Review: IBM Data Science Professional Certificate

The IBM Data Science Professional Certificate offered on Coursera is one way to gain exposure to machine learning, data science, and Python.


6/18/20223 min read


You may be a person interested in learning the latest technology, and data science is up there on the list of highly sought-after skills by employers.

In this world of rapidly advancing technology, staying up to date with current trends can be a hassle. Nothing stays stagnant in technology, with new frameworks and paradigms coming out every year. It can be hard for professionals and budding students to stay afloat, especially in our busy lives.

With the IBM Data Science Professional Certificate, students can go through the courses at their own pace with lectures on-demand for learners, as well as quizzes given throughout the courses to show the students' progress in learning the material.

There are also plenty of exercises/labs to get hands-on with data science in all of its forms, from courses ranging from learning Python, to working with SQL databases, and then to working with Data Frames creating visuals to analyze datasets. You will find all of this and more in IBM's Data Science Professional Certificate.

After completing each course, you are given an official course badge that you can display on your LinkedIn profile or anywhere else that allows you to showcase completion of each course. At the end of the series of courses, you are given the highly coveted digital certificate to start becoming a Data Science Professional.

There are ten courses in this certificate:

  1. What Is Data Science

  2. Tools For Data Science

  3. Data Science Methodology

  4. Python for Data Science, Ai & Development

  5. Python Project for Data Science

  6. Databases and SQL for Data Science with Python

  7. Data Analysis with Python

  8. Data Visualization with Python

  9. Machine Learning with Python

  10. Applied Data Science Capstone

The tools you will learn in this certificate are: Pandas, Jupyter Notebook, SciPy, Seaborn, GitHub, Watson Studio, SQL, DB2, NumPy, Folium, Scikit-learn, ipython-sql, Python, and a lot of other various tools.

This sounds like a lot, and it can be, especially for beginners in this field.

My Review

I have been working on this certificate for over four years now and have had struggles along the way in completing this course. While the earlier courses do give you exposure, I find that they do not fully prepare you for the culminating Applied Data Science Capstone. The capstone has challenged me to use a lot of outside resources from the IBM Data Science Professional course. I've scoured the web looking at Stack Exchange, Stack Overflow, and a really great site called Towards Data Science.

I've even purchased a course on Udemy to help with understanding Pandas and all of the DataFrame manipulations you will need to learn to become a master with data science, machine learning, and artificial intelligence in general. While I'm not affiliated with Udemy or the instructor of this course, I would recommend giving this course a look if you want to get more experience with DataFrames in general.

The course is called The Complete Pandas Bootcamp 2022: Data Science with Python.

It has been a lot of years since I first started going down this series of courses from IBM, and with my faint memory of what it was like going through the earlier courses, I can tell you that you should try and work through everything as soon as you can. The earlier courses provided knowledge to the libraries and tools you will be using as a data scientist, and the labs are usually written for you to run and see what comes about with the code. These labs provide a good reference for later courses with their labs that have you come up with solutions on your own.

I remember the SQL course being particularly challenging, because it was not like the other courses from earlier. The hand-holding stops with the SQL course, but then it goes back to hand-holding in the next few courses. That's another thing, each course will have different instructors who have different styles of teaching. While I'm used to it due to having gone to a university, this may be challenging for others.

In summary, I am grateful that Coursera has this Data Science Professional Certificate available for students. It's also a big plus that this certificate comes from one of the legends in the technology industry, IBM.

As of this writing, I'm still working on finishing the last course in this series, the Applied Capstone Project. This course especially makes you work your brain and resources to come up with solutions they require in the labs/exercises they provide. I do not think the earlier courses provided even knowledge to tackle the problems they give, and that's after I went through a lot of the earlier labs and tried to use what was learned there to complete this final course.