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Data Analytics Foundations for Accountancy I
提供方
University of Illinois at Urbana-Champaign
教学大纲 - 您将从这门课程中学到什么
周
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 个视频 （总计 8 分钟）, 4 个阅读材料, 1 个测验
4 个阅读材料
Syllabus10分钟
About the Discussion Forums10分钟
Updating Your Profile10分钟
Social Media10分钟
1 个练习
Orientation Quiz10分钟
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 个视频 （总计 29 分钟）, 2 个阅读材料, 2 个测验
5 个视频
The Importance of Data Analytics in Modern Accountancy3分钟
Introduction to the Course JupyterHub Server7分钟
Introduction to Markdown5分钟
Introduction to Python8分钟
2 个阅读材料
Module 1 Overview10分钟
Lesson 1-1 Readings10分钟
1 个练习
Module 1 Graded Quiz20分钟
周
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 个视频 （总计 29 分钟）, 2 个阅读材料, 2 个测验
5 个视频
Why Accounting Students Should Learn to Code4分钟
Python Data Structures7分钟
Introduction to Python Functions5分钟
Python Programming Concepts6分钟
2 个阅读材料
Module 2 Overview10分钟
Lesson 2-1 Readings10分钟
1 个练习
Module 2 Graded Quiz20分钟
周
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 个视频 （总计 29 分钟）, 2 个阅读材料, 2 个测验
5 个视频
Why Use Python Instead of Excel?3分钟
Introduction to Unix6分钟
Python File I/O7分钟
Introduction to Pandas6分钟
2 个阅读材料
Module 3 Overview10分钟
Lesson 3-1 Readings10分钟
1 个练习
Module 3 Graded Quiz20分钟
周
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 个视频 （总计 33 分钟）, 2 个阅读材料, 2 个测验
5 个视频
How the Pandas Module Can Support Standard Business Analytics2分钟
Introduction to Numpy8分钟
Introduction to Descriptive Statistics10分钟
Advanced Pandas8分钟
2 个阅读材料
Module 4 Overview10分钟
Lesson 4-1 Readings10分钟
1 个练习
Module 4 Graded Quiz20分钟
讲师
Robert Brunner
ProfessorAccountancy
立即开始攻读硕士学位
此 课程 隶属于 University of Illinois at Urbana-Champaign 提供的 100% 在线 Master of Science in Accountancy (iMSA)。如果您被录取参加全部课程，您的课程将计入您的学位学习进程。
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