уровень образования
язык программы
длительность программы
понадобится для освоения
за обучение
The specialization is intended for a general audience of business analysts, seeking to augment their toolkit with the newest analytical methods. Specifically, they will get introduced to the analysis of networks and unstructured data (texts) – the two areas that are currently hailed as the “methods of the future.” The connections that people build and the words they use can potentially tell us much more about the organizational processes than the traditional analytics on numbers.
It is also for anyone who wants to learn practical analytics. “Business” is a very broad domain. Learners will know about the application of the newest methods to the analysis of business and will be able to extend the knowledge to other areas.
To immerse the newly learned methods into the broader analytical context, specialization offers two additional overview courses. One is dedicated to the field of analytics, helping form a solid understanding of the role that different methods play in generating insights. The second one is an overview of business analytics specifically, with practical tools and tips for a more successful analytic outcome.
Each course contains a variety of hands-on projects that will aid the understanding of new methods and provide real-life applications of newly learned skills. Having completed the specialization, learners will acquire advanced methodological tools that can be immediately implemented to improve the analysis and decision-making in the modern corporate world.
All projects included in this specialization are providing the hands-on experience with the newly learned methods. Unlike “textbook” projects that use clean, “nice” data, these projects are based on real-life data, with their corresponding problems and issues.
Use the R programming language to work with both structured and unstructured (text) data
Prepare text data for analysis
Train and evaluate supervised learning models on text data
Train and evaluate unsupervised learning models on text data
Interpret the results of unsupervised and supervised modelling
Навыки:
Business Analytics
better decision-making
networks
Text Analysis
Social Network Analysis
Business Process
Performance Measurement
Text Mining
уровень образования
язык программы
длительность программы
понадобится для освоения
за обучение
Должность: Lecturer
Должность: Lecturer: Faculty of Social Sciences / School of Sociology
Должность: Lecturer: ICEF; Oxford Internet Institute
Должность: Junior Research Fellow, Senior Lecturer: International laboratory for Applied Network Research
Должность: Lecturer
Должность: Analyst: Investment Analyst in Russian Direct Investment Fund