebDriver APIs, native relative locators, and improved grid support are available. Python offers simplicity and strong integration with testing frameworks like Pytest, making it a powerful choice for developing scalable and maintainable test automation suites.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level testers and developers who wish to use Selenium with Python to automate web application testing in real-world environments.

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

• Install and configure Selenium with Python in a test environment.
• Build robust test automation scripts using Selenium WebDriver and Pytest.
• Apply Page Object Model (POM) for maintainable test frameworks.
• Run tests across multiple browsers using Selenium Grid.
• Integrate automated tests with CI/CD pipelines.
• Troubleshoot common issues and apply best practices for automation stability.

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.

In this instructor-led, live training in Opole (onsite or remote), participants will learn how to combine the capabilities of Python and Excel.

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

• Install and configure packages for integrating Python and Excel.
• Read, write, and manipulate Excel files using Python.
• Call Python functions from Excel.

This instructor-led, live training in Opole (online or onsite) is aimed at Matlab users who wish to explore and 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 obtain insights from various datasets.
• Convert existing Matlab applications to Python.
• Integrate Matlab and Python applications.

This instructor-led, live training in Opole (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 Opole (online or onsite) is aimed at developers who wish to use Python to automate the process of crawling many websites to extract data for processing and analysis.

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

• Install and configure Python and all relevant packages.
• Retrieve and parse data stored across many different websites.
• Understand how websites work and how their HTML is structured.
• Construct spiders to crawl the web at scale.
• Use Selenium to crawl AJAX-driven web pages.

"Python Training for Programmers" is a comprehensive course that provides in-depth knowledge of the Python language for programmers. Participants will gain skills in data structures, classes, file handling, network communication, and integration with other programs. The course covers practical aspects such as configuring editors, running programs in different environments, and installing additional libraries.

This instructor-led, live training in Opole (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 instructor-led, live training in Opole (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to use Python to build blockchain and cryptocurrency applications.

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

• Use Python to create and manipulate blockchain and cryptocurrency systems and data.
• Use Python libraries and frameworks such as Flask, PyCrypto, and web3.py to interact with blockchain and cryptocurrency networks and services.
• Use Python to implement smart contracts, consensus algorithms, and cryptographic protocols for blockchain and cryptocurrency applications.
• Use Python to develop and deploy decentralized applications (DApps) that run on blockchain and cryptocurrency platforms.
• Use Python to perform data analysis and visualization on blockchain and cryptocurrency data.

ChatBots are computer programs that automatically simulate human responses via chat interfaces. ChatBots help organizations maximize their operations efficiency by providing easier and faster options for their user interactions.

In this instructor-led, live training, participants will learn how to build chatbots in Python.

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

• Understand the fundamentals of building chatbots
• Build, test, deploy, and troubleshoot various chatbots using Python

Audience

• Developers

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

Note

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

This instructor-led, live training in Opole (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.

The training focuses on practical use of the Streamlit library to create interactive web applications and analytical dashboards in Python. Participants will learn to build functional user interfaces without needing to know HTML, CSS, or JavaScript.

The program covers all key components of Streamlit – from basic text elements and layout, through interactive input widgets, to advanced features such as forms, charts, and file handling. Participants will understand mechanisms for managing session state, caching results, and integrating with databases, which allows for the creation of efficient production applications.

Special emphasis is placed on practical application – each theory module is enriched with exercises, and the training concludes with the creation of a complete project or two, depending on time availability.

Upon completion of the training, participants will be able to independently design Streamlit applications – from simple dashboards to advanced analytical tools. They will acquire skills that enable rapid prototyping of data science solutions and creating interfaces for machine learning models.

This instructor-led, live training in Opole (online or onsite) is aimed at data scientists who wish to use TensorFlow to analyze potential fraud data.

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

• Create a fraud detection model in Python and TensorFlow.
• Build linear regressions and linear regression models to predict fraud.
• Develop an end-to-end AI application for analyzing fraud data.

The training provides a comprehensive approach to integrating Python applications with PostgreSQL databases. The program covers three main tools – the psycopg library for direct communication with the database, Pandas for operations on tabular data, and ORM SQLAlchemy for object-oriented data management.

Participants will learn to safely execute SQL queries using parameterization that protects against SQL injection attacks. The program also includes integration with the Pandas library, enabling efficient loading and exporting of data between DataFrame and PostgreSQL.

A significant portion of the training is dedicated to SQLAlchemy – participants will learn to define data models as Python classes, map them to tables, and perform all CRUD operations without writing raw SQL. They will explore techniques for filtering, sorting, grouping data, and managing relationships between tables in an object-oriented manner.

Upon completion of the training, participants will be able to choose the appropriate tool for specific use cases, communicate safely with the database, and utilize both low-level SQL queries and high-level ORM abstractions. They will gain practical skills essential for daily work with databases in Python projects.

This training introduces participants to the topic of large language models and teaches practical integration with them using Python. The program covers both the theoretical foundations of LLMs and specific techniques for communicating with these models via APIs and SDKs.

Participants will learn key concepts such as tokenization, temperature, context window, and how to construct effective prompts using techniques like few-shot learning and chain-of-thought. The course covers various interfaces for accessing models—from the OpenAI platform and ChatGPT, through direct API requests, to using the LangChain framework and the OpenRouter aggregator.

The training includes working with structured outputs, real-time streaming, and text embeddings that enable semantic search and document comparison. Emphasis is placed on practical applications—participants will implement solutions for automatic text summarization, translation, sentiment analysis, and information extraction.

Upon completion of the training, participants will be able to independently design prompts, integrate Python applications with various language models, select appropriate techniques for specific problems, and deploy LLM-based solutions in a production environment. They will gain practical knowledge that enables them to leverage generative models in real business projects.

The training guides participants through a comprehensive process of building machine learning models in Python using the scikit-learn library. The program covers both regression and classification algorithms, with an emphasis on practical application.

Participants will learn key aspects of working with data – from feature engineering, through normalization and standardization, to handling missing values and encoding categorical variables. They will also explore methods for detecting and eliminating outliers, as well as techniques for selecting the most important attributes. Special attention is given to the problem of overfitting models and methods to prevent it, including cross-validation and regularization.

In the algorithms section, participants will implement a wide range of models – from simple linear regression, through decision trees, SVM, and KNN, to advanced ensemble methods such as Random Forest and Gradient Boosting. Each algorithm is discussed from a practical application perspective, along with appropriate evaluation metrics.

The program also includes model optimization through hyperparameter tuning using grid search, as well as building pipelines to automate the data processing workflow. Upon completion of the training, participants will be able to independently prepare data, select an appropriate algorithm, train a model, and evaluate its quality using suitable metrics.

Course Format

The course begins with an overview of the applications and analysis of Process Mining. We discuss the pm4py library and various algorithms for discovering and analyzing processes based on data. We delve into the data structures that form the foundation of discovered process modeling. The course focuses on the technical aspects of Process Mining, with real-life case studies analyzed during Python exercises.
 

This instructor-led, live training in Opole (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 leverage Paramiko, Netmiko, Napalm, Telnet, and pyntc for network automation with Python.
• Master multi-threading and multiprocessing in network automation.
• Use GNS3 and Python for network programming.

In this instructor-led, live training in Opole, participants will learn how to use Python to produce high-quality natural language text by building their own NLG system from scratch. Case studies will also be examined and the relevant concepts will be applied to live lab projects for generating content.

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

• Use NLG to automatically generate content for various industries, from journalism, to real estate, to weather and sports reporting.
• Select and organize source content, plan sentences, and prepare a system for automatic generation of original content.
• Understand the NLG pipeline and apply the right techniques at each stage.
• Understand the architecture of a Natural Language Generation (NLG) system.
• Implement the most suitable algorithms and models for analysis and ordering.
• Pull data from publicly available data sources as well as curated databases to use as material for generated text.
• Replace manual and laborious writing processes with computer-generated, automated content creation.

This instructor-led, live training in Opole (online or onsite) is aimed at penetration testers who wish to penetrate test networks in Kali Linux using Python.

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

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

The "Python Programming" course covers an introduction to the Python language, installation and configuration of the environment, basic syntax, procedural and object-oriented programming, exception handling, code organization, using the standard library, installing external libraries, input/output operations, software testing and debugging, as well as applications of the Python language. Participants will acquire the skills needed for effective Python programming in various contexts, such as web applications, data analysis, or scientific computing. Good Python programming practices are also discussed during the course.

This instructor-led, live training in Opole (online or onsite) is aimed at developers who wish to use Python as the server-side language to create a web application. Various techniques and frameworks will be explored to arrive at the most suitable one for a given problem.

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

• Install and configure Python packages and frameworks.
• Set up the appropriate development environment to optimize the coding process.
• Write the code needed to enable common functionality expected by end users of an application (forms, database queries, calculations, etc.)
• Select from a number of popular frameworks such as Django and Flask to automate redundant tasks and reduce development time.

Python is a high-level programming language famous for its clear syntax and code readibility.

In this instructor-led, live training, participants will learn how to use Python for quantitative finance.

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

• Understand the fundamentals of Python programming
• Use Python for financial applications including implementing mathematical techniques, stochastics, and statistics
• Implement financial algorithms using performance Python

Audience

• Developers
• Quantitative analysts

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

Computer Vision is a field that involves automatically extracting, analyzing, and understanding useful information from digital media. Python is a high-level programming language famous for its clear syntax and code readibility.

In this instructor-led, live training, participants will learn the basics of Computer Vision as they step through the creation of set of simple Computer Vision application using Python.

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

• Understand the basics of Computer Vision
• Use Python to implement Computer Vision tasks
• Build their own face, object, and motion detection systems

Audience

• Python programmers interested in Computer Vision

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

This course introduces the student to the Python language. Upon completion of this class, the student will be able to write non trivial Python programs dealing with a wide variety of subject matter domains. Topics include language components, working with a professional IDE, control flow constructs, strings, I/O, collections, classes, modules, and regular expressions. The course is supplemented with many hands-on labs, solutions, and code examples.

After Completing the course students will be able to demonstrate knowledge and understanding of Python Security Principles.

The training focuses on building a Retrieval Augmented Generation (RAG) system, which combines the capabilities of large language models with information retrieval from local documents. Participants will learn to create applications that answer questions based on their own data, eliminating issues of hallucination and knowledge limitations in LLMs.

The program covers all key stages of RAG system creation. Participants will learn the principles of communicating with the OpenAI API and using the LangChain framework to facilitate working with language models. They will also learn to process documents in various formats, divide them into optimal segments, and transform them into vector representations. They will be introduced to the Qdrant database and mechanisms for semantic search based on embedding similarity.

Special emphasis is placed on system performance—participants will implement result reranking techniques and learn to quantify retrieval effectiveness and generated responses using the DeepEval library. The program also covers practical aspects of prompt engineering and methods for avoiding common pitfalls when working with LLMs.

The outcome of the training will be a functional web application built in Streamlit, which allows users to ask questions about their own document base. Upon completing the course, participants will be able to independently design and implement a RAG system tailored to their business needs.

This instructor-led, live training (online or onsite) is aimed at developers and data scientists who wish to use spaCy to process very large volumes of text to find patterns and gain insights.

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

• Install and configure spaCy.
• Understand spaCy's approach to Natural Language Processing (NLP).
• Extract patterns and obtain business insights from large-scale data sources.
• Integrate the spaCy library with existing web and legacy applications.
• Deploy spaCy to live production environments to predict human behavior.
• Use spaCy to pre-process text for Deep Learning

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.
• To learn more about spaCy, please visit: https://spacy.io/

Tableau is a business intelligence and data visualization tool. Python is a widely used programming language which provides support for a wide variety of statistical and machine learning techniques. Tableau's data visualization power and Python's machine learning capabilities, when combined, help developers rapidly build advanced data analytics applications for various business use cases.

In this instructor-led, live training, participants will learn how to combine Tableau and Python to carry out advanced analytics. Integration of Tableau and Python will be done via the TabPy API.

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

• Integrate Tableau and Python using TabPy API
• Use the integration of Tableau and Python to analyze complex business scenarios with few lines of Python code

Audience

• Developers
• Data scientists

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

In Python Machine Learning, the Text Summarization feature is able to read the input text and produce a text summary. This capability is available from the command-line or as a Python API/Library. One exciting application is the rapid creation of executive summaries; this is particularly useful for organizations that need to review large bodies of text data before generating reports and presentations.

In this instructor-led, live training, participants will learn to use Python to create a simple application that auto-generates a summary of input text.

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

• Use a command-line tool that summarizes text.
• Design and create Text Summarization code using Python libraries.
• Evaluate three Python summarization libraries: sumy 0.7.0, pysummarization 1.0.4, readless 1.0.17

Audience

• Developers
• Data Scientists

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice