Наука о данных: от данных к продукту
Наука о данных: от данных к продукту
Центр Непрерывного образования ТСИ предлагает Вам программу дополнительного профессионального образования "Наука о данных: от данных к продукту".
|Начало программы: Февраль, 2020|
|Занятия будут проводиться: по пятницам, 18.00-21.30 и по субботам, 10.00-13.30|
|Язык обучения: английский или русский|
|Название курса: Executive programme: Data Science: from Data to Product|
|Цена курса||Оплатить 1300 EUR|
|Цена студентам TSI, членам Ассоциации выпускников TSI и Корпоративным клиентам||Оплатить 1000 EUR|
[ВАЖНО] Перед оплатой убедитесь, укомплектована ли группа.
Информация о курсе
The 70 ac. hours course provided by Transport and Telecommunication Institute (TTI) aims to give an overview, from theory to practical applications and an introduction to selecting data sources and choosing which algorithms best fit a particular problem.
Participants will obtain the necessary skills:
- to manage and analyze data,
- to complete exploratory data analysis, statistical inference and modelling, machine learning, and high-dimensional data analysis,
- to develop data products including R programming, data wrangling, reproducible research, and communicating results.
The course focuses more on business applications than theory and it covers the set of techniques and tools which are being adopted by modern businesses.
Participants are tutored on selecting the best tools and frameworks for solving problems with data.
This course includes tutorials and demonstrations that emphasize discussion and illustration of methods, as well as hands-on, practical exercises that provide both a sound base of learning and an opportunity to test and develop skill. Participants will learn these concepts through data analysis project.
The project implements the learning-by-doing approach – participants utilise methods and techniques, presented during the tutorials of the course, for real-world data sets. Two cases studies demonstrate all stages and challenges of data analytics life cycle.
On successful completion of the course, participants will be able:
- to identify promising business applications of data sciences methods,
- to do data science task setting, to determine the appropriate techniques and to implement in their future business/research activities,
- to know the key methods of classification, clustering, prediction and exploration in data analysis,
- to get a general understanding of how each method works, recognize why the method is appropriate to a particular business environment, understand how to perform the analysis using appropriate tools and be able to do interpretation of the results in business context,
- to communicate in terms of the conventions of the course.
Информация о преподавателях
Doctor of Science in Engineering; specializes in statistical data processing and of transport systems’ analysis and modelling.
High school teaching experience since 1990, internships in Oxford University (1997) and EPFL (2007). Prof. Jackiva is an author of the first course on Data Mining in Latvia (2004). Professor in MSc and PhD programmes in TSI and invited professor in RISEBA (PhD-level course on Data Mining) and Higher School of Economics (MSC-level programme on Simulation Modeling as Research Tool); an active supervisor of PhD students, 5of them successful defended their theses in 2012-2018.
Prof. Jackiva has awards from Latvian Ministry of Education and Science, K.Irbish’s foundation, Latvijas Gaisa Satiksme, Latvian Academy of Sciences and Latvian “Izglītībai, zinātnei un kultūrai” foundation for excellent specialist training in the sphere of computer science and information technologies. Prof. Jackiva leads European and national projects in transport modelling and data processing areas.
Postdoctoral researcher; assistant professor; head of TSI mathematical methods and modelling department. Dmitry holds two doctoral degrees – in economics and in engineering and has17 years of high school teaching experience.
Dmitry is an active researcher in the sphere of data analytics and a highly experienced R developer, the author of two R packages, accepted in the official Comprehensive R Archive Network (CRAN).
Jelena is a data scientist with more than five years of practical experience in industry and 17 years of scientific & academical experience in the field of analytics, machine learning, AI and operational research field. Jelena is experienced in the field of deep learning & machine learning. Several years she has worked as a business risks & business process analysis in a financial & banking sector. She has a number of successfully implemented data science projects in a banking, production, marketing, customer service and government sectors.
Jelena had graduated from TTI with master’s degree in the field of computer science and afterwards has defended PhD thesis in the field of engineering science.
Jelena is a assistant professor and a senior scientific researcher in TSI and participated in a number of research projects in the field of image and text recognition, system analysis and simulation.
Doctor of Science in Engineering, scientific sub-area "Telematics and Logistics" (2015), Master's degree in computer science. Assistant professor at the Department of Mathematical Methods and Modelling, experience as a teacher since 2003. Participation in various research and applied projects, currently executor of the postdoctoral project “Non-traditional regression models in transport modelling” (220.127.116.11/VIAA/1/16/075).
Doctor of Science in Engineering, Associate Professor; Head of Department of Software Engineering of Transport and Telecommunication Institute; Senior Researcher; the author of more than 20 scientific articles; the specialist in Programming (C++, C#, .Net, MathLab) Software Development, Image Processing, Transportation System.
Anastasija’s core capability is around mathematical and statistical methods in econometrics, modelling, and data mining. She works as an analyst and data scientist, and has experience with R language for 7+ years. Anastasija holds a Bachelor's degree in Mathematics and Statistics at University of Latvia and a Master of engineering degree in Management of Information Systems at Transport and Telecommunication Institute.
Dr.sc.ing. Mihails Savrasovs is one of leading researchers and academic staff members at Mathematical methods and modelling department of Transport and Telecommunication Institute. He has deep knowledge and professional skills in IT application for business. He has completed several IBM courses regarding Deep Learning, Data Science, BigData, ChatBots. Also he is a Microsoft Certified Professional in MS SQL.
firstname.lastname@example.org, Институт транспорта и связи, ул. Ломоносова, 1 – 404. Каб., г. Рига, LV-1019, Латвия, Тел.: (+371) 67100652