Магистратура
2024/2025
Научно-исследовательский семинар "Прикладная статистика и науки о данных"
Статус:
Курс обязательный (Аналитика данных и прикладная статистика / Data Analytics and Social Statistics)
Направление:
01.04.02. Прикладная математика и информатика
Где читается:
Факультет социальных наук
Когда читается:
1-й курс, 1-4 модуль
Формат изучения:
без онлайн-курса
Охват аудитории:
для своего кампуса
Преподаватели:
Карташева Анна Александровна
Прогр. обучения:
Аналитика данных и прикладная статистика
Язык:
английский
Кредиты:
6
Контактные часы:
48
Course Syllabus
Abstract
This course is about different approaches in business analytics and major types of business analytics. Specifically, there will be the focus on necessary vocabulary of business analyst and digital trends in the companies and applied skills in MS Office (Word, Excel, and Power Point). Throughout the semester there will be practical cases in different business fields as well as discussion of practice-oriented term papers. The seminar is aimed at developing students' skills of research work and applications of theoretical knowledge to solving practical cases.
Learning Objectives
- The course gives students an important foundation to develop and conduct their own research as well as to evaluate research of others.
Expected Learning Outcomes
- By the end of the course the students are expected to be able to undertake a substantial research project through which to demonstrate their research and analytical skills and how well they can apply a given theoretical understanding and methodology to a set problem.
- - - 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 compares research design
- 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.
- Distinguish between qualitative and quantitative research methods;
- 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
- Able to demonstrate knowledge on the principles for data visualization
- Be able to present a model using a dashboard, charts, etc.
- 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
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
- EssayReflective 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-courseIn 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 projectIn 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 AIIn 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 assignmentIn 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
- 2024/2025 4th module0.1 * Essay + 0.3 * Hard skills project + 0.3 * Project of a research pilot with AI + 0.1 * Quizzes in the e-course + 0.2 * Visualization assignment
Bibliography
Recommended Core Bibliography
- Exploratory social network analysis with Pajek, Nooy de, W., 2018
- Grant, R. (2019). Data Visualization : Charts, Maps, and Interactive Graphics. Boca Raton, Florida: Chapman and Hall/CRC. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1944722
- Models and methods in social network analysis, , 2006
- Seamark, P. (2018). Beginning DAX with Power BI : The SQL Pro’s Guide to Better Business Intelligence. [United States]: Apress. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1743806
- Social network analysis : methods and applications, Wasserman, S., 2009
- Платова, Е. Д. Effective Presentations in English : учебное пособие / Е. Д. Платова. — Оренбург : ОГУ, 2019. — 140 с. — ISBN 978-5-7410-2406-5. — Текст : электронный // Лань : электронно-библиотечная система. — URL: https://e.lanbook.com/book/160030 (дата обращения: 00.00.0000). — Режим доступа: для авториз. пользователей.
- Феррари, А. Анализ данных при помощи Microsoft Power BI и Power Pivot для Excel : руководство / А. Феррари, М. .. Руссо , перевод с английского А. Ю. Гинько. — Москва : ДМК Пресс, 2020. — 288 с. — ISBN 978-5-97060-858-6. — Текст : электронный // Лань : электронно-библиотечная система. — URL: https://e.lanbook.com/book/179497 (дата обращения: 00.00.0000). — Режим доступа: для авториз. пользователей.