The idea of this course is to introduce the engineering way of looking at data analytics in modern companies. It presents basic knowledge, tools and concepts that may be required to design and implement Data Engineering processes to simplify making data-driven decisions. In practice, this helps to make it easier to access datasets, tame huge amounts of data in a proper manner and gain insights, using the available hardware efficiently. Students will be able to choose components for building data pipelines, including retrieval, processing and storing the data using popular open source tools like Python, Airflow, Hadoop, Spark, Kafka, various types of databases and storages for Data Lake and Data Warehouse architectures.

At the heart of every well-engineered software system lies a software architecture. This course is tailored for students who wonder how to design architecture, what driving forces influence it, how to evaluate architecture, and what good architectural documentation looks like. We'll explore these concepts and their application in modern software architectures based on case studies from the industry. This course will also be helpful to prepare students for system design interviews.

DevOps and SRE specialization has emerged as an answer to the increasing complexity and the diversity of tasks around the development and implementation of technical solutions. This course focuses on the practical aspects of DevOps, and the problems it is targeting to resolve. The goal is to help participants learn the tools and techniques required to support development activities nowadays.

Clouds are an essential part of today’s life. Therefore, cloud computing skills are in high demand right now. The course curriculum includes the foundations of clouds: virtualisation and fundamental principles of distributed systems. In this module, different aspects of the design and implementation of distributed systems are explained. We will deep-dive into technologies like: google file system, spanner, dynamo DB, s3, and consensus algorithms like Raft and Paxos. The course also covers public clouds (AWS, GCP and Azure), and cost analysis of cloud solutions. Throughout the course, we will design and deploy cloud-native applications.

Modern computing is all about distribution. Big Data, Machine Learning, Systems – all these new and fancy subjects require us to leverage the power of many available cores and devices. This course aims to provide students with background knowledge in parallel programming and concurrent and distributed computing. Students will learn how to structure, write, run and debug multithreaded applications in Java. More importantly, they will also learn how to reason about the code running in parallel to ensure that the desired safety and liveness properties are present in a scalable way without sacrificing performance. As a teaser, by the end of the course students are introduced to distributed computing. The course builds on the classical model of computation with a single processor and memory, and iteratively introduces one more bit of complexity at once. First, the course explores the effects of introducing several processors into the computational model while keeping a shared memory. Then, the course explores the effects of replacing the shared memory model with the message-passing model (as in distributed computing). If time permits, the effects of failures on the computational model will be discussed. On the practical side, the course includes a lot of labs and programming exercises to ensure enough hands-on experience. Performance matters are covered as well, as students will be delivered content on basic performance analysis capabilities.

In this course, students will learn about the fundamentals of blockchains by building one from scratch. The curriculum is structured around a group project, with interactive lectures providing all the required theoretical and practical knowledge to succeed. The course will cover major classical and modern blockchain architectures as well as applications such as DeFi, NFT, DAO, etc.

Java is one of the most popular programming languages in the software development industry. This course covers topics about the Java programming language as it is applied to networking, databases, web services, mobile applications, and other practical aspects. The course is designed for graduate students with some programming experience who would like to develop software in Java to solve real problems.

Computers are great at helping us with repetitive tasks, and this applies just as much to our use of the computer as it does to the computations we want it to perform. Because of today’s technology, we have a vast range of tools to choose from that enables us to be more productive. Yet, many of us only use a small fraction of these tools; this course is an attempt to address this issue. To do so, this course will cover topics such as command-line, bash scripts, debugging, profiling, version control, testing, and data wrangling. We will also cover how to use a powerful text editor called Vim.

C++ is a powerful multi-paradigm language. Learning C++ will grow your ability to think and solve problems in many different ways. This course is an introduction to C++ language and the usage of object-oriented programming. You'll also learn how to think algorithmic and solve problems regardless of the tools you have. Modern C++ is expressive, readable, and fast. It has many high-level features added to it. This course will teach you how to use them effectively.

This course will focus on how a modern framework (e.g. Laravel) can be used to quickly get from (a business) idea to an app in production. This module focuses on advanced concepts (testing, API access, optimising for speed/traffic, …) and everything needed for putting an application into production. At the end, students will have a working application on a production server.

This course is designed to equip students with the necessary skills and knowledge to excel in technical job interviews for software engineering positions. Through a combination of lectures, practical exercises, coding challenges, and mock interviews, students will gain a deep understanding of key topics such as data structures and algorithms, system design, behavioral interviews, and more. By the end of the course, students will have acquired essential interview preparation techniques, enhanced their problem-solving abilities, and gained confidence in their technical and communication skills. The course adopts a hands-on approach, providing ample opportunities for practice and feedback to ensure students are well-prepared for real-world job interviews.

The course will provide students with a comprehensive understanding of graph theory and necessary combinatorics. The course covers basic concepts of combinatorics, theoretical fundamentals of graph theory, and algorithms on graphs. Students will gain practical skills and knowledge that can be applied in advanced algorithms and data structure courses.

The first part of the course provides an introduction to combinatorics and probability theory by uncovering their basic notions and techniques. We will learn how to compute the probability of an event and discuss standard probability distributions and their properties. Then, we will move to statistical inference. Topics covered in this part of the course include point estimates, confidence intervals, and hypothesis testing. In the last part of the course, we will learn to model the relationship between several variables with linear regression. Since statistical analysis is typically done on the computer, homework will include not only pen-and-paper exercises but also practical assignments with Python.

This course aims to introduce students to the contemporary state of Machine Learning and Artificial Intelligence. It combines theoretical foundations of Machine Learning algorithms with comprehensive practical assignments. The course covers materials from classical algorithms to Deep Learning approaches and recent achievements in the field of Artificial Intelligence. Programming assignments will be implemented in Python 3.

The course introduces participants to the fundamentals of game development using Unity. Utilising this game engine (or, more precisely, ecosystem), most mobile games are developed. It uses one of the most popular programming languages, C#, and allows projects to be ported to dozens of different platforms. During the course, we will get acquainted with both the editor itself and Unity services that make it easy to integrate multiplayer, analytics, monetization, and various tools for team development into the project. Participants will have the opportunity to study both existing games and develop their own.

In today’s world, where development becomes faster, and companies are rushing their products to the market, it is crucial to apply security practices as early as possible. Software developers must understand security concepts, and cybersecurity engineers should adjust their practices to agile environments. The course covers the modern approach to secure coding from both the development and security point of view.

Creativity is the engine of the 21st century. The contemporary world is full of ideas, concepts, products, and people trying to find their way through this maze. Every start-up has to have not only the idea and (future) product but first of all the story to tell both to the potential investors as well as users, now and future, which brings us to the necessity of creativity and storytelling. Whatever you do, you have to have a story. Another intent of this course is bringing together people of different backgrounds and knowledge, to engage them in working towards a common goal in a new way – through writing a piece of fiction and performing it. Uniting those two fields gives students the possibility to try out their abilities in a safe environment as well as cooperate with other students, bringing in new viewpoints and experiences. This is one of the best ways of establishing teams that have innovation at their core.

This course is designed to equip participants with the necessary skills to cultivate long-lasting leadership influence and make a meaningful impact, even in the face of change, crises, and criticism. While technical or "hard" skills may secure high-potential individuals top positions, this course focuses on the development of "real skills" that enable leaders to build, sustain, and thrive in their leadership roles. The course will empower future leaders with the transformative Three Pillars of Leadership: Awareness, Behavior, and Visibility to take their leadership to the next level.

This course is a business English course for business people. It consists of authentic topics of great interest to everyone involved in or studying international business. The course reflects the latest trends in the business world. If you are into business, the course will greatly improve your ability to communicate in English in a wide range of situations. If you are a student of business, the course will develop the communication skills you need to succeed in a professional environment and will broaden your knowledge of the business world. Everybody studying this course will become more fluent and confident in using the language of business in a variety of contexts.

Pitching to Investors prepares students to craft and deliver concise, high-impact presentations to one of the most demanding audiences: investors. Over three weeks, participants refine their individual presentation style, learn how to frame startup narratives, and master the use of visual storytelling to support funding goals. The course culminates in a polished, investor-grade pitch.

Product Analytics Fundamentals is a comprehensive course that covers the essential elements of analytics, including applied statistics, programming skills, AB-testing, visualization, and understanding data. This course is designed to provide students with a solid foundation in analytics so they can make data-driven decisions. Students will learn how to collect and analyze data using statistical methods, how to extract insights from data, how to conduct AB-testing to optimize product performance, and how to visualize data to communicate insights effectively.

This course has two parts: (1) building and launching a user-facing software product with a special emphasis on understanding user needs, and (2) applying data-driven product development techniques to iteratively improve the product. Students will learn how to transform an idea into software requirements through user research, prototyping, and usability tests, and then they will proceed to launch the MVP version of the product. The students will apply an iterative, data-driven approach to developing a product, integrate event analytics, and run controlled experiments.

Building great tech requires more than great product knowledge and management - it requires a deep understanding of Agile ways of working. “Being agile” is so much more than dev team practices, it is being mentally flexible and highly adaptable to constant change. In this class, students will learn how to navigate the jargon and use agile concepts to achieve terrific results with teams and organizations. In addition to learning about the frameworks scrum and kanban, we will review the philosophical principles behind why these frameworks can be useful, how to modify or recombine them, and how to be sensitive to the human psychology that makes it all work. Through a combination of lectures, small-group work, learning games, workshops, and projects (both structured and self-directed), students will learn to avoid the pitfalls and leverage Agile for their product and business success.