Программы онлайн-образования

бакалавриата

магистратуры

дополнительного и бизнес-образования

довузовской подготовки

онлайн-образования

НИУ ВШЭ

The course is devoted to the usage of computer vision libraries like OpenCV in 2d image processing. The course includes sections of image filtering and thresholding, edge/corner/interest point detection, local and global descriptors, video tracking. Aim of the course: • Learning the main algorithms of traditional image processing • Thorough understanding of benefits and limitations of traditional image processing Practical Learning Outcomes expected: • Mastering programming skills of image processing with computer vision libraries

The Large Hadron Collider (LHC) is the largest data generation machine for the time being. It doesn’t produce the big data, the data is gigantic. Just one of the four experiments generates thousands gigabytes per second. The intensity of data flow is only going to be increased over the time. So the data processing techniques have to be quite sophisticated and unique. In this online course we’ll introduce students into the main concepts of the Physics behind those data flow so the main puzzles of the Universe Physicists are seeking answers for will be much more transparent. Of course we will scrutinize the major stages of the data processing pipelines, and focus on the role of the Machine Learning techniques for such tasks as track pattern recognition, particle identification, online real-time processing (triggers) and search for very rare decays. The assignments of this course will give you opportunity to apply your skills in the search for the New Physics using advanced data analysis techniques. Upon the completion of the course you will understand both the principles of the Experimental Physics and Machine Learning much better.

You will master your skills by solving a wide variety of real-world problems like image captioning and automatic game playing throughout the course projects. You will gain the hands-on experience of applying advanced machine learning techniques that provide the foundation to the current state-of-the art in AI

During the course "Mathematics for ComputerVision", students will complete the project “Use matrix filters and set functions to detect the edges of an object in the image”. During the working at this project, students using Python programming language (Jupiter's notebook), will implement the application that performs the required functions. All operations will have to be implemented independently without using third-party libraries. At the course "Object-oriented Programming", students will apply the acquired skills and develop an application in C++ programming language. At the course "2D Image Processing", students will design the application -Development of C++ application that use OpenCV to detect and count coins in a given image. In addition, they will test the quality of created detector application

People apply Bayesian methods in many areas: from game development to drug discovery. They give superpowers to many machine learning algorithms: handling missing data, extracting much more information from small datasets. Bayesian methods also allow us to estimate uncertainty in predictions, which is a desirable feature for fields like medicine. When applied to deep learning, Bayesian methods allow you to compress your models a hundred folds, and automatically tune hyperparameters, saving your time and money. In this online HSE course we will discuss the basics of Bayesian methods: from how to define a probabilistic model to how to make predictions from it. We will see how one can automate this workflow and how to speed it up using some advanced techniques. We will also see applications of Bayesian methods to deep learning and how to generate new images with it. We will see how new drugs that cure severe diseases can be found with Bayesian methods.

This course is designed to open the doors of the world of business analytics. Nowadays a lot of organizations make their decisions based on data-driven approach. How to make the right decision? Which methods are used in multinational companies? This course is about demonstrating the diversity of real cases and applications of methods, techniques, and theories in various areas. Each week of this course is a piece of a puzzle where you will meet different experts from the industry who will share with you best practices from the market. Bringing together all the pieces you will understand the key definitions used in business analytics and will learn about data analytics techniques which can be applied in marketing, sales, PR, HR, and finance. “Business Analytics: Diversity of Practical Applications” aims to help you to navigate in the variety of career opportunities which are opened for business analysts.

This online course is about the specific conditions and the most efficient practical approaches to succeed in emerging markets. You will learn first-hand instruments, cases and thinking patterns to grow a business strong against uncertainties and competition. The HSE course aims to transfer the fundamental knowledge and to form the basic competencies necessary for the development and the implementation of a business strategy in an emerging market. The students are going to improve their analyzing, decision making, and planning skills as well as the ability to recognize strategic opportunities and threats. The course requires the knowledge of basic economics concepts as the pre-requisite. It is preferable that the students have some practical entrepreneurial or marketing experience, but this is not obligatory. The course has a distinct stress to the practice of strategic management. Although a few fundamental theories are mentioned, the bulk of the ideas are based on simple though efficient applied model that are easy to understand and convenient to use. The multitude of examples and stories from the personal consulting and managerial experience of the author are the hallmark of the course. The author’s original drawings make the key concepts well memorable ad cozy to deal with. The course is for: 1. Management and business students 2. Marketing professionals 3. Sales managers 4. Top managers This distant course consists of 8 topics with 5-6 videos each. After each topic you will be offered to pass a short multiple-choice test. Пререквизиты: знание английского языка

Our online course aims to provide necessary background in Calculus sufficient for up-following Data Science courses. Course starts with a basic introduction to concepts concerning functional mappings. Later students are assumed to study limits (in case of sequences, single- and multivariate functions), differentiability (once again starting from single variable up to multiple cases), integration, thus sequentially building up a base for the basic optimisation. To provide an understanding of the practical skills set being taught, the course introduces the final programming project considering the usage of optimisation routine in machine learning. Additional materials provided during the course include interactive plots in GeoGebra environment used during lectures, bonus reading materials with more general methods and more complicated basis for discussed themes. Трудоемкость:3 ЗЕ. 12 заданий с автоматическим оцениванием

Online classes are created to tell about principal theories of interaction sphere and its realistic administration. Our course is targeted at academical access, methods of investigation, actual cases, examinations and study. This program can be useful for bachelors in different areas, for people who desires to update the knowledge to be more theoretical oriented. The lessons are highly recommended for all experts in advertising, marketing, public relations, social and mass media. Communication is all around, there is no interaction without cooperation, everyone needs to apply it. Thus, regardless of your education during the program you will gain information in different fields of communication: from interpersonal to indirect. The main purpose of this program is to give the abstract base for communication learning and applied administration. Finally, inquiring public will know the concept of communication, the main points of it and also will be informed about the main figures in various spheres of connection. We will talk about the main aspects of communication: interpersonal, group, mass and indirect. We will concern the point how global corporations can use communication to achieve business success and take into account that factors like management skills as well as media competence are particularly important in the highly developed world. And we will definitely study throughout the program why and what for communication influences so much on every spheres of life. Трудоемксоть: 2 ЗЕ. 9 заданий с автоматическим оцениванием, 1 задание на взаимную проверку Пререквизиты: знание английского языка

Despite a large variety of different courses on analytics, the courses that offer a broad overview of the field are rare. From practice of teaching statistics, it became clear that it is difficult for learners to put together a broad field map if they have taken only a few of the different topics on analytical tools. As a result, they do not see the overall picture of everything that the field of data analysis has to offer. This course is designed to fill this gap. It is a survey course on state-of-the-art in interdisciplinary methods of data analysis, applicable to business and academia alike. Unlike other statistical courses, which focus on specific methods, this course will focus on the broader areas within statistics and data analytics. There are five major topics it will cover. It will start with the root of it all - the data – and some of the problems with the data. Then it will move through the contemporary approaches to descriptive, inferential, predictive and prescriptive analytics. Within each broader topic, the course will offer the theoretical foundation behind the methods without focusing too much on the mathematics. It will provide historical references, examples, explanations and case studies to illustrate the main concepts within each broader topic. In doing so, it will introduce the applied, problem-based approach to using specific tools. Then, it will discuss some of the specific of a particular approach. Overall, after taking this course, the students will get a good understanding of the state-of-the-art tools that the field of data analysis currently has to offer. The course consists of two parts. There is a review part with six lectures, providing the description of the major data analysis areas. This 6-lecture course is offered as part of the “Network analytics for business” specialization. For students of the “Master of data and network analytics” program, there are six additional lectures on specific topics. They are designed to illustrate some of the specific state-of-the-art approaches within the broader areas.

Corporate Finance course develops a conceptual framework to analyze the broad area of corporate financial decisions (investing, financing, payout, strategic deals). It provides the prevailing empirical evidence for the motives and impact of corporate performance in developed and emerging capital markets. The online course covers topics in corporate financial architecture (e.g. governance issues, board’s role), ownership structure, and corporate performance of a firm. Corporate Finance course develops a conceptual framework to analyze the broad area of corporate financial decisions (investing, financing, payout, strategic deals). It provides the prevailing empirical evidence for the motives and impact of corporate performance in developed and emerging capital markets. The online course covers topics in corporate financial architecture (e.g. governance issues, board’s role), ownership structure, and corporate performance of a firm. During the Corporate Finance course, you will gain insight into both theoretical and practical aspects of Corporate Finance, including financing and capital structure of organization, its life-cycle stage and payout policy decisions. You will learn about the dilemmas of executives and shareholders and such recent trends as knowledge firms and zero debt capital structure.

This online course provides an overview of current pedagogical, psychological and philosophical theories and approaches, accompanied by a large practical block on the design of personalized learning environment in the classroom. The broad goal of this course is to spread relevant pedagogical solutions to a wide range of teachers. An important element of the course is the practical block, providing clearly presented recommendations and guidelines for creating personalized learning environment in the classroom, including tools and techniques to provide individualized instruction. Changes in professional style do not occur revolutionarily, it is an evolutionary process. Each week students would be given lectures, readings and practical tasks to redesign their lesson plans to make them more personalized and student-friendly. Each lesson gives an opportunity to implement methods in their daily teaching routine or to redesign the whole teaching process. This distance course is for: – Students of pedagogical education programs (Bachelor's degree, Master's degree) – Middle and High School Teachers – University Educators – Tutors and instructors in social and educational enterprises – Tutors

Main objective of this online course is a) to understand the development of the Cultural and Creative Industries as an idea and as a concept and b) to identify the key changes of Cultural and Creative Industries in relation to contemporary digital connected world. Another important task of this course is to provide the deep understanding of the differences between cultural and symbolic meaning products (such as films, recorded music, book and periodicals, online media content, etc.) and other kinds of goods. This HSE course will help the students to: • Identify the main peculiarities of cultural and symbolic goods in comparison to other branches of economy in terms of production chain, risks, different stages of production. • Be able to analyze cultural products and symbolic goods from the organizational, economic, business model perspectives • Be able to invent new business models and analyze cultural products and assess their productions risk • Be able to analyze cultural policies and creative industries/clusters policies You need basic analytical skills and general knowledge in philosophy, social sciences (sociology, anthropology political science. This course will be especially useful for art students (who want to understand the organizational production of symbolic goods) or for the students from economics and management (who want to get an alternative view on the peculiarities of cultural production The main prerequisite to this distant course is to be able to produce analytical texts in humanities. In general the course fits all the students of master level interested in peculiarities of media and cultural economy and management. This course is not recommended to those who: • Analyse any market or industry only in microeconomic perspective (supply and demand, competition, etc.). This course is not about market but about peculiarities of the symbolic goods; • Try to interpret culture only in terms of marketing and management (i.e. culture is considered like a simple good to be sold to the consumer). This course considers the culture broader as a human agency to produce meanings of everyday life. That’s why cultural goods are different and can not be interpreted exclusively in terms of consumption and need a certain level of state support • Try to interpret culture like pure “art” and consequently totally exclude the organizational aspect of the culture. This course uses a large number of concepts coming from different fields of science: political economy of communications, cultural studies, sociology etc. Some aspects of the course are commented by known scholars in this field such as David Hesmondhalgh (Universyt of Leeds), Phillipe Bouquillion (University Paris 13 Nord), Bernard Miege (Grenoble Alpes University)

Обучение построено на изучении не только соответствующих математических моделей и алгоритмов, но и на рассмотрении примеров их реального применения в этой области. Это позволяет студентам изучить весь жизненный цикл аналитической модели, начиная с этапа формирования требований, подготовки данных и заканчивая этапом внедрения/эксплуатации

Цель данного междисциплинарного курса – получение студентами представления об особенностях задач анализа данных в бизнесе с учетом специфики разных отраслей экономики, знакомство с конкретными примерами бизнес-задач, использующих анализ клиентских данных. В рамках курса студенты и слушатели научатся при помощи визуального интерфейса и кода строить прогнозные модели и делать анализ клиентских и тектовых данных

This specialization gives an introduction to reinforcement learning, natural language understanding, computer vision. Upon completion of 4 courses you will be able to apply modern machine learning methods in enterprise and understand the caveats of real-world data and settings

Deep learning added a huge boost to the already rapidly developing field of computer vision. With deep learning, a lot of new applications of computer vision techniques have been introduced and are now becoming parts of our everyday lives. These include face recognition and indexing, photo stylization or machine vision in self-driving cars. The goal of this online course is to introduce students to computer vision, starting from basics and then turning to more modern deep learning models. We will cover both image and video recognition, including image classification and annotation, object recognition and image search, various object detection techniques, motion estimation, object tracking in video, human action recognition, and finally image stylization, editing and new image generation. In the course project, students will learn how to build face recognition and manipulation system to understand the internal mechanics of this technology, probably the most renown and often demonstrated in movies and TV-shows example of computer vision and AI.

The online course in Digital Literacy offered by HSE University was designed to help the students acquire various competencies that will enable them to safely and effectively use digital technologies and Internet resources in an academic and professional context. The Digital Literacy course is a step-by-step guide covering various topics that will help you find your way around in the digital environment. We did our best to include the most essential insights and skills that can guarantee your success in the world of information technology. And we packed them all into one course. This course highlights some aspects that may seem simple but far from self-evident, like the parameters to keep in mind when looking for a new computer, the right ways to prevent online data theft, the inner workings of the Internet, and the laws that govern online activities. It also covers the basics of handling data and provides essential skills required for working with information sources, customizing table design, and doing simple analytics. You will find this extremely helpful not only for your time spent at the university but also at your future job. To take part in the course, you will need a computer with Internet access and some free memory to install the required software, a Google account, and a pre-installed MS Office package.

This course will help you to navigate ambiguity in definitions of "Smart City". You can review successful cases and practices of different approaches to transformation management, determine the potential of your city in the digital transformation, as well as find useful practical advices on search for funding of various digital projects in your city. In addition, lecturers introduce you with formation of Smart City structure and infrastructure from the officials’ point of view. If you are already an expert in the field of Smart Cities, the course will give you the opportunity to assess your strengths and to improve knowledge in this field. You will gain additional skills in managing digital transformation programs with real examples, as well as you will be acquainted with communication methods and marketing of government projects. Трудоемксоть: 2 ЗЕ. 6заданий с автоматическим оцениванием и 2 задания на взаимную проверку Пререквизиты: знание английского языка

The main goal of this online course is to introduce topics in Discrete Mathematics relevant to Data Analysis. We will start with a brief introduction to combinatorics, the branch of mathematics that studies how to count. Basics of this topic are critical for anyone working in Data Analysis or Computer Science. We will illustrate new knowledge, for example, by counting the number of features in data or by estimating the time required for a Python program to run. Next, we will apply our knowledge in combinatorics to study basic Probability Theory. Probability is everywhere in Data Analysis and we will study it in much more details later. Our goals for probability section in this course will be to give initial flavor of this field. Finally, we will study the combinatorial structure that is the most relevant for Data Analysis, namely graphs. Graphs can be found everywhere around us and we will provide you with numerous examples. We will mainly concentrate in this course on the graphs of social networks. We will provide you with relevant notions from the graph theory, illustrate them on the graphs of social networks and will study their basic properties. In the end of the course we will have a project related to social network graphs. As prerequisites we assume only basic math (e.g., we expect you to know what is a square or how to add fractions), basic programming in Python (functions, loops, recursion), common sense and curiosity. Our intended audience are all people that work or plan to work in Data Analysis, starting from motivated high school students. Пререквизиты: знание английского языка