Masterful MOOCs, Completed Certificates, and What I’ve Learned So Far

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If you are not already familiar with Massive Open Online Courses (MOOCs), here’s a brief introduction of the learning ideology that is reshaping modern education. MOOCs are relevant, flexible, and specific to commonly-desired topics. More accurately, they are online courses which are open to anyone who wants to enroll. Note that this does not necessarily mean free; more on this later. They are often taught by top-notch professors or practitioners in their respective fields. The fact that this quality education content has been made available outside of the university setting is one of the biggest reasons these have been so massively popular.


First off, why should a programmer, data scientist, manager, teacher or any one else invest time in formally completing these? Put another way, what is the professional or marketable value of completing them? The most obvious is continuous learning aspect and to learn the subject matter, especially for those who have departed from academia for some time. But there are so many ways to learn a given topic in our modern society that can be completely a la carte. Take a simple example of somebody who wants to learn a new programming language, perhaps R. They could simply pick up books, watch YouTube videos, read GitHub repos, or a slew of other miscellaneous methods to begin their journey of becoming an expert in statistical analysis with R. You could make the case that because the course content is professionally produced by top-notch universities, the major benefit of the courses is in learning from some of the best academic resources in the world. While the content of the online course is structured and usually high-quality content, the content alone cannot be the cause of their success.

I believe the real value of completing MOOCs certificates has two facets. It sets a concrete bite-sized goal with a low barrier to entry and it sends a message about the educational attitude of an individual. A true professional in any field will exhibit a commitment to continuous learning. This is true whether the individual is just starting out or has 30 years experience. They will use many resources to fill in gaps in learning that has become dated or stale by several means. However, it is the very fact that there is still a time commitment involved and structure that facilitates completion of the course or series.


Should I ‘audit’ a course or obtain the certificate? Many of the online learning sites allow you to take a course for free as an audit of the course material. In many cases this may be preferable especially if you want to just try it out or perhaps take a preview of the content for a few weeks. However, if you want to have your work graded, you will usually need to signup and pay. Most of the sites also give you a certificate of completion if you pass under this paid plan. Note that obtaining a certificate often (but not always) means paying. Racking up a bunch of certificates may or may not help you meet your career objectives but I’ve found that it does help in one very important way, motivation. By paying and setting a completion goal, you’ve get extra motivation for spending dedicated time and actually finishing.

So are these online course certificate programs destined to take their place alongside coding boot-camps and trade-specific college programs as the new de facto secondary education model in United States? Not likely in my opinion, at least in the near term. However, their relevance as a tool for keeping up with today’s fast-moving workforce and ever changing technology environment is undeniable.


I’ve taken several courses in the past for various topics in mathematics, business topics, education, computer science, data science, and even sales. Many of them were taken as a refresher for stuff I learned in college, others were to learn something new. I was less committed to several of them simply because I did not intend to take the full course from the start. I’ve taken courses from EdX, Khan, and Udacty but my favorite format is Coursera. The structure of the online presentation works best for me. As such many of my completed certificates have been through Coursera.

My favorites so far have been a couple of machine learning classes taught by Andrew Ng. The classic Stanford Machine Learning course and the more recent Deep Learning specialization series have provided a good basis for an introductory understanding of the core concepts. The details for the specialization series can be found here. What I liked about them is the approachable overview of the fundamentals of machine learning. Professor Ng does an excellent job of explaining the concepts in a concise and relevant manner. It is by no means a comprehensive study but gives you enough to seek further learning in the area.

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Basic Neural Net Computation Diagram

The Deep Learning course also provides some good exercises using modern machine learning techniques which guide you through the coding your own experimental models. You will learn core concepts of parameter initialization, forward propagation, back propagation and learning rate evaluation. You will explore optimization models starting with basic gradient descent, through mini-batch, momentum and adam methods. You will work on real datasets and train your own image classification system. It was great to have my own working model in a relatively short period of time, even if the accuracy rate needed improvement. It was an efficient way to learn the models required.

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Learning rate output for gradient descent optimizer from course assignment

I think it’s important to maintain a certain level of zeal when it comes to continuous learning. Self-study online courses can be a great way to do this. They are not for everyone but for those who enjoy self-motivated study, they provide a proven format for building your professional skills.

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