Datu zinātne: no datiem līdz produktam
TSI Mūžizglītības mācību centrs piedāvā Jums neformālās izglītības programmu "Datu zinātne: no datiem līdz produktam".

Informācija par kursu

Vieta: Lomonosova iela 1
Instruktors: Irina Jackiva, Dmitry Pavlyuk, Jelena Jursevica, Nadezda Spiridovska, Irina Pticina, Anastasija Hismutova, Mihails Savrasovs
Kursa valoda: Angļu, Krievu
No datiem līdz produktam

Galvenā informācija

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.

Apmācību sasniedzamie mērķi

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.

Learning Outcomes

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.

Pasteidzies! Dalībnieku skaits grupā ir ierobežots - ne vairāk kā 12 cilvēki!

Pieteikties

Vairāk informācijas rakstot uz kursi@tsi.lv, Transporta un sakaru institūts, Lomonosova iela 1 – 404.kab., Rīga, LV-1019, Latvija, tālrunis: (+371) 67100535, (+371) 29389408

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