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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.
Instructors: Linden Lu
10,806 already enrolled
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(184 reviews)
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Intermediate level
Programming background would be a plus, but not mandatory.
(184 reviews)
Recommended experience
Intermediate level
Programming background would be a plus, but not mandatory.
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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.
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.
Articulate the benefits of using Big Data and analytics in the modern accounting profession.
Describe and implement a framework for using Big data to help provide insights that lead to action.
Critique the ability of a dataset to answer questions, then assemble data from different sources for summarization, visualization, and analysis.
Use Excel, Tableau, and Visual Basic for Applications to design and perform basic and advanced analyses.
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.
The concept of various machine learning algorithms.
How to apply machine learning models on datasets with Python in Jupyter Notebook.
How to evaluate machine learning models.
How to optimize machine learning models.
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.
This Specialization is part of the following degree program(s) offered by University of Illinois Urbana-Champaign. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹
This Specialization is part of the following degree program(s) offered by University of Illinois Urbana-Champaign. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹
University of Illinois Urbana-Champaign
Degree · 1.5 – 3 years
University of Illinois Urbana-Champaign
Degree · 6-10 months
¹Successful application and enrollment are required. Eligibility requirements apply. Each institution determines the number of credits recognized by completing this content that may count towards degree requirements, considering any existing credits you may have. Click on a specific course for more information.
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Time to completion can vary widely based on your schedule, most learners are able to complete the Specialization in 5-7 months.
Basic understanding of Microsoft Excel is recommended
It is recommended that the courses in the Specialization be taken in the order outlined.In the Capstone Project, you will have the opportunity to synthesize your learning in all courses and apply your combined skills in a final project
You will be able to understand how to operate software that will help you create, run and execute Python code for wrangling data from different structures into a Pandas dataframe structure.
You will also be able to run and interpret fundamental data analytic tasks in Python including descriptive
Courses on Coursera do not carry University of Illinois credit on their own. Each iDegree course has an enhanced for-credit component. You can earn academic credit if you combine an open online course with the enhanced for-credit component offered on the University of Illinois platform. To learn more visit https://giesbusiness.illinois.edu/graduate-hub/online. Some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.
Each course in the Specialization offers regular and open enrollment. You can begin and complete the course on your own schedule.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you only want to read and view the course content, you can audit the course for free. If you cannot afford the fee, you can apply for financial aid.
This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
Please find more information at https://giesbusiness.illinois.edu/graduate-hub/online or email your questions to giesonline@illinois.edu
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.