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).
This course is part of the Accounting Data Analytics Specialization
Offered By
About this Course
What you will learn
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.
Skills you will gain
- Python Programming
- Data Visualization (DataViz)
- Linear Regression
- SQL
- Data Preparation
Offered by
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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Syllabus - What you will learn from this course
INTRODUCTION TO THE COURSE
In this module, you will become familiar with the course, your instructor and your classmates, and our learning environment. This orientation module will also help you obtain the technical skills required to navigate and be successful in this course.
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.
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.
MODULE 3: INTRODUCTION TO PYTHON PROGRAMMING
In this module you will learn about working with fundamental data structures in Python: strings, tuples, lists, and dictionaries. You will also learn about how to write loops for performing repetitive tasks.
MODULE 4: PYTHON PROGRAMMING
In this module you will learn about creating and using modules, which is a group of functions. You will then learn about two of the most important modules for data analytics: NumPy and Pandas. NumPy performs numerical calculations on large data arrays. Pandas simplifies procedures for working with panel data, also known as dataframes.
Reviews
- 5 stars55.07%
- 4 stars26.08%
- 3 stars7.24%
- 2 stars8.69%
- 1 star2.89%
TOP REVIEWS FROM ACCOUNTING DATA ANALYTICS WITH PYTHON
It is very easy to learn and also very interesting because you can modify and try other things.
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.
very useful and important to computer science engineering students
About the Accounting Data Analytics Specialization
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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