Advanced Data Science with IBM

https://www.coursera.org/specializations/advanced-data-science-ibm

Such empty! Here's a question for those in ML/AI/data science:
I'm compensating for my degree not having AI/ML modules with Coursera and I'm currently on the advanced data science specialization from IBM but they also offer a mixed level professional certification. Are they equivalent or is one better than the other for my case of wanting to get into AI/data science jobs? Looks to me like the 'advanced' is more suited for someone already experienced with the topics and the 'professional' one spends ages teaching people basics of coding and data and whatnot so could include needless repetition of known topics for me graduating with MEng SWE in July.
How would employers/recruiters see the two in comparison?

Just finished this ( https://www.coursera.org/professional-certificates/ibm-data-science? ) data science course on Coursera.

Would the advanced data science course be something that I can actually benefit from or is it still too early for me to try? https://www.coursera.org/specializations/advanced-data-science-ibm?

@ herbertbailbonds

Considering that i work full time, it took me about 2-3 months by studying just a couple of nights per week. I had 0 experience too on Python, but i come from a CS master, while i have a super-solid sql background.

Just as a rough estimate, if you were to study full time it would take a couple of weeks to complete at most (8 hours/day).

As regards the career, if you really want to improve you should study This book, which is basically a deeper dive into the course arguments. After that you can either choose to stop an start making a couple of projects on your own to showoff your skill and improve in this directior, or dive into other subjects (like NLP and Neural Networks). In the end to answer your question: No, it did not improve my career, you need to study more :)

@ The_Real_BruceWayne

The course i'm talking about is This one

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I'm currently working my way through Coursera (and others) - I'm aiming for more of a lateral move from Data Engineering into Data Science, still deciding where I might go as I learn more. Therefore please take my advice with a pinch of salt but if it helps; here's a bit of a review of what I've tried so far:

Depending upon how good your Python skills are, I really recommend dataquest.io. It teaches Python from scratch and does a deep dive on Numpy & Pandas. It then covers a Data Science pathway that covers the scikit-learn library in-depth and more high level coverage of other areas (inc. Spark). The whole pathway is 250 hrs and last I checked was about $30-50 pcm (cheaper annual package).

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I've also started the MIT MicroMasters (on EDX). This is very heavy on the Maths. I've enjoyed it but found it very challenging. It's $1,100 but follows a strict schedule. I've read elsewhere that the MIT course is like learning how to build a plane from scratch, and then learn how to fly it - and so there are more suitable courses if all you want to do is learn how to fly a plane.

I've just about finished a Coursera module on the maths of machine learning - this is to help boost my maths for the MIT https://www.coursera.org/specializations/mathematics-machine-learning

Next up for me is an IBM module, probably starting this weekend https://www.coursera.org/specializations/advanced-data-science-ibm

One to avoid. I tried this Data Science path by Michigan University. I didn't rate it at all. I knew most of what they were teaching from DataQuest and I still found it confusing so I quite after completing the 1st module. https://www.coursera.org/specializations/data-science-python

As a final thought, it sounds like you've already found your chosen area of Data Science and are going to get a masters in it. Do you really need the 2nd masters from local college? If you're going to be an expert in Eduction maybe just look to boost your DS skills with some specialist Coursera modules, etc - rather than pay a lot of money for a 2nd masters (no idea how much local college costs). But anyway, hopefully someone more qualified than me will give some insight on the latter point.

Best of luck!

Planning on doing these Coursera courses in this order:

https://www.coursera.org/specializations/data-science-foundations-r

https://www.coursera.org/specializations/introduction-data-science

https://www.coursera.org/specializations/applied-data-science

https://www.coursera.org/specializations/ai-foundations-for-everyone

https://www.coursera.org/specializations/data-science-statistics-machine-learning

https://www.coursera.org/specializations/ibm-intro-machine-learning

https://www.coursera.org/specializations/deep-learning

https://www.coursera.org/specializations/advanced-data-science-ibm

I want to become proficient enough in Data Science to be able to have it as a "tool in my toolbox." What are your thoughts on my self-teaching course plan?