Аналитические инструменты управления финансами предприятия

2024/2025

Статус: Маго-лего

Кто читает: Департамент финансов

Когда читается: 4 модуль

Охват аудитории: для своего кампуса

Преподаватели: Назарова Варвара Вадимовна, Светлов Кирилл Владимирович

Язык: английский

Кредиты: 3

Контактные часы: 32

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Abstract

The purpose of the discipline is to form the student's knowledge of analytical methods of tools in the management of enterprise finances. As part of the course, students will study decision-making methods in various functional areas of enterprise finance, as well as methods and algorithms for quantitative assessments of the processes of providing enterprise activities with financial resources. The main goal of the course is to familiarize with modern approaches to modeling and optimization of financial operations and functions, approaches to the problem of making economically sound decisions in conditions of uncertainty.

Learning Objectives

Introduction to relational database management systems with MS SQL Server as an example
Learning solid basis of SQL querying
Exploring Window Functions
Acquiring bases in Pandas and Numpy for data transformation, including Effective Pandas, as well as simple data visualization

Expected Learning Outcomes

Ability to write SQL queries in a relational DBMS

Course Contents

Lecture 1. MS SQL Server and SQL foundations.
Lecture 2. Single-Table Queries, Data types and built-in functions
Lecture 3. Table Joins and Set operators.
Lecture 4. Subqueries and table expressions.
Lecture 5. Window functions.
Lecture 6. Crash course into Pandas and Numpy
Lecture 7. Effective Pandas.
Lecture 8. Data visualization in Python.

Assessment Elements

In class test 1
In class test 2
Final Examination

Interim Assessment

2024/2025 4th module
0.5 * Final Examination + 0.25 * In class test 1 + 0.25 * In class test 2

Bibliography

Recommended Core Bibliography

McKinney, W. (2012). Python for Data Analysis : Data Wrangling with Pandas, NumPy, and IPython. Sebastopol, CA: O’Reilly Media. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=495822
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

Recommended Additional Bibliography

Date, C. J. (2015). SQL and Relational Theory : How to Write Accurate SQL Code (Vol. Third edition). Sebastopol, CA: O’Reilly Media. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1099367

Authors

Churakova Iiia Iurevna
SOLOVEVA EKATERINA EVGENEVNA

Course Syllabus