Adventures & experiences in contemporary technology
Recently, I shared my thoughts on learning new computing languages by oneself using books, online research and personal practice. As successful as that can be, there remains a place for getting some actual instruction as well. Maybe that is why so many turn to YouTube, where there is a multitude of video channels offering such possibilities without cost. What I have also discovered is that this is complemented by a host of other providers whose services attract a fee, and there will be a few of those mentioned later in this post. Paying for online courses does mean that you can get the benefit of curation and an added assurance of quality in what appears to be a growing market.
The variation in quality can dog the YouTube approach, and it also can be tricky to find something good, even if the platform does suggest new videos based on what you have been watching. Much of what is found there does take the form of webinars from the likes of the Why R? Foundation, Posit or the NHSR Community. These can be useful, and there are shorter videos from such providers as the Association of Computing Machinery or SAS Users. These do help more if you already have some knowledge about the topic area being discussed, so they may not make the best starting points for someone who is starting from scratch.
Of course, working your way through a good book will help, and it is something that I have been known to do, but supplementing this with one or more video courses really adds to the experience and I have done a few of these on LinkedIn. That part of the professional platform came from the acquisition of Lynda.com and the topic areas range from soft skills like time management through to computing skills courses with R, SAS and Python seeing coverage among the data science portfolio. Even O’Reilly has ventured into the area in an expansion from the book publishing activities for which so many of us know the organisation.
The available online instructor community does not stop at the above since there are others like Baeldung, Udacity, Programiz, Udemy, Business Science and Datanovia. Some of these tend towards online education provision that feels more like an online university course and those are numerous as well as you will find through Data Science Central or KDNuggets. Both of these earn income from advertising to pay for featured blog posts and newsletters, while the former also organises regular webinars and was my first port of call when I became curious about the world of data science during the autumn of 2017.
My point of approach into the world of online training has been as a freelance information professional needing to keep up to date with a rapidly changing field. The mix of content that is both free of charge and that which attracts a fee is one that can work. Both kinds do complement each other while possessing their unique advantages and disadvantages. The need to continually expand skills and knowledge never goes away, so it is well worth spending some time working what you are after, since you need to be sure that any training always adds to your own knowledge and skill level.