Making Time for Data Analytics Training

My life over the past few months would be best described by this Michael McIntyre skit about trying to leave the house whilst telling the kids to find their shoes and put on their jackets. You can imagine the time I have for training is minimal. However, I wanted to quickly summarize my take on these Massive Open Online Course (MOOCs) that I started but have not yet completed:

1. Analytics edge on edx

2. The data science specialization on coursera

3.  The data analyst nanodegree on udacity

The analytics edge was a 12 week course of which I completed the first two weeks. I missed a deadline for one of the homework assignments at that point which meant I could not keep up and complete the course as I had wanted. The score required to get the verified certificate for this course is quite low but the material is challenging (especially later) and the homework assignments, while not extremely difficult, are in depth and long. The course focuses on real life applications of analytics which makes the material interesting and the lectures easier to digest.

The data science specialization consists of nine courses, of which I completed the first: the data scientist’s toolbox. This was essentially a guide to get yourself set up on Github. I registered and paid for the second, but had to request the refund as the first week went by and I had not managed to watch a single lesson. The tool used for this series of courses is R and the approach is more academic (and “statistics based”) than the next series of courses including courses on regression and statistical inference. One of the courses that particularly peaked my interest was “getting and cleaning data”. Personally, I would prefer to choose one or two courses like the last from this series in order to hone specific skills, while skipping material that is already familiar to me.

For the udacity nanodegree, I only registered for the one-week free trial and looked around. This is a very practical and in depth series of courses and it was obvious that it required a commitment in time and effort which I could not make. In addition it is a series of courses which costs 200 dollars per month so the commitment also has a real monetary cost attached to it. However, at the end of the “9 to 12 months” projected to complete the course, you would have gone through a portfolio of projects that are both detailed and diverse.

There are some additional courses I’ve looked into; for example this excel course which explores some of the newest Microsoft analytics tools such as power BI and power query.

Hopefully, I can return next time with a review of a completed course but I believe I have provided some useful leads for anyone wanting to take courses in data analytics. If you have a spare hour or two each day, the most valuable and rewarding gift you can give yourself is one of these courses.

Michael Lazarou
Michael Lazarou
Michael Lazarou manages revenue assurance and fraud at Epic, a Cypriot telco, having joined their RA function in March 2011. His background includes a double major in Computer Science and Economics, as well as an MBA. Before being lured into the exciting world of telecoms he worked as a software developer.

Michael is interested to gain a better understanding of different aspects of RA and data analysis. He shares his insights on training courses he participates in with Commsrisk. Michael's accumulated experience of online training also led him to volunteer for the role of Coordinator of the RAG Learning online education platform.