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.

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. 

Creative Writing, Storytelling, and Creative Performing

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.

Leadership

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.

English Business Communication

“You can read a thousand books on how to swim in the ocean. But you have to experience and practice; otherwise, you sink. If you take this course, your pitching and public speaking will never be the same again! You will learn how to properly structure your pitch for investors, and you could easily deliver an elevator pitch. You will learn the principles of managing anxiety and fear from the audience. You will understand how to work with difficult audiences, their objections, and complex questions. You will learn to confidently control your body, voice, and gestures and hold yourself on stage while enjoying what is happening. You will know how to inspire the audience, which will listen to you by holding a breath!

Pitching to Investors

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.

Product Analytics Fundamentals

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.

Technical Product Management

Agile Product Development

The course covers basic Python methods for data analysis: pandas, numpy, scipy, and sklearn, along with advanced techniques for their application. We’ll also review basic integrations of Python with external libraries like xgboost, tensorflow, and pytorch, along with data wrangling and some hyperparameter optimisation methods. Jupyter notebook usage and tricks will also be given as an organic part of the course. At the end of the module, everyone is expected to be ready to work with ssh and git as long as they come up with a simple data wrangling system.

Python Refresher for Masters 

This course focuses on key and in-depth algorithms and data structures that form a modern computer specialist’s toolkit. The computational complexity of algorithms and their comparative analysis will also be discussed. Students will be extensively trained in implementing data structures and algorithms on many problems reducible to the discussed data structures and techniques. The  programs will be tested against carefully prepared test cases using an automated testing system. 

Advanced Algorithms and Data Structures

All contemporary software platforms, whether developed by large corporations (Facebook, Google, OpenAI, etc.) or small businesses, rely on the use of databases or data storage. The foundation of this course is the notion that data storage is an answer or a solution to a problem rather than a technology in and of itself. During this course, we will study what problems modern software can solve with data storage. We will study the whole spectrum of existing data storages, such as classical RDBMS, key-value storages, NOSQL, document storages, column storages, OLAP, vector databases, embedded and serverless databases, and their weak and strong points. Students will learn to understand how to identify requirements for the data storages in a given software system and how to wisely choose a particular data storage (or multiple storages), taking into consideration both business requirements and the chosen software architecture (monolithic, microservice, etc.). We will study all concepts and mental models needed to understand data storage, wisely choose them, and embed them into software - manually, as a manager, or using an LLM, such as ChatGPT.

Data Storages

This course will focus on how a modern framework (e.g. Laravel) can be used to quickly get from (a business) idea to implementation (proof-of-concept, MVP). This module focuses on understanding the core concepts behind modern frameworks and the development of workflows. At the end, students will have a working application on their local development server.

Modern Web Application

Are you searching for a place that teaches you how to start and go through the entire process and content of developing an Android application? Did you know that, currently, there are over three billion Android devices active worldwide that come in the form of smartphones, tablets, watches, TVs’, and even cars? So, if you want to learn about mobile development for Android, look no further. In this course, you’ll start from scratch, and you will build new features for your app in each class, going from the Android basics through the latest libraries, always following the best practices for development. This course will give you a unique opportunity to have your app running everywhere and anywhere. Are you ready? Let’s start!

Mobile Application Development

There is a big difference between coding and engineering, working on a project alone or contributing to a large software system. In this course, we will discuss what software engineering is and how to become one. We will cover all phases of software development from requirements gathering to project maintenance, and discuss processes and best practices. Most of the concepts will be tried in practice using Java and Spring Framework. 

Software Engineering (Java\Spring)

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.

Data Engineering

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.

Modern Software Architectures

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. 

DevOps

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.

Distributed Systems & Clouds

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. 

Parallel and Distributed Computing

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.

Fundamentals of Blockchain

Software Testing, Verification and Validation

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.

Java Programming & OOP

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.

Practical Linux & Scripting Languages

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.

Modern C++ Programming

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.

Modern Web Application 2.0

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.


Job Interview in Software Development

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.

Combinatorics and Graph Theory

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.

Theory of Probability and Statistics

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. 

Machine Learning

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.

Unity Game Development

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.

Secure Software Development

The course represents a deep dive into concepts and frameworks introduced during orientation. It is designed to teach students the process of creating a new venture. It introduces its participants to the concepts, challenges, and tools needed to create a successful new venture. Business model design & validation frameworks are studied and applied to the teams’ startups.

From Zero to Hero

First

Second

Our Computer Science programme has solid roots in mathematics and engineering, while our innovative department optimises the relevance of the programme by including disciplines such as linguistics, psychology, economics, physics and music.


Barcelona

A full-time graduate program to advance expertise and open career opportunities

An innovative format that blends academic learning with professional work experience. Study for the first six months, spend a year in a work placement, and return to complete the final six months of coursework. Perfect for those who wish to balance education with hands-on experience, this structure enhances practical skills and career development.

Applied Master

Computer Science

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A focused one-year program designed for those who want to fully immerse themselves in academic study. This format builds strong theoretical and practical expertise through an intensive and comprehensive curriculum.

Master

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Bangkok

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The Final Capstone Project is the culmination of the Front-End Development program, giving students the opportunity to showcase their ability to design and build polished, user-centered web applications. Working individually or collaboratively, students will apply modern front-end technologies—such as React, Vue, or Angular—alongside tools for responsive design, accessibility, performance optimization, and user experience. Projects may involve real-world client briefs, startup prototypes, or portfolio-driven applications, and should reflect best practices in UI/UX design, code quality, and deployment. The capstone serves as a comprehensive demonstration of students’ readiness to enter the front-end development industry at a professional level.

A career in web design requires different degrees of interaction with developers, sometimes even moving into a frontend developer career. Getting familiar with the basics of programming and acquiring essential knowledge of web development will improve how you communicate with the developer members of your team to create better projects more efficiently. In this course, we will learn the principles of interactivity with code. Using Javascript, HTML, and CSS, a responsive landing page with animations will be created that will challenge our creativity.

Programming Interactivity

This course dives deep into modern JavaScript and TypeScript, equipping students with the advanced skills required to build scalable, maintainable, and high-performance front-end applications. Topics include asynchronous programming, closures, modules, functional patterns, and object-oriented design in JavaScript, alongside robust type systems, interfaces, generics, and tooling in TypeScript. Through real-world exercises and projects, students will learn to write clean, reliable code and adopt best practices that align with professional development standards.

Advanced JavaScript and TypeScript

React is the most used JavaScript framework in the world, and there is a good reason for it: it has managed to create a nice encapsulation of UI components that can easily be reused. It's not only used for web development but also for making mobile apps, games and more. In this course students will learn about React master components, state and props, how to navigate with React Router, and explore styling and animations. Students will take part in practical projects to create dynamic web applications. By the end students will learn how to use the more advanced React, as well as dive into Typescript and the overall React ecosystem.

React Web

This course introduces students to React Native, a powerful framework for building cross-platform mobile applications using JavaScript and React. Students will learn how to design and develop native-quality apps for iOS and Android from a single codebase, covering key concepts such as components, navigation, state management, and device integration. With a hands-on, project-based approach, the course equips future front-end developers with the skills to bring mobile-first experiences to life and extend their reach beyond the browser.

React Native

One of the main user experience factors is performance. Every second that users have to wait dramatically increases their frustration and the likelihood of them giving up and switching to another product or service. Performance is an even more important topic now that most users browse the web on mobile devices and web development revolves more and more around running JavaScript in the browser. During this course, students will learn how browsers work and the different things that can affect performance. It will guide them through the tools and techniques they can use to research and fix performance issues in real-world projects. The goal of this course is to equip the students with the knowledge required to create fast and smooth web experiences.

Web Performance

How do modern product designers and copywriters accomplish a recognizable voice and tone in all the expressions of the different products their company offers? How do UX practitioners achieve a memorable visual projection that is always aligned between teams, products and applications? How do design and engineering teams manage to keep aligned and painlessly bridge the gap between visual expectations and actual implementation? How do UI developers build Agile interfaces without having to reinvent the wheel each time by leveraging a battle-tested set of components designed for maximum performance and interoperability? Last but not least, how can we achieve all this on scale given the fast pace dictated by modern times in products encompassing hundreds or even thousands of pages and screens? Design Systems have emerged as the way to go, being, in short, a complete set of standards intended to manage design on scale using reusable components and patterns.

Design Systems for Interactive Applications

This course explores the most widely used front-end frameworks that power modern web development. Students will learn the core principles behind component-based architecture, reactive data handling, state management, and routing. Through practical projects and comparisons across frameworks, the course helps students understand how to choose and apply the right tools for different use cases—equipping them to build efficient, scalable, and maintainable user interfaces in diverse development environments.

Front-End Frameworks

This course will introduce the students to WebGL and the power of real-time rendering on the web. They will learn the basics of WebGL using the Three.js APIs, starting with simple scenes, lighting, and shadows. We will then delve into more advanced areas, including custom shaders, custom materials, and even some post-processing, building a couple of practical demos from 0 to final product. Throughout the course, students will acquire the skills to animate scenes, add interactivity, and optimize both scenes and models.The course will be in vanilla javascript, no frameworks.

WebGL in Practice

This course provides an overview of the latest technologies used for a modern web programming setup . Students will compare and contrast options, then make an educated decision on a setup that will be used throughout the remainder of the program.

Web Tooling and Modern Setup

This course bridges the gap between coding and architecture, teaching developers how to design scalable, maintainable applications and APIs. Through principles like the Twelve-Factor App and SOLID, hands-on labs, and real-world case studies, participants will learn to evaluate trade-offs (monoliths vs. microservices, REST vs. GraphQL), implement DevOps and observability best practices, and deliver production-ready systems. Ideal for mid-level developers ready to transition from building features to architecting resilient, enterprise-grade solutions.

Designing Apps and APIs

The Deep Dive Into Node.js course endorses Middle and Junior Web Developers to improve their software development skills and qualification in Web Technologies, as well as systematize their knowledge in backend programming in general. After the course developers will be able to write BackEnd applications in JavaScript & TypeScript programming languages and use ideas from modern Node.js frameworks.

Deep Dive Into Node.js

Angular is a powerful framework powered by Google for building dynamic, interactive web applications. Since its launch back in 2016, Angular has become the most comprehensive framework in the industry for building high-performance, feature-rich applications and, nowadays, is used by thousands of companies worldwide, being particularly popular in large corporate environments such as banking and finance. Contrary to other alternatives for building web components, Angular is a full-featured framework, meaning it provides a vast catalog of tools and features out of the box to build literally anything that a modern web application might require, without resourcing to third-party libraries. This obviously entails a very steep learning curve. In this course we will cover all the core entities of Angular and set the ground for building state-of-the-art UI applications combining Angular, RxJS and TypeScript. By the end of the course, students will become seasoned Angular developers fully able to design, implement, and deploy advanced, production-ready e-commerce solutions.

Introduction to Angular

This course will be an introduction to the Vue framework and ecosystem, with a special emphasis on practicing how to build a real world web application. We’ll learn how to create a Vue project, its template syntax, as well as the new Vue 3 composition API. We’ll learn how all of these can be used together to create a modern SPA (Single Page Application) using a component-based development approach. We’ll cover the fundamentals of the Vue Router, so we can navigate between the different views of our app, and we’ll even fetch real external data using API calls. We’ll also have an intro to basic Unit Testing and why it’s important, and we’ll end by learning about the building process and how to deploy our app into production.

Introduction to Vue.js

This course will introduce the open source framework Nuxt3, built on top of Vue3 and Node.js. The goal of Nuxt is to make web development pleasant, simple and powerful, with almost zero configuration efforts. This enables powerful features such as Code Splitting, Server side, Client side or Hybrid rendering, SEO optimization, asynchronous data fetching and more, straight out of the box. We will learn the basics of Nuxt3, then explore different ways of building a website using its extensive ecosystem of plugins and modules, and by the end of the course we will learn how to quickly deploy and update our Nuxt3 project in the cloud.

The Vue Ecosystem

This course explores cutting-edge technologies reshaping the digital experience, including Artificial Intelligence (AI), Extended Reality (XR), and Web3. Designed for front-end developers, it provides practical insights into how these innovations integrate with modern web interfaces, from AI-powered user interactions to immersive XR environments and decentralized applications. Through hands-on projects and real-world case studies, students will learn to prototype and build forward-thinking interfaces that align with the future of web development.

Emerging tech (AI, XR, Web3...)

Creative coding combines programming techniques with artistic expression to create dynamic and interactive digital experiences. This course will introduce students to the fundamentals of creative coding with a beginner-friendly Javascript library. We will learn how to draw and animate visuals with code, using the web browser as a sketchbook. Students will be introduced to computational thinking in driving interactions and design. New programming concepts and creative coding techniques are introduced incrementally each session. By the end of the course, students will integrate techniques learned throughout the course into a final interactive project in the web browser.

Creative Coding

This course is a quick and concentrated introduction to relational databases, from the very beginning to complex problems. It’s giving the students the necessary knowledge for creating their own database in a conscious way, based on strong theoretical principles. It also includes unique materials based on years of hands-on experience. Students will have the opportunity to solve thought-provoking problems related to the real practice of modern business. This course provides an introduction to SQL, the long-accepted standard query language for relational database systems. Students will have an overview of related topics such as data collection, management, and analysis. Other types of data storage will also be discussed. This course provides a comprehensive overview of MySQL, one of the leading database management systems.

Basics of Databases

This course introduces students to the fundamentals of typography and layout design through hands-on workshops. Over the course of three weeks, students will learn the principles of typography and how to apply effective layouts to a poster and a website. Students will learn how to inspire creativity and generate ideas, practice researching and mind-mapping, apply the principles of typography and layout design to create cohesive designs, both physical and digital, and develop practical skills for using design software and tools.

Intro to Typography, Grids & Layouts

This course explains how a modern framework (e.g. Laravel) is used to quickly get from (a business) idea to implementation (proof-of-concept, MVP). The course focuses on understanding the core concepts behind modern frameworks and the workflow development. At the end, students will have a working application (based on their own idea) on a local development server.

Motion Design is a discipline that takes graphic design principles and applies them to video production through the use of animation and visual effects. From the analogue experimental films of the 1920s to the digital interfaces we interact with today, the evolution of motion media has always been closely tied to that of technology. Thus, it is an exciting field that combines animation and graphic design principles with new cutting-edge technologies.

Applications of Motion Design

3D technology has been around since the 1970s, but it's only been in the last decade that it's become accessible to people other than technically oriented professionals. With the availability of low-cost and powerful 3D tools, the design industry has seen an emergence of 3D designers in various fields such as motion design, UI/UX, experiential design, and architecture, to name a few. Although already in high demand, more industries will be looking for designers proficient in 3D as new platforms emerge that are capable of handling 3D content.

3D for Designers

This course bridges the gap between technical training and professional practice, helping students understand what it means to work as a developer in real-world environments. Covering essential topics such as agile workflows, team collaboration, version control, code reviews, and communication with stakeholders, the course prepares students for the day-to-day realities of a development career. Through simulations, mentorship, and portfolio-building, students gain the soft and technical skills needed to succeed as front-end professionals in modern tech teams.

Development as a Job

The client project rounds out the program and the course begins with each student presenting a brief outlining the subject, scope, and purpose of the project. As the project progresses, teams give tutorials demonstrating their methods and progress, and the project culminates with a presentation to the entire program base. Some client briefs are developed in conjunction with real external partners. Others are internal.

Client Project

Our Front-end Development programme is where programming and creativity collide to build intricate, inventive and interesting web interfaces by applying animations and motions, and advanced web programming, including JavaScript, WebGL and CSS. 

Front-end Development

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The Final Capstone Project serves as the culmination of the Data Science Master’s program, allowing students to apply the full range of skills and knowledge they have acquired to solve a real-world problem. Working individually or in teams, students will design and implement data-driven solutions using advanced analytical methods, machine learning models, and visualization tools. Projects may be industry-partnered or research-focused, and they are expected to demonstrate technical depth, business relevance, and clear communication of insights. The capstone provides a platform for students to showcase their readiness for data science roles in industry, academia, or entrepreneurship.

Understanding Machine Learning requires fundamental knowledge in mathematical areas such as linear algebra, calculus, optimization, probability and statistics. The Math Refresher course focuses, through practical examples and assignments, on revising the necessary topics that will allow students to join future Machine Learning courses and gain thorough knowledge about modern Artificial Intelligence.

Math Refresher for Masters

This advanced course aims to give students knowledge about statistical analysis methods with a focus on applications. We’ll consider various data science tasks that require statistics, study the taxonomy of statistical methods, learn their requirements and limitations, and apply them to different real-world problems and datasets using R.

Statistical Data Analysis

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. This course is accompanied by Deep Learning in Applications course, which brings the most recent achievements in the field and their applications. Programming assignments will be implemented in Python 3. PyTorch framework will be used for Deep Learning practice.

Masters Machine Learning

State-of-the-art approaches in different domains of artificial intelligence are based on deep learning techniques (e.g. computer vision, natural language processing, reinforcement learning, etc.). Deep neural architectures show great potential and promise even better results, so now is definitely the time to explore this field. In this course, we will start from the basics and rapidly dive into the latest results in deep learning, focusing on the NLP and RL domains. This course focuses both on practical skills and theoretical background to provide the students with thorough theoretical knowledge and the ability to work on their own in the deep learning area. This course accompanies the Master’s Machine Learning course. Programming assignments will be implemented in Python 3. The PyTorch framework will be used for deep learning practice.

Deep Learning in Applications

Machine Learning is a powerful tool that is widely used today and is specified in computer science education, while Statistics and Probability are traditionally studied in mathematical departments.  Nevertheless, there is a strong relationship between these theories, and it is desirable to be aware of both general principles and differences in approaches. Indeed, machine learning uses mathematical and/or statistical models to gain an overview of the data to make predictions. The novel contributions in data mining are mostly informal and usually linked with the Bayesian point of view on statistics. But, probability theory itself is more than just Kolmogorov's axiomatic approach or Bayesian reasoning. This course tries to show the existing diversity of approaches while staying within classical Kolmogorov's probability theory. The necessary classical theoretical material will be explained as well. We aim to consider several paradoxical situations that arise in practice. Most examples will be taken from natural sciences and simple situations in data analysis. The outcome is expected to be practical training in understanding the popular statistical models and the ability to critically read a professional text.

Probability and Statistics: Theory and Implementation

Deep Learning, i.e., training multilayered neural architectures, was one of the oldest tools in machine learning but has revolutionized the industry over the last decade. In this course, we begin with the fundamentals of deep learning and then proceed to modern architectures related to basic computer vision problems: image classification, object detection, segmentation, and others. Modern computer vision is almost entirely based on deep convolutional neural networks, so this is a natural fit that lets us explore interesting architectures, while at the same time staying focused and not going into too wide of a survey of the entire field of deep learning. Computer vision is also a key element in robotics: vision systems are necessary for navigation, localization and mapping, and scene understanding, which are all key problems for creating industrial and home robots.

Neural Networks and Computer Vision

Nowadays, machine learning technologies are widely used in various fields such as retail, mass media, PR and marketing, banking, telecommunications, manufacturing, science and many others. Even though it is very important to use the appropriate methods in every project, often the choice of a particular machine learning algorithm does not play a key role. Most of the time, the most important factors are the appropriate formulation of the problem from the business point of view, the correct mathematical formalization of the problem, and an accurate assessment of the potential economic effect. In the course, we will learn the structure and the lifecycle of the machine learning-based project and cover topics ranging from the problem statement definition to the final model quality assessment, as well as an estimation of the economic effect.

Industrial Machine Learning

In three weeks, we're going to learn the principles of ML System Design and apply it to build an application that we and other people can use. This will include some amount of software development, product thinking, and machine learning. ML will be the backbone of our product, SE will be the means to make it work, and product thinking will lead us through. We’ll start with an idea, outline user scenarios an app should fulfil, proceed with system design, and dive into implementation. We’ll use the app ourselves, collect and analyse our feedback, work on improving the user experience, and finally publish this to the outside world to get real feedback and reflect on our experience. This class will help you understand how complex ML systems are built and will be part of your portfolio that you can showcase and reason about.

ML System Design 

This three-week hands-on course provides a jumpstart into design and development of modern MLOps platforms. From initial project scoping to exploratory analysis and data engineering, from feature engineering to model training, to ML pipelines and CI/CD automation, productization, monitoring, and operations. You are going to create an ML project in Amazon SageMaker Studio and go through all stages of development such as data exploration, interactive experimentation, setting up MLOps pipelines, and finally deliver the project into production. You’ll learn how to work with a feature store, model registry, pipelines, model and data monitor, and CI/CD projects. Through this course, you will work with Amazon SageMaker to get you inspired to implement your own MLOps solution. The course provides recommended patterns and practical architecture blueprints for real-world ML projects. The course gives you an overview of the industry-standard ML platforms and MLOps products, like MLflow, Apache Airflow, H20, DataIKU. As the course's main deliverable, you’re required to implement an end-to-end ML project with the main components of MLOps, such as reproducible ML pipelines, scalable data processing and model training, model registry, experiment tracking, observability, and event-driven workflows.

Development of Modern MLOps Platforms

During this course, students will master and sharpen their knowledge of basic technologies of the modern Big Data landscape, namely: HDFS, MapReduce, Hive, Spark (especially real-time instruments like Spark Streaming and Kafka Streams), and NoSQL frameworks like HBase and Cassandra. Of particular interest for the course will be the subject of efficient data warehousing using Hive and Spark. Under the teacher’s supervision, students will study the intricacies of the system’s internals and their applications. They will also learn distributed file systems, the purpose of their existence, and the ways to apply them. The learners will also practice using the MapReduce and Spark frameworks, a workhorse for many modern Big Data applications. The key element of this course is to apply knowledge into practice, and to process texts and solve sample business cases. The participants will deal with Spark, the next-generation computational framework, from its basic concepts up to advanced applications made to squeeze maximum performance. Finally, they will get acquainted with the modern NoSQL frameworks like HBase and Cassandra.

Big Data Technology

This course is about modeling real-world problems with optimization and numerical linear algebra tools and how to solve them. We will discuss the most important algorithms from NLA, classical convex optimization, and stochastic optimization methods which are crucial for efficient training of large neural networks. The selected topics will be discussed from both theoretical and practical perspectives. In particular, practice sessions will include introducing the standard open-source packages for solving considered problems. Every block of the course will be equipped with multiple practical demos and home assignments that help students go deeper into the discussed topics.  

Optimization Methods

This course focuses on giving students the skills required to participate and excel in real-world ML tasks by practicing in ML competitions. The syllabus is designed to teach students how to solve ML problems going step-by-step. Students will create a framework for their solutions and test the problem by creating simple no-ML solutions, by preparing Python scripts, building Docker images, or deploying models. The course covers several topics, such as ML metrics understanding, optimization, EDA, feature generation, ensembling models, and debugging solutions.

Practicing DS Skills in ML Competitions

Because the world is overwhelmed with information and people need automatic systems to filter and rank relevant information, recommendation systems are widespread technology today. We see them in video hosting services, social networks, online shops, etc. Recommendation systems are here to solve this task and save people’s time and effort on information retrieval. This course aims to introduce students to a full spectrum of recommendation systems tool belts, starting from simple user-based collaborative filtering to sequential recommendations based on transformers. Materials include both a theoretical part (matrix decompositions, SLIM) and a practical part addressing production techniques such as knn indexes, embedding quantization, and scalable item-to-item service.

Recommendation Systems

In our data-driven world, the technological revolution has simplified the generation and collection of data across various aspects of our personal, social, and professional lives. The interpretation of this data empowers us to make informed decisions, generate ideas, recognize trends, and either validate or challenge our beliefs. This course aims to equip you with effective techniques for visualizing data, enabling you to comprehend and effectively communicate your findings to others, whether through a research paper, a corporate meeting, or a landing webpage. Additionally, we will cultivate a critical approach to data, enabling us to identify both its limitations and strengths.

Data: Interpretation, Visualization & Presentation

Large Language Models

The course gives a 360° view of time series analysis methods and real-world problems. The main focus is on forecasting, with a range of solutions from simple averaging to NN-based sequential models. The course also covers unsupervised learning problems such as clustering and anomaly detection, as well as causal inference on time series data.

Time Series Analysis

Job Interview in AI & Data Analysis

This course focuses on key and in-depth algorithms and data structures that form a modern computer specialist’s toolkit. The computational complexity of algorithms and their comparative analysis will also be discussed. Students will be extensively trained in implementing data structures and algorithms on many problems reducible to the discussed data structures and techniques. The programs will be tested against carefully prepared test cases using an automated testing system. 

Cloud technologies have become increasingly prevalent in the business world, providing companies with the opportunity to deploy products and infrastructure with greater speed and scalability than ever before. However, clouds bring new security risks, threats, and tools that organizations must be prepared to tackle. Why is cloud security so different from “in-house” infrastructure and product security? How does cloud migration impact security risks? In this class, we get to know cloud technologies from a security point of view, and students will learn how to assess security risks and how to protect our products and infrastructure in clouds. 

Cloud Security

In this course, students will learn the basic principles of technological entrepreneurship. Students will be able to create a Minimal Viable Prototype (MVP) by applying principles of paper prototyping, create and implement a customer development pipeline and  evaluate a product’s market fit and unit economics. They will will also learn how to create a pitch deck for their project from scratch, evaluate the quality of the early-stage venture capital, and implement a fund-raising plan. By the end of the course, students will have a good understanding of the overall properties of venture capital markets.

Entrepreneurship for Engineers

While the world holds its breath in anticipation of the Age of the Petabyte, we’re getting ready for the Age of the Exabyte. The Data Science programme is the first dedicated BSc programme in the world.

Data Science

bcn-ds-applied-master

bcn-ds-master

bkk-ds-master

The Final Capstone Project marks the culmination of the Cybersecurity Master’s program, enabling students to integrate and apply their knowledge to address a real-world security challenge. Working individually or in teams, students will design, implement, and evaluate a comprehensive cybersecurity solution or investigation—such as developing secure systems, conducting penetration tests, performing forensic analysis, or assessing organizational risks. Projects may be conducted in collaboration with industry partners, government agencies, or research institutions. The capstone emphasizes technical proficiency, critical thinking, and ethical responsibility, preparing students for advanced roles in cybersecurity operations, consulting, or research.

The course serves as a technology bootcamp giving students quick introduction to technologies foundational to cybersecurity programme including programming, operating systems, networks and application development.

IT Technology Essentials

The course examines the main aspects of building an Information Security Management System of modern Enterprises. The course focuses on eight major security domains, ranging from Risk Management to Software Development Security in the context of three areas - People, Process and Technologies. We analyze the main risks and threats Enterprise Cybersecurity and risk mitigation using predictive, preventive, detective and corrective security controls. An overview of modern security toolkit beginning from Next Generation Firewalls and Antiviruses and finishing with publishing SandBox and User Behavior Analytics will be presented.

Enterprise Security Architecture

This course provides essential information about cybersecurity assessment of information systems and applications. Different approaches, such as compliance audit and certification, penetration testing and Red Team exercises will be discussed. You will learn practical cases of compliance assessment according international standards such as ISO/IEC 15408, ISO/IEC 27002, PCI DSS, PA DSS. The course is full of practical methods. It provides spacious coverage of tools and techniques that are used in penetration testing and ethical hacking.

Security Assessment, Penetration Testing and Audit

This course will fully introduce attendees to incident response and digital forensics. The hands-on, practice-oriented format of this course will allow students to obtain the required skills to conduct the cycle of detection, response and analysis of compromised systems, in both live and postmortem situations, with best practices to discover different cyber attacks. We will study various tools to perform evidence collection and live analysis, and go through different techniques to analyse volatile and nonvolatile data. We will learn what approaches and tools can be used and how to perform static and dynamic analysis of malicious executables for multiple platforms – Windows, Linux, MacOS and Android. Vulnerabilities and exploits analysis, reverse engineering byte-code and script languages, automating reverse engineering tasks, unpacking, deobfuscating and dynamic binary instrumentation will be dicussed.

Malware Analysis, Digital Forensic and Incident Response

Information security is a complex of processes, people and technologies, and their mutual effectiveness defines efficiency of overall Infosecurity program in the enterprise. Security operations is the crucial glue between these three components and Security operations center is its implementation in practice. During the module classes students get acquainted with modern attack tactics, techniques and procedures and how they can be addressed by security operations staff. In lab classes students will get practical skills in attack detection and investigation.

Security Operations Center and Cyber Threat Hunting

The course covers different aspects of cybersecurity and cyber resilience of systems and applications based on Artificial Intelligence and Machine Learning. We will learn cybersecurity of AI in various aspects: from threat modelling and requirements development to vulnerability research and practical attacks against AI models such as Adversarial ML, Model Backdooring etc.

Artificial Intelligence Security

Cybersecurity management is the management of risk, specifically the risks to information assets assessed by an organization. This course explores the role of governance, risk management, and compliance (GRC) as part of the cybersecurity governance process, including key planning, policy, and technology administration functions to support the protection of critical information assets. The course will give you an insight into current laws and regulations such as GDPR, ISO / IEC 27002, PCI DSS, CIIP, HIPPA. Understanding the basics of implementing a risk management strategy will help manage policies, create controls, and measure the effectiveness of controls. In this course, you will learn how to customize processes to ensure compliance with the norms of behavior in your organization, including risk analysis, ensuring a systematic culture of documentation, review, audits, remediation, control, accountability and authority.

Cyber Governance, Risk and Compliance

The module covers various aspects of cybersecurity and cyber resilience of mobile and telecommunication networks, financial institutions and industrial systems. During this course we will learn cybersecurity in various aspects: from analyzing risks and the requirements of international and industry standards to vulnerability research in incident response in ICS/SCADA, ATM and SS7 telecom networks.

Critical Information Infrastructure Cyber Resilience

The course is dedicated to all the most relevant topics of modern cryptography. It covers the full spectre of security notions and corresponding adversary models that define the theoretical and practical properties of cryptographic mechanisms that are currently used. All widely used primitives, algorithms and protocols are observed in the course - together with reviewing of their vulnerabilities, theoretical and practical attacks and most important results of security assessment. The two most important protocols - IPsec and TLS - are deeply studied, together with the history of attacks and countermeasures against them. The final part of the course is dedicated to the problems of practical applications of cryptography, including the most discussed topics, such as blockchain technologies, IoT, backdoors and security of implementations (HSMs, smart cards and tokens, digital signature servers).

Modern Cryptography

The module covers various aspects of cybersecurity and cyber resilience of modern Data Centres, Cloud and Big Data Platforms. During this course we will learn cybersecurity in various aspects: from analysing risks and the requirements of international and industry standards to vulnerability research and practical attacks against cloud applications.

Datacenter and Cloud Security

This course provides essential information about the security development lifecycle (SDLC). You will learn about the process of SDLC, its practices and how to apply them to your development method. By learning about SDLC you will be able to improve development methods process in order to better integrate security aspects with the goal of built in security. We will discuss secure design for multiple SDLC models, software architecture considerations, and design patterns. You’ll understand how to identify and implement secure design when considering databases, UML, unit testing, and ethics. Different technical tools, such as SAST, DAST and CI and CD pipeline security tools will be introduced.

Security goals cannot be addressed by technical means alone. Significant aspect of protection comes down to the awareness, behaviour and capabilities of the people involved. In this course we will discuss different aspects of information security culture such as user acceptance of security policies and technologies, usable security, social engineering and other human-related risks to help to prepare and execute efficient cybersecurity program.

Security Program Management, Social Engineering and Security Awareness

The aim of the course is a deep immersion in various aspects of the security of modern mobile technologies. The course consists of two main parts. The first part focuses on mobile communications, from WiFi and Bluetooth to the telecommunications networks of 4G and 5G carriers. Vulnerabilities of systems and protocols and their possible impact on systems using mobile networks are discussed in detail. The second part focuses on the security of mobile devices such as mobile phones, IoT devices, etc. The security model of Android and iOS operating systems and approaches to secure application development will be considered.

Mobile & Wireless Network Security

Hardware is an essential part of modern IT technology. The course examines how defense mechanisms are implemented at the hardware level. The main approaches to the design of secure systems and the main approaches to the analysis of the security of equipment will be considered. Special attention will be paid to various IoT devices and their security.

Hardware Security

The course is aimed at a detailed analysis of the security system of operating systems of the Windows and Linux families. It covers local, network and group configurations such as Domains and Security Policies. Particular attention is paid to the development of Security Templates and security assessment of host configuration. As a result of the course, you will have a deep understanding of the built-in defense mechanisms of modern operating systems and be able to make the most of these opportunities to implement the Bastion Host concept.

Host Security Hardening

The course is focused on improving knowledge in the field of security of modern network technologies based on the concept of Zero-Trust Networks. It covers Network configuration management, VLANs, micro segmentation, DNS Security, SMTP, Web App, DDoS protection, routing security, including BGP. Special attention is paid to network security in the virtualized environment and SD-WAN technology.

Network Security Advanced

The course is intended to be a full-size course covering the Python programming language. We are going to cover basic constructions of the language, the design principles of the language, how different syntax sugar in the language works, how to work with lazy computations and what do you need to know to write production code in Python. The course is intended for the people who already had an introductory course on Python or familiar with one of the other programming languages like Java or C++.

Python Programming

Harbour.Space students gain knowledge of the most sophisticated encryption methods and threat detection techniques under the capable leadership of cyber security experts. 

Programmes

Technology

Computer Science

Data Science

Cyber Security

Front-end Development

Applied Data and Computer Science

Artificial and Machine Intelligence

Creative

Interaction Design

High-tech Entrepreneurship

Digital Marketing

Fintech

Product Management

Digital Transformation