Data science project update

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I finally completed my IBM data science specialization. I completed the 8 first courses of the specialization very fast but the last course took me for ever. I met all kinds of technical issues and had to simplify my final project to the point that I feared I would not get a passing grade. However, this worked and I am really relieved the course is finally over.

This does not mean I am over with data science. I want to learn more about this field. The IBM data science specialization was great to have a broad view of different aspects of data science and improve my Python skills. However, I will need to review some of the points seen if I really want to master them.

Here is a list of the 9 courses of the specialization:

  1. What is data science?
  2. Tools for data science
  3. Data Science methodology
  4. Python for data science and AI
  5. Databases and SQL for data science
  6. Data Analysis with Python
  7. Data visualization with Python
  8. Machine learning with Python
  9. Applied data science capstone

I also took a couple of other courses as I was blocked so long on the last course. I guess you can call it procrastination but I am still happy I took these courses. Here are the other courses I took:

  • Data Science Math Skills, Duke University: this course aims to give you the basic math skills you need for data science. This was a good reminder for me as I had seen many of the notions of the course when still in high school and I had forgotten some of them.
  • AI for Everyone, : This is a very good introduction course fabout artificial intelligence. It was easy to follow but I still learnt a lot.
  • Programming for Everybody (Getting Started with Python), University of Michigan: I have already followed a course on Python with Codecademy so the course was easy for me. This is the first of the 5 courses of the Python for Everybody specialization of the University of Michigan. I wanted to try the course to learn Python in a deeper way and see how well I do with the assignments.

Related posts

You can see below my previous posts on the project:


  • Dianne Horvath

    Your article sort of stopped half way through something? Or did I miss the icon that said read further? You didn’t say what your ultimate goal is or why you chose this area, or did I need to be a reader from your first post to know all this? I’m not trying to be critical, it’s just that I stumbled upon your blog and this is the 3rd one I’m reading, and I love reading your work, I’d say because I love learning just as much as you do so I love reading about your experiences. Honestly! it helps me learn something without having to enrol in yet another course. My list is endless too.
    So please let me know if there was more to this post? Thx for sharing.

    • momslovelearning

      I am afraid I oversaw your comment… Sorry for the late answer and thanks for the feedback. This post was just supposed to be a short update. I added links to former posts in which the data science project is described more precisely.

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