This Machine Learning Capstone course uses various Python-based machine learning libraries, such as Pandas, sci-kit-learn, and Tensorflow/Keras. You will also learn to apply your machine-learning skills and demonstrate your proficiency in them. Before taking this course, you must complete all the previous courses in the IBM Machine Learning Professional Certificate.
In this course, you will also learn to build a course recommender system, analyze course-related datasets, calculate cosine similarity, and create a similarity matrix. Additionally, you will generate recommendation systems by applying your knowledge of KNN, PCA, and non-negative matrix collaborative filtering.
Finally, you will share your work with peers and have them evaluate it, facilitating a collaborative learning experience.
Status: Scikit Learn (Machine Learning Library)
Scikit Learn (Machine Learning Library)
Status: Python Programming
Python Programming
Advanced·Course·20 hours
Featured reviews
5.0
·Reviewed Apr 9, 2025
I learned so much by completing the machine learning capstone project. I encourage anyone who decides to take this course to explore the deeper nuances of each type of recommender system.
4.0
·Reviewed Mar 23, 2024
It was really a quite informative and well planned course. Will continue to get more Professional Certificate from IBM related to ML-DL and Generative AI
5.0
·Reviewed Apr 16, 2025
Really great course which combines informational videos with hands on labs. The projects at the end are great fun and an awesome way to apply what you've learnt during the course.
5.0
·Reviewed Jun 26, 2025
Amazing Project to work on and gain more knowledge of Machine Learning Techniques
4.0
·Reviewed Oct 19, 2025
helpfull
5.0
·Reviewed Aug 28, 2024
good for getting overview of different machine learning ways
4.0
·Reviewed Oct 25, 2025
all is good but little diffuclt on seeing the videos and understand
All reviews
Showing: 20 of 46
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D
Dan
4.0
·Reviewed Jul 21, 2023
This was an interesting summary to the specialisation. It covered topics from each of the courses while covering one new topic - recommender systems. It's not substantial enough to stand on it's own as a course, but acts as a "final exam/coursework" for the machine learning specialisation.
D
Deborah
5.0
·Reviewed Apr 9, 2025
I learned so much by completing the machine learning capstone project. I encourage anyone who decides to take this course to explore the deeper nuances of each type of recommender system.
B
Bartosz
5.0
·Reviewed Apr 17, 2025
Really great course which combines informational videos with hands on labs. The projects at the end are great fun and an awesome way to apply what you've learnt during the course.
S
Susanne
5.0
·Reviewed Dec 12, 2025
There was a lot to learn, the videos were good, the labs worked well but it took a lot more time then was suggested.
M
Mateo
5.0
·Reviewed Jul 15, 2025
Un curso excelente. Aborda muchos temas de interés en tema de ciencia de datos e IA. Recomendado
G
Gosavi
5.0
·Reviewed Jun 27, 2025
Amazing Project to work on and gain more knowledge of Machine Learning Techniques
A
Abhisekh
5.0
·Reviewed Aug 29, 2024
good for getting overview of different machine learning ways