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Data Analytics Foundations for Accountancy I
proposé par
University of Illinois at Urbana-Champaign
Programme du cours : ce que vous apprendrez dans ce cours
Semaine
1Course Orientation
You will become familiar with the course, your classmates, and our learning environment. The orientation will also help you obtain the technical skills required for the course.
2 vidéos (Total 8 min), 4 lectures, 1 quiz
4 lectures
Syllabus10 min
About the Discussion Forums10 min
Updating Your Profile10 min
Social Media10 min
1 exercice pour s'entraîner
Orientation Quiz10 min
Module 1: Foundations
This module serves as the introduction to the course content and the course Jupyter server, where you will run your analytics scripts. First, you will read about specific examples of how analytics is being employed by Accounting firms. Next, you will learn about the capabilities of the course Jupyter server, and how to create, edit, and run notebooks on the course server. After this, you will learn how to write Markdown formatted documents, which is an easy way to quickly write formatted text, including descriptive text inside a course notebook. Finally, you will begin learning about Python, the programming language used in this course for data analytics.
5 vidéos (Total 29 min), 2 lectures, 2 quiz
5 vidéos
The Importance of Data Analytics in Modern Accountancy3 min
Introduction to the Course JupyterHub Server7 min
Introduction to Markdown5 min
Introduction to Python8 min
2 lectures
Module 1 Overview10 min
Lesson 1-1 Readings10 min
1 exercice pour s'entraîner
Module 1 Graded Quiz20 min
Semaine
2Module 2: Introduction to Python
This module focuses on the basic features in the Python programming language that underlie most data analytics scripts. First, you will read about why accounting students should learn to write computer programs. Second, you will learn about basic data structures commonly used in Python programs. Third, you will learn how to write functions, which can be repeatedly called, in Python, and how to use them effectively in your own programs. Finally, you will learn how to control the execution process of your Python program by using conditional statements and looping constructs. At the conclusion of this module, you will be able to write Python scripts to perform basic data analytic tasks.
5 vidéos (Total 29 min), 2 lectures, 2 quiz
5 vidéos
Why Accounting Students Should Learn to Code4 min
Python Data Structures7 min
Introduction to Python Functions5 min
Python Programming Concepts6 min
2 lectures
Module 2 Overview10 min
Lesson 2-1 Readings10 min
1 exercice pour s'entraîner
Module 2 Graded Quiz20 min
Semaine
3Module 3: Introduction to Data Analysis
This module introduces fundamental concepts in data analysis. First, you will read a report from the Association of Accountants and Financial Professionals in Business that explores Big Data in Accountancy. Next, you will learn about the Unix file system, which is the operating system used for most big data processing (as well as Linux and Mac OSX desktops and many mobile phones). Second, you will learn how to read and write data to a file from within a Python program. Finally, you will learn about the Pandas Python module that can simplify many challenging data analysis tasks, and includes the DataFrame, which programmatically mimics many of the features of a traditional spreadsheet.
5 vidéos (Total 29 min), 2 lectures, 2 quiz
5 vidéos
Why Use Python Instead of Excel?3 min
Introduction to Unix6 min
Python File I/O7 min
Introduction to Pandas6 min
2 lectures
Module 3 Overview10 min
Lesson 3-1 Readings10 min
1 exercice pour s'entraîner
Module 3 Graded Quiz20 min
Semaine
4Module 4: Statistical Data Analysis
This module introduces fundamental concepts in data analysis. First, you will read about how to perform many basic tasks in Excel by using the Pandas module in Python. Second, you will learn about the Numpy module, which provides support for fast numerical operations within Python. This module will focus on using Numpy with one-dimensional data (i.e., vectors or 1-D arrays), but a later module will explore using Numpy for higher-dimensional data. Third, you will learn about descriptive statistics, which can be used to characterize a data set by using a few specific measurements. Finally, you will learn about advanced functionality within the Pandas module including masking, grouping, stacking, and pivot tables.
5 vidéos (Total 33 min), 2 lectures, 2 quiz
5 vidéos
How the Pandas Module Can Support Standard Business Analytics2 min
Introduction to Numpy8 min
Introduction to Descriptive Statistics10 min
Advanced Pandas8 min
2 lectures
Module 4 Overview10 min
Lesson 4-1 Readings10 min
1 exercice pour s'entraîner
Module 4 Graded Quiz20 min
Enseignant
Robert Brunner
ProfessorAccountancy
Commencez à travailler pour obtenir votre master
Ce cours fait partie du diplôme intégralement en ligne Master of Science in Accountancy (iMSA) de University of Illinois at Urbana-Champaign.
Si vous êtes admis au programme complet, vos cours sont pris en compte dans votre apprentissage diplômant.
À propos de University of Illinois at Urbana-Champaign
The University of Illinois at Urbana-Champaign is a world leader in research, teaching and public engagement, distinguished by the breadth of its programs, broad academic excellence, and internationally renowned faculty and alumni. Illinois serves the world by creating knowledge, preparing students for lives of impact, and finding solutions to critical societal needs.
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