About this Course

12,224 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.
Course 6 of 6 in the
Intermediate Level

Comfort with Python and completion of the prerequisite IBM Machine Learning Professional Certificate. 

Approx. 19 hours to complete
English

What you will learn

  • Compare and contrast different machine learning algorithms by creating recommender systems in Python

  • Develop a final project using machine learning methods and evaluate your peers’ projects

  • Predict course ratings by training a neural network and constructing regression and classification models

  • Create recommendation systems by applying your knowledge of KNN, PCA, and non-negative matrix collaborative filtering

Skills you will gain

  • Artificial Neural Network
  • Python Programming
  • Data Analysis
  • Supervised Learning
  • unsupervised machine learning
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.
Course 6 of 6 in the
Intermediate Level

Comfort with Python and completion of the prerequisite IBM Machine Learning Professional Certificate. 

Approx. 19 hours to complete
English

Offered by

Placeholder

IBM Skills Network

Syllabus - What you will learn from this course

Week
1

Week 1

23 minutes to complete

Capstone Overview

23 minutes to complete
2 videos (Total 8 min)
Week
2

Week 2

4 hours to complete

Exploratory Data Analysis and Feature Engineering

4 hours to complete
Week
3

Week 3

4 hours to complete

Unsupervised-Learning Based Recommender System

4 hours to complete
1 video (Total 5 min)
Week
4

Week 4

6 hours to complete

Supervised-Learning Based Recommender Systems

6 hours to complete
1 video (Total 7 min)

About the IBM Machine Learning Professional Certificate

IBM Machine Learning

Frequently Asked Questions

More questions? Visit the Learner Help Center.