Analytical tools for enterprise financial management

2023/2024

Учебный год

ENG

Обучение ведется на английском языке

3

Кредиты

Кто читает:

Департамент менеджмента

Статус:

Курс обязательный

Когда читается:

1-й курс, 4 модуль

Преподаватель

Козлова Наталия Ильинична

Course Syllabus

Abstract

The course is designed to introduce the advanced tools used to create interactive, visual analytical dashboard applications. It discusses important contemporary practices in the field of data visualization in Python. The course starts with the basics of Python programming language, Pandas and NumPy libraries and progresses towards the advanced topics in the process of creating interactive dashboard applications on this foundation, e.g. using real-time data visualization, multi-page apps’ creation, authorization issues and ways of deploying the created app in order to make it available for the broader range of users. After mastering this course, the students will gain substantial knowledge about the advanced tools used to create interactive dashboard applications, understand the code used, application protection, deployment and unlimited improvement abilities using the open-source software. Successful completion of the course will make them ready for the job market as well as for rigorous research in finance.

Learning Objectives

• After mastering this course, the students will gain substantial knowledge about the advanced tools used to create interactive dashboard applications, understand the code used, application protection, deployment and unlimited improvement abilities using the open-source software.

Expected Learning Outcomes

• Apply Plotly Open Source Graphing Library to create interactive, publication-quality graphs (line plots, scatter plots, bar charts, histograms, heatmaps, subplots, bubble charts and more)
• Apply Plotly Dash, the original low-code framework, to rapidly building multi-page data applications in Python
• Secure interactive dashboards with App Authorization
• Deploy interactive dashboards to the internet with services like Render
• Learn how to read the Dash documentation for further deep dive

Course Contents

• Lecture 1: Introduction to Data Visualization Ecosystem for Python
• Lecture 2: NumPy and Pandas Crash Course
• Lecture 3: Plotly Basic Charts and Plots
• Lecture 4: Dash Basics for Dashboards
• Lecture 5: Advanced Dash Tools
• Lecture 6: Milestone Project
• Lecture 7: Real-Time Updating Dashboards
• Lecture 8: Authorization and Deployment

Assessment Elements

• Homework
• Case Study
• Class Participation
• Examination

Interim Assessment

• 2023/2024 4th module
  0.2 * Case Study + 0.1 * Class Participation + 0.4 * Examination + 0.3 * Homework

Bibliography

Recommended Core Bibliography

• Creating interactive plots in five minutes with datapasta and plotly. (2018). Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.29C809E2

Recommended Additional Bibliography

• McKinney, W. (2018). Python for Data Analysis : Data Wrangling with Pandas, NumPy, and IPython (Vol. Second edition). Sebastopol, CA: O’Reilly Media. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1605925
• Даббас, Э. Интерактивные дашборды и приложения с Plotly и Dash. Используем полноценный веб-фреймворк в Python на всю мощь – без JavaScript / Э. Даббас , перевод с английского А. Ю. Гинько. — Москва : ДМК Пресс, 2023. — 306 с. — ISBN 978-5-97060-988-0. — Текст : электронный // Лань : электронно-библиотечная система. — URL: https://e.lanbook.com/book/315485 (дата обращения: 00.00.0000). — Режим доступа: для авториз. пользователей.

Authors

• NAZAROVA VARVARA VADIMOVNA
• SOLOVEVA EKATERINA EVGENEVNA