- Machine Learning
- Python Programming
- Data Visualization (DataViz)
- Data Preparation
- Exploratory Data Analysis
- Data Analysis
- Predictive Analytics
- Data Architecture
- coding
- Linear Regression
- SQL
- Text Analysis
Accounting Data Analytics Specialization
Develop Data Analytics Skills for Accountants. This specialization develops students’ skills of data preparation, data visualization, data analysis, data interpretation, and machine learning algorithms and their applications to real-world problems.
Offered By
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
About this Specialization
Applied Learning Project
Projects included in this specialization allow learners to apply the skills developed within the data analytics specialization to real-world problems. Learners will be able to articulate the general process of the CRISP-DM framework, demonstrate data analytics skills in data preparation, data visualization, modeling, and model evaluation, and apply data analytics knowledge and skills to real-world problems. For example, in the capstone project, learners will develop a machine learning model in order to predict whether a loan is to be fully paid and construct a loan portfolio with the help of the analysis.
Programming background would be a plus, but not mandatory.
Programming background would be a plus, but not mandatory.
How the Specialization Works
Take Courses
A Coursera Specialization is a series of courses that helps you master a skill. To begin, enroll in the Specialization directly, or review its courses and choose the one you'd like to start with. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. It’s okay to complete just one course — you can pause your learning or end your subscription at any time. Visit your learner dashboard to track your course enrollments and your progress.
Hands-on Project
Every Specialization includes a hands-on project. You'll need to successfully finish the project(s) to complete the Specialization and earn your certificate. If the Specialization includes a separate course for the hands-on project, you'll need to finish each of the other courses before you can start it.
Earn a Certificate
When you finish every course and complete the hands-on project, you'll earn a Certificate that you can share with prospective employers and your professional network.
There are 4 Courses in this Specialization
Introduction to Accounting Data Analytics and Visualization
Accounting has always been about analytical thinking. From the earliest days of the profession, Luca Pacioli emphasized the importance of math and order for analyzing business transactions. The skillset that accountants have needed to perform math and to keep order has evolved from pencil and paper, to typewriters and calculators, then to spreadsheets and accounting software. A new skillset that is becoming more important for nearly every aspect of business is that of big data analytics: analyzing large amounts of data to find actionable insights. This course is designed to help accounting students develop an analytical mindset and prepare them to use data analytic programming languages like Python and R.
Accounting Data Analytics with Python
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).
Machine Learning for Accounting with Python
This course, Machine Learning for Accounting with Python, introduces machine learning algorithms (models) and their applications in accounting problems. It covers classification, regression, clustering, text analysis, time series analysis. It also discusses model evaluation and model optimization. This course provides an entry point for students to be able to apply proper machine learning models on business related datasets with Python to solve various problems.
Data Analytics in Accounting Capstone
This capstone is the last course in the Data Analytics in Accountancy Specialization. In this capstone course, you are going to take the knowledge and skills you have acquired from the previous courses and apply them to a real-world problem.
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.
Start working towards your Master's degree
Frequently Asked Questions
What is the refund policy?
Can I just enroll in a single course?
Is financial aid available?
How long does it take to complete the Specialization?
What background knowledge is necessary?
Do I need to take the courses in a specific order?
What will I be able to do upon completing the Specialization?
Will I earn university credit for completing the Specialization?
How often is each course in the Specialization offered?
Can I take the course for free?
Is this course really 100% online? Do I need to attend any classes in person?
Where can I learn more and ask questions about earning credit or a degree from the University of Illinois at Urbana-Champaign?
More questions? Visit the Learner Help Center.