New course areas: focus on in-demand technologies and professions of the future
We create training programs that reflect modern industry requirements and meet the challenges of the IT market. Our courses cover the following areas:
Development of artificial intelligence and machine learning
Within this area, you will get acquainted with machine learning algorithms, neural networks, big data processing and the creation of intelligent systems. Learn to use Python and TensorFlow, PyTorch libraries to solve real-world problems, including data analysis, pattern recognition and automation.
Cybersecurity and data protection
A critical area that ensures the security of digital information. You will learn vulnerability analysis methods, principles of building secure systems, working with cryptography and ethical hacking. Hands-on tasks will help you understand how to prevent hacking and protect corporate networks.
Cloud Solution Development and DevOps
This course focuses on cloud infrastructure, containerization, orchestration and process automation. You will master the AWS, Azure platforms, as well as Docker and Kubernetes tools that allow you to build scalable, flexible and reliable services.
Artificial Intelligence and Machine Learning Development
Why choose this direction:
Artificial intelligence and machine learning are key technologies of the 21st century that are radically changing industries: from healthcare to finance. Companies are looking for specialists who can analyze large amounts of data and build predictive models. The demand for such developers is high and continues to grow, and salaries in this field are consistently among the highest in IT.
What is studied:
Fundamentals of machine learning: linear regression, decision trees, support vector machines.
Deep learning: artificial neural networks, convolutional and recurrent neural networks.
Practice with frameworks: TensorFlow, PyTorch.
Data processing and visualization (NumPy, Pandas, Matplotlib).
Learning methods with and without a teacher.
Data preparation and cleaning (data preprocessing).
Introduction to neural architectures (ResNet, Transformer, etc.).
Building pipelines and deploying models.
Why do you need it:
Solving business problems: demand forecasting, automating routine processes, classifying and clustering information.
Career growth: the opportunity to become an ML engineer, data scientist, data analyst, or AI researcher.
Developing innovations: creating intelligent services, chatbots, recommendation systems, and automatic assistants.
Cybersecurity and data protection
Why you should choose this direction:
Every year the world is becoming more digital, which means it is more vulnerable. Information protection is a priority for businesses, banks, healthcare organizations, and government agencies. Cybersecurity specialists are needed always and everywhere, especially in the era of remote work, cloud services, and constant cyber threats.
What they study:
Information security basics: threat models, access policies, rights management.
Vulnerability analysis, penetration testing, ethical hacking.
Cryptography: encryption, digital signatures, security protocols.
Web application security: SQL injections, XSS, CSRF, protection methods.
Network security: VPN setup, firewall, IDS/IPS.
Incident management and attack response.
Regulatory requirements: GDPR, ISO 27001.
Monitoring and logging tools: SIEM, Wireshark, Metasploit.
Why you need it:
Confidence and control: the ability to protect digital assets, customer data and intellectual property.
High demand: companies are investing heavily in cybersecurity, and the market for specialists is empty.
Many career options: information security specialist, auditor, security officer (CISO), threat analysis engineer.
Cloud Development and DevOps
Why choose this direction:
Most modern services operate in the cloud. It is cost-effective, flexible and scalable. Companies are moving to microservice architecture and automating product deployment. Cloud technology specialists and DevOps engineers are at the forefront of digital transformation.
What they study:
Cloud platforms: AWS, Microsoft Azure, Google Cloud.
Infrastructure as code (IaC): Terraform, Ansible.
Containerization: Docker, basic and advanced practices.
Orchestration: Kubernetes — cluster setup, deployment, autoscaling.
CI/CD pipelines: Jenkins, GitLab CI, GitHub Actions.
Monitoring and logging: Prometheus, Grafana, ELK stack.
Security and fault tolerance in clouds.
Practice of building DevOps processes: from commit to production.
Why is it necessary:
Quick scaling of projects: you can deploy a full-fledged infrastructure in minutes.
Continuous integration and delivery: automation of all stages of development speeds up the launch of a product to the market.
Career opportunities: professions of DevOps engineer, Cloud architect, SRE engineer, next-generation system administrator.
Our teachers
Olga Nikitina
Senior Web developer with 8 years of experience
Olga specializes in JavaScript, Vue.js and adaptive layout. She worked in several startups and product companies, where she developed interfaces with a high load. In her training, she focuses on clean code, architecture and understanding of client-server interaction. Her classes focus on practice and code review.
Andrey Maksimov
Technical leader of the testing department in an international company
Andrey is an expert in automated testing in Python and Selenium. Led QA teams on various projects in e-commerce and fintech. Has been teaching for over 4 years, focusing on building automated tests, configuring CI/CD, proper documentation, and teamwork.
Elena Chernova
Mobile Application Developer (iOS and Android)
Elena is a practitioner who has created over 10 applications posted in the App Store and Google Play. Her specialty is her ability to explain complex architectural approaches in simple language. She focuses on UX design, working with API, publishing, and supporting applications after release.
Why should you study programming with us?
Learning programming is not just gaining theoretical knowledge. It is a practical activity that allows you to create real products and discover new opportunities. Here are the key benefits of our courses:
Intensive practice and real projects
We believe that the best way to learn programming is through constant practical application of knowledge. You will create your own applications, solve problems encountered in real companies, and work on projects in a team.
Relevance and flexibility of programs
Courses are updated regularly, taking into account the latest trends and technologies. You can choose the format of training – face-to-face, online or blended, as well as the pace that suits your level of preparation.
Support from experienced mentors
Each student receives personal feedback from industry professionals. Our teachers not only share knowledge, but also help develop thinking, form the right skills and prepare for a successful career.
Development of problem-solving skills and creativity
Programming is, first of all, the ability to think analytically and creatively. We teach you to approach complex problems in a structured way, find non-standard solutions and constantly improve your programs.
Broad career prospects
Mastery of modern technologies opens doors to companies in various fields – from finance and medicine to the gaming industry and science. You will be able to choose the path of a developer, data analyst, security specialist or systems architect.
Feedback from our students
“The courses completely changed my understanding of the profession. Previously, I only knew basic HTML and a little CSS, but thanks to project practice and attentive teachers, I built my first adaptive landing page in just 3 months. I would especially like to note the React module – structured, with real cases and an accessible explanation. Now I work in an IT company and develop as a junior frontend developer.”
Alexey K
“The course program turned out to be much broader than I expected. In addition to theory, we worked with real bugs, learned to write automated tests and set up Jenkins for CI. The convenient format of homework, regular code checks and real cases helped me not only learn the material, but also confidently pass the interview for the position of QA Automation Engineer.”
Maria S
“The Kotlin course was rich and very practical. I liked the focus on user experience, code structure and working with databases. We developed a full-fledged application – from a prototype to uploading to Google Play. Thanks to the feedback and help of the teacher, I not only learned the language, but also started thinking like a developer.”