Machine Learning for Accounting with Python
Master Python-based machine learning for accounting analytics, covering classification, regression, and time series analysis.
Master Python-based machine learning for accounting analytics, covering classification, regression, and time series analysis.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Accounting Data Analytics Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.6
(41 ratings)
9,306 already enrolled
Instructors:
English
پښتو, বাংলা, اردو, 2 more
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What you'll learn
Apply various machine learning algorithms to accounting problems
Implement classification and regression models using Python
Perform text analysis and time series analysis on financial data
Evaluate and optimize machine learning models
Develop practical skills in using Jupyter Notebook for data analysis
Skills you'll gain
This course includes:
2.8 Hours PreRecorded video
8 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 9 modules in this course
This comprehensive course introduces machine learning algorithms and their applications in accounting. It covers classification, regression, clustering, text analysis, and time series analysis, with a focus on model evaluation and optimization. Students learn to apply machine learning models to business datasets using Python in Jupyter Notebook, building on prerequisites from Accounting Data Analytics with Python. The course completes the data analytics process by covering modeling and model evaluation, enabling students to perform end-to-end data analytics in accounting contexts.
Introduction to the Course
Module 1 · 1 Hours to complete
Introduction to Machine Learning
Module 2 · 8 Hours to complete
Fundamental Algorithms I
Module 3 · 8 Hours to complete
Fundamental Algorithms II
Module 4 · 7 Hours to complete
Model Evaluation
Module 5 · 8 Hours to complete
Model Optimization
Module 6 · 7 Hours to complete
Introduction to Text Analysis
Module 7 · 8 Hours to complete
Introduction to Clustering
Module 8 · 7 Hours to complete
Introduction to Time Series Data
Module 9 · 7 Hours to complete
Fee Structure
Instructor
Instructor of Accountancy
Linden Lu is an Instructor of Accountancy at the University of Illinois Urbana-Champaign, where he has been teaching since 2017. He holds multiple degrees, including an M.S. in Finance from UIUC, an M.S. in Computer Science from Indiana University, and a B.S. in Computer Science from Tsinghua University. His diverse educational background equips him with a unique perspective on the integration of technology and accounting practices.Professor Lu specializes in courses that merge accounting with data analytics and machine learning, offering classes such as "Accounting Data Analytics with Python" and "Machine Learning for Accounting with Python." His teaching focuses on equipping students with the skills to analyze financial data using advanced analytical techniques, preparing them for the evolving demands of the accounting profession. Recognized for his excellence in teaching, he has consistently been listed among the faculty ranked as excellent by students. Through his innovative approach to education, Linden Lu is dedicated to fostering a new generation of accountants who are proficient in data analytics and technology-driven solutions.
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4.6 course rating
41 ratings
Frequently asked questions
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