About this Course

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100% online
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Intermediate Level

A working knowledge of Python and Data Analysis and Visualization techniques. A minimum of high school math.  

Approx. 13 hours to complete
English

What you will learn

  • Describe the various types of Machine Learning algorithms and when to use them 

  • Compare and contrast linear classification methods including multiclass prediction, support vector machines, and logistic regression 

  • Write Python code that implements various classification techniques including K-Nearest neighbors (KNN), decision trees, and regression trees 

  • Evaluate the results from simple linear, non-linear, and multiple regression on a data set using evaluation metrics 

Skills you will gain

  • SciPy and scikit-learn
  • Machine Learning
  • regression
  • classification
  • Hierarchical Clustering
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

A working knowledge of Python and Data Analysis and Visualization techniques. A minimum of high school math.  

Approx. 13 hours to complete
English

Offered by

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IBM Skills Network

Start working towards your Bachelor's degree

This course is part of the 100% online Bachelor of Science in Computer Science from IBM Skills Network. If you are admitted to the full program, your courses count towards your degree learning.

Syllabus - What you will learn from this course

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Week
1
Week 1
1 hour to complete

Introduction to Machine Learning

1 hour to complete
5 videos (Total 29 min)
Week
2
Week 2
2 hours to complete

Regression

2 hours to complete
5 videos (Total 43 min)
Week
3
Week 3
4 hours to complete

Classification

4 hours to complete
5 videos (Total 35 min), 1 reading, 7 quizzes
Week
4
Week 4
3 hours to complete

Linear Classification

3 hours to complete
4 videos (Total 46 min), 1 reading, 5 quizzes

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