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Courses
Courses in object-oriented programming with C++, C#, Java, Kotlin and Python, and in parallel and distributed computing. Every topic consists of a lecture divided into chapters, worked examples, task variants at three levels of difficulty, and review questions.
Choose the course for your subject. The OOP courses start from the basics of the language and need no prior experience with it. “Object-oriented programming in C# II” continues the “Object-oriented programming in C# I” course, and “Parallel and distributed computing” is meant for those who have already completed an object-oriented programming course.
Object-Oriented Programming in C++
From the first program in Visual Studio 2026 to classes, templates, containers, ranges and C++26 modules. 16 topics in three modules.
Object-Oriented Programming in C# I
From the .NET platform and your first program to classes, interfaces, generics, LINQ, working with files, the SOLID principles and unit testing. 18 topics in three modules.
Object-Oriented Programming in C# II
A continuation of the C# I course: Git, regular expressions, Windows Forms, async/await, ADO.NET and Entity Framework Core, network applications, REST and SignalR, WPF, .NET MAUI and integrating AI models. 16 topics in three modules.
Object-Oriented Programming in Java
From JDK 27 and IntelliJ IDEA to classes, records, generics, collections, the Stream API, modules, JDBC and GUI applications with JavaFX. 16 topics in four modules.
Object-Oriented Programming in Kotlin
From Kotlin 2.4 and Gradle projects to null safety, data classes, generics, collections, coroutines, databases with Exposed and applications built with Compose Multiplatform. 16 topics in four modules.
Object-Oriented Programming in Python
From Python 3.14 and PyCharm to functions, collections, generators, classes and protocols, pytest, SQLite and SQLAlchemy, NumPy and pandas, GUI applications with PySide6 and packaging. 16 topics in four modules.
Parallel and Distributed Computing
From threads and synchronization in C# (TPL, PLINQ, SIMD) to high-performance computing in C++ with OpenMP, CUDA and MPI on a Slurm cluster, and distributed .NET applications with RabbitMQ, Orleans, Docker and Kubernetes. 18 topics in three modules.