IBM ODM Decision Management Training Course

This instructor-led, live training in Poland (online or onsite) is aimed at advanced-level participants who wish to optimize rule execution, integrate Drools with enterprise systems, and leverage advanced features like decision tables and domain-specific languages (DSLs).

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

• Optimize the performance of complex rule execution.
• Utilize advanced Drools features such as decision tables, DSLs, and rule templates.
• Integrate Drools seamlessly with enterprise applications and external systems.
• Implement robust version control and collaboration mechanisms for rule development.
• Design and deploy scalable Drools-based solutions for enterprise needs.

This course is aimed at enterprise architects, business and system analysts, technical managers and developers who want to apply business rules to their solutions.

This course contains a lot of simple hands-on exercises during which the participants will create working rules. Please refer to our other courses if you just need an overview of Drools.

This course is usually delivered on the newest stable version of Drools and jBPM, but in case of a bespoke course, can be tailored to a specific version.

Business Process Model and Notation (BPMN), Decision Model and Notation (DMN) and Case Management Model and Notation (CMMN) are three Object Management Group (OMG) standards for processes, decisions, and case modelling. This course provides an introduction to all of them and informs when should we use which.

This course is aimed at enterprise architects, business and system analysts and managers who want to apply business rules to their solution. With Drools, you can write your business rules using almost natural language, therefore reducing the gap between business and IT.

This instructor-led, live training in Poland (online or onsite) is aimed at intermediate-level developers who wish to get a solid introduction to Drools 6 and use it to implement business rules within their applications.

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

• Understand the core concepts and benefits of rule engines like Drools.
• Use the Drools Workbench and Eclipse for rule authoring and testing.
• Create, organize, and execute business rules with the Drools rule engine.
• Apply advanced features like decision tables, ruleflows, and DSLs.

This 3 days course is aimed to introduce Drools 7 to Business Analysts responsible for writing tests and rules.

This course focuses on creating pure logic. Analysts after this course can writing tests and logic which then can be further integrated by developers with business applications.

This 3 days course is aimed to introduce Drools 7 to developers.This course doesn't cover drools integration, performance or any other complex topics.

This instructor-led, live training in Poland (online or onsite) is aimed at intermediate-level system administrators and developers who wish to configure, manage, and deploy Java applications on the JBoss platform.

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

• Install and configure JBoss Application Server and its core components.
• Customize JBoss AS services for monitoring, database connections, and transaction management.
• Develop and deploy EJB 3 session beans and web applications.
• Utilize the JBoss Messaging Service to deploy and manage JMS applications.
• Manage JBoss AS through the Java Management Extension and Administration Console.
• Implement JBoss Drools for business rules management and utilize the Guvnor tool for rule development and testing.

This course teaches how to design and execute decisions with OMG DMN (Decision Model and Notation) standard.

This course uses a practical approach to teaching OptaPlanner. It provides participants with the tools needed to perform the basic functions of this tool.

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.

This training allows participants to gradually enter the world of programming in the Python language. The course covers the most important elements of the language—from basic syntax and working with the environment, through data operations and program flow control, up to functions, modules, and the first elements of object-oriented programming.

Participants will become familiar with key constructs used in daily programming work, learn algorithmic thinking, and organize code in a transparent and consistent manner according to best practices. During the training, significant emphasis is placed on writing high-quality code and error analysis.

Upon completion of the training, participants will be able to independently write simple scripts, create functions and classes, organize projects into files, as well as understand, analyze, and run Python code in practical applications.

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 how to create applications that answer questions based on their own data, eliminating the problem of hallucinations and knowledge limitations in LLMs.

The program guides participants through all key stages of creating a RAG system. They will become familiar with communication principles using the OpenAI API and the LangChain framework, which facilitates working with language models. Participants will learn how to process documents in various formats, divide them into optimal segments, and transform them into vector representations. They will also get to know the Qdrant database and mechanisms for semantic search based on embedding similarity.

We place special emphasis on the quality of system performance—participants will implement result reranking techniques and learn how to quantify retrieval effectiveness and generated responses using the DeepEval library. The program also covers practical aspects of prompt engineering and methods for avoiding typical 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 specific business needs.

In this instructor-led, live training in Poland (onsite or remote), participants will learn how to use Python skope-rules to automatically generate rules based on existing data sets.

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

• Use skope-rules to extract rules from available data.
• Apply skope-rules to carry out classification, particularly useful in supervised anomaly detection, or imbalanced classification. 
• Generate rules for classifying new incoming data.
• Fit rules to address real-world problems in fraud detection, predictive maintenance, intrusion detection, insurance application approvals, etc.

This 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 knowledge of HTML, CSS, or JavaScript.

The program covers all key components of Streamlit – from basic text elements and layout to interactive input widgets, advanced features such as forms, charts, and file handling. Participants will understand session state management, result caching, and database integration, enabling them to create efficient production applications.

We emphasize practical application – each theoretical module is supplemented with exercises, and the training concludes with the creation of a complete project or two, depending on time availability.

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