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).
Dieser Kurs ist Teil der Spezialisierung Spezialisierung Accounting Data Analytics
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von
Spezialisierung Accounting Data AnalyticsUniversity of Illinois at Urbana-ChampaignÜber diesen Kurs
20.033 kürzliche Aufrufe
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Kurs 2 von 4 in
Stufe „Mittel“
Ca. 35 Stunden zum Abschließen
Englisch
Untertitel: Englisch
Was Sie lernen werden
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.
Kompetenzen, die Sie erwerben
- Python Programming
- Data Visualization (DataViz)
- Linear Regression
- SQL
- Data Preparation
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Kurs 2 von 4 in
Stufe „Mittel“
Ca. 35 Stunden zum Abschließen
Englisch
Untertitel: Englisch
von
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.
Beginnen Sie damit, auf Ihren Master-Abschluss hinzuarbeiten.
Dieses Kurs ist Teil des reinen Onlineabschlusses Master of Science in Accountancy (iMSA) von University of Illinois at Urbana-Champaign.
Wenn Sie in das komplette Programm aufgenommen werden, werden Ihre Kurse auf Ihren Abschluss angerechnet.
Lehrplan - Was Sie in diesem Kurs lernen werden
1 Stunde zum Abschließen
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.
1 Stunde zum Abschließen
4 Videos (Gesamt 12 min), 5 Lektüren
4 Stunden zum Abschließen
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.
4 Stunden zum Abschließen
14 Videos (Gesamt 84 min), 2 Lektüren, 2 Quiz
4 Stunden zum Abschließen
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.
4 Stunden zum Abschließen
12 Videos (Gesamt 72 min), 1 Lektüre, 2 Quiz
5 Stunden zum Abschließen
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.
5 Stunden zum Abschließen
15 Videos (Gesamt 85 min), 1 Lektüre, 2 Quiz
4 Stunden zum Abschließen
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.
4 Stunden zum Abschließen
5 Videos (Gesamt 16 min), 1 Lektüre, 2 Quiz
Bewertungen
Top-Bewertungen von ACCOUNTING DATA ANALYTICS WITH PYTHON
von SM27. Juni 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.
von EG30. Nov. 2020
It is very easy to learn and also very interesting because you can modify and try other things.
Über den Spezialisierung Accounting Data Analytics
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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