This week, I was sick and had to stay home. This was of course bad but this gave me the opportunity both to spend more time with the children (also sick at home) and to work on my data science course. And I finally completed the course 8: Machine learning with Python
Course 8: Machine learning with Python
I completed the course on December 10th 2019. This was an interesting course. You learn for instance how recommendation systems work on popular websites such as Amazon or Netflix.
The part on regression was not totally new. I had already seen these notions in previous courses. However, the parts on classification, clustering and recommendations included a lot of new information and techniques and it was a lot of work.
The final assignment focused mainly on classification so this is the part of the course which I master best now. However, I found the questions in the assignment not always quite clear, and you have to check the course forum to understand really what is expected.
Course 9: Applied data science capstone
This is the very last course and it will enable me to work on a “real life” data science project. I am curious about how difficult it will be. According to the course description, it should take 5 weeks of studies or a total of 45 hours. I found that the expected time of completion for other courses was not always accurate though, so I will see how long it will really take me. When I complete the course, I will receive a IBM data science professional certificate.
You can see below my previous posts on the project:
- My goals for September -> first presentation of the project
- Book review: Ultralearning (Scott H Young) ->the post is actually about the book Ultralearning but at the end of the article I am showing how the book helped me to define my data science project better
- Data science project: first weeks -> description of the first courses I took
- Data Science project: October update -> an update on the data science project
- Data science project: November update-> an update on the data science project
- Data visualization and machine learning -> an update on the courses 7 and 8