Studying 'IBM Data Science' on Coursera? Tackle 'Introduction to Data Science' first

1 March 2020

If you are looking to gain a solid grounding in data science, then online learning platform Coursera is a good place to start. Its IBM Data Science Professional Certificate program is certainly proving popular, with more than 120,000 users enrolled to date.

To achieve the Professional Certificate, learners have to work through a curriculum of nine courses (or, as I would call them, modules). There is no set schedule, but Coursera suggests dedicating 12 hours per week for approximately three months. That's around 150 hours of study - a fairly considerable investment of time.

What Coursera does not highlight particularly clearly is that four of the courses in the IBM Data Science Professional Certificate program make up a so-called 'Specialization' called Introduction to Data Science. In effect, the Specialization courses are a subset of the Professional Certificate courses, and together require around 50 hours of study according to Coursera's suggestion. (I completed the Specialization myself in 46 days trying to dedicate an hour a day, so that sounds about right.)

Enroll and pass

What that means is that once you have completed these four courses as part of the Professional Certificate, it is worth enrolling in the Specialization (at no extra cost) to immediately pass it. Alternatively, you could enroll in the Specialization first, complete this, and then continue on with the rest of the courses in the Professional Certificate. Either approach would give the same results, though Coursera suggests the latter in its FAQs:

If you are unsure about your ability to commit to the level of effort and time required to complete this Professional Certificate, we recommend starting with the Introduction to Data Science Specialization, which has fewer courses. And if after earning the specialization certificate you are still determined to continue building your Data Science skills, you can then enroll for this Professional Certificate and then just complete the courses that are not in the specialization.

It's notable that only 24,000 learners have enrolled in the Specialization, which suggests that the majority of those studying towards the Professional Certificate are unaware they can claim the Specialisation too (either that, or Coursera has a low course completion rate!).

The four courses that appear in the IBM Data Science Professional Certificate program and which constitute the Introduction to Data Science Specialization are:

  • What is Data Science?
  • Open Source Tools for Data Science
  • Data Science Methodology
  • Databases and SQL for Data Science

These are actually courses 1, 2, 3 and 5 of the Professional Certificate.

Order of completion

Why am I telling you this? The courses in the Professional Certificate can be completed in any order, and so I would be tempted to work through the ones that appear in the Specialization first - completing course 5, Databases and SQL for Data Science, before course 4, Python for Data Science and AI (the SQL course does touch on Python a little, but not enough to make the Python course a prerequisite).

That way, if life forces you to stop working towards the Professional Certificate for any reason - time, health or finance spring to mind - you are more likely to be in a position to be able to claim the Specialization and will have that at least to show for your efforts.

But whether you are working towards the Specialization, the Professional Certificate or just tackling the odd course here and there - best of luck from me on your data science journey!

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