Научно-исследовательский семинар "Прикладная статистика и науки о данных"

Магистратура 2025/2026

Лучший по критерию «Полезность курса для Вашей будущей карьеры»

Лучший по критерию «Полезность курса для расширения кругозора и разностороннего развития»

Статус: Курс обязательный (Аналитика данных и прикладная статистика / Data Analytics and Social Statistics)

Когда читается: 1-й курс, 1-4 модуль

Охват аудитории: для своего кампуса

Преподаватели: Карташева Анна Александровна, Крянина Дарья Николаевна, Осокина Дарья Александровна, Пашков Станислав Георгиевич, Перехожев Егор Сергеевич

Язык: английский

Кредиты: 6

Контактные часы: 48

Full Syllabus Ask Question

Abstract

Research Seminar in Applied Statistics and Data Science is a practice-oriented course covering contemporary methods, technologies and professional practices used in data-driven research and business analytics. Students follow the analytical process from formulating a research question and collecting and preparing data to selecting methods, building analytical models, interpreting results and communicating findings. The course introduces performance evaluation, social network analysis, text analysis, business process modelling, AI-assisted research, Python-based data analysis, A/B testing, open data and APIs, dashboards and visual communication. Learning activities include case discussions, quizzes, a reflective essay and independent applied projects. Students learn to select appropriate tools, evaluate their limitations and present analytical results through reports, visualisations, dashboards and presentations.

Learning Objectives

To provide students with a systematic understanding of contemporary approaches in applied statistics, data science and business analytics
To develop the ability to formulate research questions, select appropriate analytical methods and critically interpret the results
To develop practical skills in collecting, preparing, analysing and visualising data and communicating evidence-based conclusions

Expected Learning Outcomes

- - be able to design and understand the structure of data; use various visual and table presentations of data.
Be able to present and/or interpret data in tables and charts.
- Use storytelling when giving a presentation.
A student can choose proper tools and instruments for data visualization
A student can prepare his data for visualization
Be able to escribe graph/diagram, analysing visual prompts, interpret tables/charts.
an ability to solve analytical and research problems with modern technical means and information technologies; an ability to organize their activities in the framework of professional tasks.
Apply the basics of social network analysis at the network level (e.g. density, clustering, degree distribution, etc.); at the node level (e.g. degree, betweenness, closeness); at the subgraph level (e.g. triads, communities)
Able to build integrated reports and dashboards
Ability to formulate research question, and explain how the question and theory define methodology;
- to learn the fundamental analytical scheme starting from data preparation and ending up with data visualisation in a form of a dashboard in Power BI
- develop critical assessment and academic presentation skills;
- to develop their presentation skills and abilities to participate in the discussions
Be able to present a model using a dashboard, charts, etc.
Understand key terms in business analytics and role of business analyst in modern organizations
To reproduce types of analytical approaches according to Gartner
Be familiar with basics of Data management
Be able to build model for measuring efficiency - Data Envelopment Analysis model - in R
Be aware of Open Data sources
Be able to extract the data using API
Be able to apply text mining in your own tasks
Be able to draw basic processes using BPMN 2.0 notations
demonstrate how AI tools can be used at various levels of data analysis
apply cohort analysis and A/B testing to analyze data and hypotheses

Course Contents

1 - Introduction to Business Analytics
2 - Analytics and labor market research: skills and requirements for data analysts
3 - The hard skills for data-driven approach in organizations
4 - The soft skills for data-driven approach in organizations
5 - Performance Evaluation
6 - Social Network Analysis: Applications for Organizations
7 - Analytical Process: from Idea to Solution
8 - Contemporary Text Analysis
9 - Business Process Management and Financial Modelling
10 - AI tools for working with data
11 - Product approach to social research
12 - Python for data analysis
13 - A/B testing (Split testing)
14 - Visual Communications: Charts
15 - Dashboards and Visual Analytics
16 - Data Analysis and Visualization with Power BI
17 - Network Visualization for Better Decision-Making
18 - Business reporting
19 - Making Presentations

Assessment Elements

Essay
Reflective Essay on Methods Applicable to Business Analytics. In this assignment, you are required to write a reflective essay exploring various methods that are applicable to business analytics. The objective of this essay is to critically analyze and reflect on the different analytical techniques and tools that businesses use to interpret data, make informed decisions, and drive strategic initiatives.
Quizzes in the e-course
In this assignment, you are tasked with developing five quizzes that assess the knowledge and understanding of the material covered in a pre-recorded course based on video content and supplied materials and literature. The purpose of these quizzes is to reinforce learning, evaluate comprehension, and provide feedback to learners on their grasp of the subject matter.
Hard skills project
In this task, you are required to select one project from a list of five, each focusing on the hard skills you have acquired during the pre-recorded online course. You have the flexibility to choose a project that can be developed using Python, R, Excel, or other relevant tools. Your chosen project should demonstrate your understanding and application of the specific skills learned in the course. Please ensure that your project is well-structured and clearly showcases your expertise in the selected area.
Project of a research pilot with AI
In this assignment, you are required to conduct a one-day research pilot that utilizes various artificial intelligence (AI) tools to address a specific problem or question. The objective of this pilot is to guide you through the process of defining a research question, selecting appropriate AI tools, and implementing a solution. You will also be expected to write a reflective essay that analyzes your experience, the effectiveness of the tools used, and the insights gained from the research process. This reflection should critically evaluate how AI can enhance research methodologies and contribute to problem-solving in real-world scenarios.
Visualization assignment
In this assignment, you will focus on data visualization by creating a presentation based on a selected article. The aim is to effectively communicate the insights and findings from the article through visual representations of data. You will also complete a series of exercises designed to enhance your skills in data visualization using various datasets.

Interim Assessment

2025/2026 4th module
0.3 * Hard skills project + 0.3 * Project of a research pilot with AI + 0.2 * Visualization assignment + 0.1 * Quizzes in the e-course + 0.1 * Essay

Bibliography

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Authors

STEGNIY ELENA ANATOLEVNA

Course Syllabus