About this Course

7,828 recent views
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Intermediate Level
Approx. 64 hours to complete
English

What you will learn

  • 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.

Skills you will gain

  • Text Analysis
  • Basic Time Series Analysis
  • Machine Learning Model Evaluation and Optimization
  • Python Programming
  • Machine Learning Modeling
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Intermediate Level
Approx. 64 hours to complete
English

Instructor

Offered by

Placeholder

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
3 videos (Total 10 min), 4 readings
8 hours to complete

MODULE 1: INTRODUCTION TO MACHINE LEARNING

8 hours to complete
4 videos (Total 24 min), 1 reading, 2 quizzes
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
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
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

About the Accounting Data Analytics Specialization

Accounting Data Analytics

Frequently Asked Questions

More questions? Visit the Learner Help Center.