About this Course

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Shareable Certificate
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100% online
Start instantly and learn at your own schedule.
Flexible deadlines
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Intermediate Level
Approx. 63 hours to complete
English

Skills you will gain

Text AnalysisBasic Time Series AnalysisMachine Learning Model Evaluation and OptimizationPython ProgrammingMachine Learning Modeling
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 63 hours to complete
English

Offered by

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University of Illinois at Urbana-Champaign

Start working towards your Master's degree

This course is part of the 100% online Master of Science in Accountancy (iMSA) from University of Illinois at Urbana-Champaign. If you are admitted to the full program, your courses count towards your degree learning.

Syllabus - What you will learn from this course

Week
1

Week 1

1 hour to complete

INTRODUCTION TO THE COURSE

1 hour to complete
2 videos (Total 9 min), 3 readings
2 videos
About Linden Lu3m
3 readings
Syllabus10m
Glossary10m
Update Your Profile10m
8 hours to complete

MODULE 1: INTRODUCTION TO MACHINE LEARNING

8 hours to complete
4 videos (Total 24 min), 1 reading, 2 quizzes
4 videos
1.1 Introduction to Machine Learning6m
1.2 Introduction to Data Preprocessing10m
1.3 Introduction to Machine Learning Algorithms3m
1 reading
Module 1 Overview and Resources10m
1 practice exercise
Module 1 Quiz20m
Week
2

Week 2

8 hours to complete

MODULE 2: FUNDAMENTAL ALGORITHMS I

8 hours to complete
4 videos (Total 31 min), 1 reading, 2 quizzes
4 videos
2.1 Introduction to Linear Regression12m
2.2 Introduction to Logistic Regression8m
2.3 Introduction to Decision Tree6m
1 reading
Module 2 Overview and Resources10m
1 practice exercise
Module 2 Quiz20m
Week
3

Week 3

8 hours to complete

MODULE 3: Fundamental Algorithms II

8 hours to complete
4 videos (Total 15 min), 1 reading, 2 quizzes
4 videos
3.1 Introduction to K-nearest Neighbors5m
3.2 Introduction to Support Vector Machine4m
3.3 Introduction to Bagging and Random Forest3m
1 reading
Module 3 Overview and Resources10m
1 practice exercise
Module 3 Quiz20m
Week
4

Week 4

8 hours to complete

MODULE 4: MODEL EVALUATION

8 hours to complete
4 videos (Total 31 min), 1 reading, 2 quizzes
4 videos
4.1 Regressive Evaluation Metrics8m
4.2 Classification Evaluation Metrics I13m
4.3 Classification Evaluation Metrics II7m
1 reading
Module 4 Overview and Resources10m
1 practice exercise
Module 4 Quiz20m

About the Accounting Data Analytics Specialization

Accounting Data Analytics

Frequently Asked Questions

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