本课程是 Accounting Data Analytics 专项课程专项课程的一部分

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Ronald Guymon 另外 +1 位授课教师

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隶属于 Master of Science in Accountancy (iMSA) 学位
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Accounting Data Analytics 专项课程伊利诺伊大学香槟分校

课程信息

15,125 次近期查看

This course focuses on developing Python skills for assembling business data. It will cover some of the same material from Introduction to Accounting Data Analytics and Visualization, but in a more general purpose programming environment (Jupyter Notebook for Python), rather than in Excel and the Visual Basic Editor. These concepts are taught within the context of one or more accounting data domains (e.g., financial statement data from EDGAR, stock data, loan data, point-of-sale data).
The first half of the course picks up where Introduction to Accounting Data Analytics and Visualization left off: using in an integrated development environment to automate data analytic tasks. We discuss how to manage code and share results within Jupyter Notebook, a popular development environment for data analytic software like Python and R. We then review some fundamental programming skills, such as mathematical operators, functions, conditional statements and loops using Python software. 
The second half of the course focuses on assembling data for machine learning purposes.  We introduce students to Pandas dataframes and Numpy for structuring and manipulating data. We then analyze the data using visualizations and linear regression. Finally, we explain how to use Python for interacting with SQL data.

可灵活调整截止日期

根据您的日程表重置截止日期。

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100% 在线

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第 2 门课程（共 4 门）

Accounting Data Analytics 专项课程

中级

完成时间大约为41 小时

英语（English）

您将学到的内容有

Know how to operate software that will help you create and run Python code.
Execute Python code for wrangling data from different structures into a Pandas dataframe structure.
Run and interpret fundamental data analytic tasks in Python including descriptive statistics, data visualizations, and regression.
Use relational databases and know how to manipulate such databases directly through the command line, and indirectly through a Python script.

您将获得的技能

Python Programming
Data Visualization (DataViz)
Linear Regression
SQL
Data Preparation

可灵活调整截止日期

根据您的日程表重置截止日期。

可分享的证书

完成后获得证书

100% 在线

立即开始，按照自己的计划学习。

第 2 门课程（共 4 门）

Accounting Data Analytics 专项课程

中级

完成时间大约为41 小时

英语（English）

授课教师

授课教师评分

4.11/5 （22 个评分）

Ronald Guymon

Senior Lecturer of Accountancy

Accountancy

47,641 个学生

5 门课程

Linden Lu

Instructor

Department of Accountancy

14,695 个学生

3 门课程

提供方

伊利诺伊大学香槟分校

立即开始攻读硕士学位

此课程隶属于伊利诺伊大学香槟分校提供的 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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授课大纲 - 您将从这门课程中学到什么

周

周 1

完成时间为 1 小时

INTRODUCTION TO THE COURSE

完成时间为 1 小时

4 个视频（总计 12 分钟）, 5 个阅读材料

完成时间为 4 小时

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.

完成时间为 4 小时

14 个视频（总计 84 分钟）, 2 个阅读材料, 2 个测验

14 个视频

Module 1 Introduction2分钟

1.1 Introduction to Data Analytics2分钟

1.2 Jupyter Notebook4分钟

Python and Integrated Development Environments (IDEs)6分钟

Installing and Running Python Using the Anaconda Distribution4分钟

Installing and Running Python Without Anaconda9分钟

Navigating Jupyter Notebook5分钟

Navigating JupyterLab5分钟

Using Notebook Files9分钟

Navigating Spyder8分钟

Comparison of Jupyter Notebook, JupyterLab, and Spyder3分钟

1.3 Introduction to Markdown3分钟

Markdown Basics9分钟

Module 1 Review6分钟

2 个阅读材料

Module 1 Overview and Resources3分钟

Lesson 1.1 Readings20分钟

1 个练习

Module 1 Quiz20分钟

周

周 2

完成时间为 4 小时

MODULE 2: INTRODUCTION TO PYTHON

This module focuses on the basic features in the Python programming language that underlie most data analytics programs (or scripts). First, you will read about why accounting students should learn to write computer programs. In the first lesson, you will also learn the basic concepts of the Python programming language, including how to create variables, basic data types and mathematical operators, and how to document your programs with comments. Next, you will learn about Boolean and logical operators in Python and how they can be used to control the flow of a Python program by using conditional statements. Finally, you will learn about functions and how they can simplify developing and maintaining programs. You will also learn how to create and call functions in Python.

完成时间为 4 小时

12 个视频（总计 66 分钟）, 1 个阅读材料, 2 个测验

12 个视频

Module 2 Introduction7分钟

2.1 Introduction to Python3分钟

Python Code Basics6分钟

Variables, Data Types, and Operators8分钟

2.2 Introduction to Python Functions2分钟

Built-In Functions6分钟

User-Defined Functions9分钟

Functions vs Methods4分钟

2.3 Conditional Statements in Python2分钟

Comparison and Logical Operators3分钟

Working with Conditional Statements5分钟

Module 2 Review4分钟

1 个阅读材料

Module 2 Overview and Resources15分钟

1 个练习

Module 2 Quiz15分钟

周

周 3

完成时间为 5 小时

MODULE 3: INTRODUCTION TO PYTHON PROGRAMMING

完成时间为 5 小时

15 个视频（总计 84 分钟）, 1 个阅读材料, 2 个测验

15 个视频

Module 3 Introduction2分钟

3.1 Introduction to Python Data Structures4分钟

Introduction to Strings6分钟

Introduction to Lists5分钟

Introduction to Dictionaries, Tuples, and Unpacking7分钟

Common Sequence Operations7分钟

3.2 Working with Python Data Structure2分钟

Working with Strings9分钟

Working with Lists and Tuples7分钟

Working with Dictionaries3分钟

3.3 Introduction to Python Loops2分钟

The For Loop13分钟

The While Loop2分钟

Comprehensions3分钟

Module 3 Review4分钟

1 个阅读材料

Module 3 Overview and Resources3分钟

1 个练习

Module 3 Quiz10分钟

周

周 4

完成时间为 5 小时

MODULE 4: PYTHON PROGRAMMING

完成时间为 5 小时

12 个视频（总计 74 分钟）, 1 个阅读材料, 2 个测验

12 个视频

Module 4 Introduction6分钟

4.1 Writing Python Programs3分钟

Python Modules8分钟

Errors and Exceptions8分钟

4.2 Introduction to NumPy1分钟

NumPy Array5分钟

NumPy Basic Functions8分钟

4.3 Introduction to Pandas2分钟

Introduction to Dataframes8分钟

Data Selection with Dataframes9分钟

Missing Values and Copies with Dataframes8分钟

Module 4 Review2分钟

1 个阅读材料

Module 4 Overview and Resources3分钟

1 个练习

Module 4 Quiz20分钟

周

周 5

完成时间为 5 小时

MODULE 5: DATA ANALYSIS WITH PYTHON

完成时间为 5 小时

14 个视频（总计 93 分钟）, 1 个阅读材料, 2 个测验

14 个视频

Module 5 Introduction3分钟

5.1 Python File IO3分钟

Reading and Writing Files with Base Python9分钟

Reading and Writing Files with Pandas8分钟

Preserving Data Types with Pickling5分钟

5.2 Working with the Pandas DataFrame1分钟

Exploring Dataframes8分钟

Copying and Sorting Dataframes7分钟

Changing Column and Row Names of Dataframes6分钟

Grouping and Aggregating with Dataframes6分钟

Stacking and Pivoting Dataframes10分钟

5.3 Introduction to Descriptive Statistics1分钟

Descriptive Statistics for Dataframes13分钟

Module 5 Review7分钟

1 个阅读材料

Module 5 Overview and Resources3分钟

1 个练习

Module 5 Quiz30分钟

周

周 6

完成时间为 6 小时

MODULE 6: INTRODUCTION TO VISUALIZATION IN PYTHON

完成时间为 6 小时

16 个视频（总计 88 分钟）, 1 个阅读材料, 2 个测验

16 个视频

Module 6 Introduction3分钟

6.1 Introduction to Plotting with Python2分钟

Introduction to Plotting with Pandas9分钟

MODULE 7: PRODUCTION DATA ANALYTICS

完成时间为 5 小时

16 个视频（总计 84 分钟）, 1 个阅读材料, 2 个测验

16 个视频

Module 7 Introduction3分钟

7.1 Introduction to CRISP-DM3分钟

7.2 Introduction to Data Preparation Techniques2分钟

Pandas Functions to Load Data7分钟

Fill in Missing Values with Conditional Means8分钟

Manipulating String Columns of a Dataframe7分钟

Creating Datetime Values4分钟

Split, Apply Combine and More on Datetimes6分钟

Lambda Functions6分钟

7.3 Linear Regression in Python2分钟

Setting up Data for Regression5分钟

Creating a Simple Regression Model7分钟

Predicting with a Regression Model5分钟

Multiple Regression Model6分钟

Categorical Variables in Regression3分钟

Module 7 Review2分钟

1 个阅读材料

Module 7 Overview and Resources3分钟

1 个练习

Module 7 Quiz30分钟

周

周 8

完成时间为 6 小时

MODULE 8: INTRODUCTION TO DATABASES IN PYTHON

完成时间为 6 小时

15 个视频（总计 86 分钟）, 3 个阅读材料, 2 个测验

15 个视频

Module 8 Introduction3分钟

8.1 Introduction to Data Persistence4分钟

Introduction to Terminal8分钟

Creating a SQLite Database From Terminal8分钟

Creating a SQLite Table From a CSV File5分钟

Using Dump and Reading in Files to Create Tables8分钟

Altering Existing SQLite Tables4分钟

8.2 Advanced Concepts2分钟

Querying Tables with SQL6分钟

SQL Join Queries5分钟

8.3 Python Database Programming3分钟

Querying Relational Database with Python and SQL7分钟

Exploring Databases and Adding Rows to Tables with Python8分钟

Module 8 Review4分钟

Gies Online Programs3分钟

3 个阅读材料

Module 8 Overview and Resources3分钟

Congratulations!10分钟

Get Your Course Certificate10分钟

1 个练习

Module 8 Quiz30分钟

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4.3

22 条评论

5 stars
56.94%
4 stars
25%
3 stars
6.94%
2 stars
8.33%
1 star
2.77%

来自ACCOUNTING DATA ANALYTICS WITH PYTHON的热门评论

由 EG 提供Nov 30, 2020

It is very easy to learn and also very interesting because you can modify and try other things.

由 SM 提供Jun 27, 2020

Really Nice course but you will not explain all the module very indepth. All the module are basic and easy to learn. I am very happy to completed this course.

由 SA 提供Mar 27, 2022

very useful and important to computer science engineering students

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关于 Accounting Data Analytics 专项课程

This specialization develops learners’ analytics mindset and knowledge of data analytics tools and techniques. Specifically, this specialization develops learners' analytics skills by first introducing an analytic mindset, data preparation, visualization, and analysis using Excel. Next, this specialization develops learners' skills of using Python for data preparation, data visualization, data analysis, and data interpretation and the ability to apply these skills to issues relevant to accounting. This specialization also develops learners’ skills in machine learning algorithms (using Python), including classification, regression, clustering, text analysis, time series analysis, and model optimization, as well as their ability to apply these machine learning skills to real-world problems.

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Accounting Data Analytics with Python

课程信息

您将学到的内容有

您将获得的技能

授课教师

Ronald Guymon

Linden Lu

提供方

伊利诺伊大学香槟分校

立即开始攻读硕士学位

授课大纲 - 您将从这门课程中学到什么

INTRODUCTION TO THE COURSE

MODULE 1: FOUNDATIONS

MODULE 2: INTRODUCTION TO PYTHON

MODULE 3: INTRODUCTION TO PYTHON PROGRAMMING

MODULE 4: PYTHON PROGRAMMING

MODULE 5: DATA ANALYSIS WITH PYTHON

MODULE 6: INTRODUCTION TO VISUALIZATION IN PYTHON

MODULE 7: PRODUCTION DATA ANALYTICS

MODULE 8: INTRODUCTION TO DATABASES IN PYTHON

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Accounting Data Analytics with Python

课程信息

您将学到的内容有

您将获得的技能

授课教师

Ronald Guymon

Linden Lu

提供方

伊利诺伊大学香槟分校

立即开始攻读硕士学位

授课大纲 - 您将从这门课程中学到什么

INTRODUCTION TO THE COURSE

MODULE 1: FOUNDATIONS

MODULE 2: INTRODUCTION TO PYTHON

MODULE 3: INTRODUCTION TO PYTHON PROGRAMMING

MODULE 4: PYTHON PROGRAMMING

MODULE 5: DATA ANALYSIS WITH PYTHON

MODULE 6: INTRODUCTION TO VISUALIZATION IN PYTHON

MODULE 7: PRODUCTION DATA ANALYTICS

MODULE 8: INTRODUCTION TO DATABASES IN PYTHON

审阅

来自ACCOUNTING DATA ANALYTICS WITH PYTHON的热门评论

关于 Accounting Data Analytics 专项课程

常见问题

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开拓职业生涯或促进职业发展

Popular Courses and Certifications

Popular collections and articles

在线获得学位或证书

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社区

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